Applied Geography

Archive for the ‘Imagery’ Category

Spatial and Temporal Analysis of Forest Cover Changes in the Bartin Region of Northwestern Turkey

In Environmental Science, Imagery, Spatial Analysis, Temporal Analysis on September 1, 2010 at 7:18 am

African Journal of Biotechnology, Vol. 9 (35), pp. 5676-5685, 30 August 2010

Ayhan Atesoglu and Metin Tunay

“This study analyzed the changes in the forest areas in Bartin province of Turkey and the surrounding areas using remote sensing data and GIS techniques. Three Landsat Thematic Mapper (TM) images of the study region, recorded in 1987, 1992, and 2000, were utilized. The main land-use characteristics were derived using a maximum-likelihood classification technique. The remotely sensed data allows monitoring of current land use/land cover and detection of temporal changes. Furthermore, a temporal and spatial comparison of the classified image can be performed using Geographical Information System (GIS) to show land-use changes. GIS analysis of the classification results based on reference datasets revealed that the area covered by forests decreased significantly and that the amount of the reduction corresponded mainly to increased agricultural land use. The reasons for this negative impact on forested areas were growth in the region’s population, and expansion of agricultural areas and settlements. The classification results also showed that past, afforestation work had been successful.”

Hyperspectral Data Classification using Geostatistics and Support Vector Machines

In GIScience, Imagery, Statistics on August 24, 2010 at 8:24 am

Remote Sensing Letters, Volume 2, Issue 2 2011 , pages 99 – 106

S. Bahria; N. Essoussi; M. Limam

“Hyperspectral imagery combined with spatial features holds promise for improved remote sensing classification. In this letter, we propose a method for classification of hyperspectral data based on the incorporation of spatial arrangement of pixel’s values. We use the semivariogram to measure the spatial correlation which is then combined with spectral features within the stacked kernel support vector machine framework. The proposed method is compared with a classifier based on first-order statistics. The overall classification accuracy is tested for the AVIRIS Indian Pines benchmark dataset. Error matrices are used to estimate individual class accuracy. Statistical significance of the accuracy estimates is assessed based on the kappa coefficient and z-statistics at the 95% confidence level. Empirical results show that the proposed approach gives better performance than the method based on first-order statistics.”

Influence of Topography on the Endemicity of Kala-azar: A Study based on Remote Sensing and Geographical Information System

In GIS, Imagery on August 24, 2010 at 6:57 am

Geospatial Health, Volume 4, Number 2, May 2010, Pages 155-165

Gouri S. Bhunia,  Shreekant Kesari,  Algarsamy Jeyaram,  Vijay Kumar,  Pradeep Das

“Kala-azar, a fatal infectious disease in many Indian states, particularly in Bihar, West Bengal, Uttar Pradesh, and Jharkhand, is caused by the protozoan parasite Leishmania donovani and transmitted by the sandfly vector Phlebotomus argentipes. The vector is distributed all over the country but the disease is confined to particular zones since before the last century. In this study, parameters such as altitude, temperature, humidity, rainfall and the normalized difference vegetation index (NDVI) were investigated for correlation with the distribution of the disease in the northeastern corner of the Indian sub-continent. Data analysis on Kala-azar prevalence during the period 2005-2007 in the four states showed that the highest prevalence was below 150 m of altitude with very few cases located above the 300 m level. Low NDVI value ranges (0.03-0.015) correlated with a high occurrence of the disease. The maximum temperatures in the affected sites varied between an upper level of 25-29°C and a minimum of 16-20°C. The rainfall in these areas fluctuated between 1154 and 1834 mm. As the disease showed a high correlation with the prevailing topographic conditions, an attempt was made to improve the relative strength of the approach to predict the potential for endemicity of leishmaniasis by introducing satellite imagery complemented with a geographical information system database.”

Estimating Sub-pixel to Regional Winter Crop Areas using Neural Nets

In Imagery on August 19, 2010 at 9:41 am

ISPRS Technical Commission VII Symposium: 100 Years ISPRS – Advancing Remote Sensing Science, 05-07 July 2010, Vienna, Austria

Clement Atzberger, and Felix Rembold

“The work aimed at testing a methodology which can be applied to low spatial resolution satellite data to assess inter-annual crop area variations on sub-pixel to regional scales. The methodology is based on the assumption that within mixed pixels land cover variations are reflected by changes in the related hyper-temporal profiles of the Normalised Difference Vegetation Index (NDVI). We evaluated if changes in the fractional winter crop coverage are reflected in changing shapes of annual NDVI profiles and can be detected by using neural networks. The neural nets were trained on reference data obtained from high resolution Landsat TM/ETM images. The proposed methodology was applied in a study region in central Italy to estimate winter crop areas between 1988 and 2002 from 1 km resolution NOAA-AVHRR profiles and additional ancillary data readily available (CORINE land cover). The accuracy of the estimates was assessed by comparison to official agricultural statistics using a bootstrap approach. The method showed promise for estimating crop area variation on sub-pixel level (cross-validated R2 between 0.7 and 0.8) to regional scales (normalized RMSE: 10%). The network based approach proved to have a significantly higher forecast capability than other methods used previously for the same study area.”

Call For Papers: IJAGR Special Issue on Spatial and Temporal Data Analysis

In GIS, Imagery, Modeling, Spatial Analysis, Temporal Analysis, Visualization on August 18, 2010 at 9:31 am

The Spatial Analysis and Modeling (SAM) Specialty Group of the Association of American Geographers (AAG) is currently soliciting research papers to be published in a special issue of International Journal of Applied Geospatial Research (IJAGR). We specifically look for papers that illustrate recent advances in spatial and temporal data analysis to address geographical issues, as well as related research in spatial data mining. Authors who are interested in contributing to the special issue should submit a letter of intent that describes the main content of paper by September 15, 2010. The guest editors will decide if the paper fits the scope of the special issue and invite the authors of selected papers to submit a full paper by January 15, 2011.

Many geographic phenomena occur in both space and time. Methods for spatial and temporal analyses have been increasingly important for spatial studies due to the rich datasets that have been made available for a wide range of applications. These methods are essential in applications such as spatial patterns of traffic accidents, infant mortality variations, landscape pattern changes, and unemployment rate changes, often over multiple time periods. We welcome papers in all relevant research areas including, but not limited to, transportation, urban and environment planning, crime, health, economics, statistics, and GIS.

This special issue aims at introducing the spatial and temporal data analysis to the GIScience/SAM/IJAGR audience.

Topics to be discussed in this special issue include (but are not limited to) the following:

  • Applications of tools such as GIS or remote sensing for space-time analysis
  • Multilevel modeling
  • Panel/Longitudinal data analysis
  • Space and time model
  • Space-time analyses
  • Space-time clusters
  • Spatial data mining
  • Spatial variation in temporal trends
  • Spatio-temporal processes
  • Spatio-temporal representation/geovisualization

Researchers and practitioners who are interested in contributing to the special issue should submit a letter of intent that describes the main content of paper by September 15, 2010. The guest editors will decide if the paper fits the scope of the special issue and invite the authors of selected papers to submit full papers for this special theme issue on Spatial and Temporal Data Analysis on or before January 15, 2011. All submissions must be original and may not be under review by another publication. INTERESTED AUTHORS SHOULD CONSULT THE JOURNAL’S GUIDELINES FOR MANUSCRIPT SUBMISSIONS at http://www.igi-global.com/development/author_info/guidelines submission.pdf. All submitted papers will be reviewed on a double-blind, peer review basis. Papers must follow APA style for reference citations.

All submissions and inquiries should be directed to the attention of:

Changjoo Kim (changjoo.kim@uc.edu)
Eric Delmelle (Eric.Delmelle@uncc.edu)
Ningchuan Xiao (xiao.37@osu.edu)
Guest Editors

Research on the Texture Extraction of QuickBird Image Based on the Geostatistics

In GIScience, Imagery, Statistics on August 17, 2010 at 6:56 am

2010 Third International Conference on Information and Computing, vol. 1, pp. 133-136

Wuxi, Jiang Su, China

“The QuickBird phantom was the multi-spectrum resolution has achieved Mi Ji one of commercial satellites, might supply the spectrum information, the structure information and the time information for the user, but in the actual application by the spectrum, the time information were many, the structure information were few, but the structure information’s application increased the remote sensing phantom classified precision. The structure information’s extraction uses in statistics variation function method, when the computation variation function uses the overlaid windows, the size is the 5X5 size, the length of stride is 1. But the QuickBird phantom’s multi-spectra have 4 wave bands, to reduce the data redundancy, before its extraction texture uses the main ingredient transformation, the first host ingredient information content is 67.04%, the second host ingredient is 32.45%, one, two main ingredient sum total is 99.49%, according to the above only withdraws the main ingredient 1, 2 image texture. Is best after the quite absolute deviation function texture.”

Urban Road Tracking by Fusion of SVDD and Region Adjacency Graphs from VHR Imagery

In GIScience, Imagery on August 16, 2010 at 7:27 am

ISPRS Technical Commission VII Symposium: 100 Years ISPRS – Advancing Remote Sensing Science, 05-07 July 2010, Vienna, Austria

Zhengjun Liu, Xiangguo Lin, Jixian Zhang, and Pengxian Pu

“Road surfaces are seriously disturbed by a variety of noises on the very high resolution (VHR) remotely sensed imagery in urban areas, e.g., abrupt geometric deformation and radiometric changes caused by sharp turning, shadows of tall buildings, and appearance of vehicles, which leads to frequent failures for most of current road tracking methods. In this paper, a semi-automatic method is proposed for urban road tracking on VHR imagery. Initially, a human operator inputs three seed points on a selected road, and then necessary information, such as road direction, road width, start point, and a reference template, is automatically derived. The automatic tracking is consequently triggered. During the process, the reference template is moved to generate several target templates. For each target template, a binary template is derived by classifying the target template using support vector data description (SVDD). Subsequently, region adjacency graphs (RAG) is used to eliminate the small disturbing features on the road surfaces in each binary template, which is helpful to search the optimal road centerline points. The above tracking process is repeated until a whole road is completed. Two VHR images were used for the test. The preliminary results show that our method can extract roads more robustly than existing least-squares template matching method in urban areas.”

Using Remote Sensing and GIS Technologies to Estimate Grass Yield and Livestock Carrying Capacity of Alpine Grasslands in Golog Prefecture, China

In Environmental Science, GIS, Imagery on August 16, 2010 at 6:52 am

Pedosphere, Volume 20, Issue 3, June 2010, Pages 342-351

Long YU, Li ZHOU, Wei LIU, and Hua-Kun ZHOU

“Remote sensing data from the Terra Moderate-Resolution Imaging Spectroradiometer (MODIS) and geospatial data were used to estimate grass yield and livestock carrying capacity in the Tibetan Autonomous Prefecture of Golog, Qinghai, China. The MODIS-derived normalized difference vegetation index (MODIS-NDVI) data were correlated with the aboveground green biomass (AGGB) data from the aboveground harvest method. Regional regression model between the MODIS-NDVI and the common logarithm (LOG10) of the AGGB was significant (r2 =0.51, P < 0.001), it was, therefore, used to calculate the maximum carrying capacity in sheep-unit year per hectare. The maximum livestock carrying capacity was then adjusted to the theoretical livestock carrying capacity by the reduction factors (slope, distance to water, and soil erosion). Results indicated that the grassland conditions became worse, with lower aboveground palatable grass yield, plant height, and cover compared with the results obtained in 1981. At the same time, although the actual livestock numbers decreased, they still exceeded the proper theoretical livestock carrying capacity, and overgrazing rates ranged from 27.27% in Darlag County to 293.99% in Baima County. Integrating remote sensing and geographical information system technologies, the spatial and temporal conditions of the alpine grassland, trend, and projected stocking rates could be forecasted for decision making.”

Evaluating a 50 Year Record of Forest Encroachment in Rocky Mountain Alpine Meadows

In Environmental Science, Imagery on August 10, 2010 at 8:47 am

95th Ecological Society of America (ESA) Annual Meeting, Pittsburgh, PA, 01-06 August 2010

Sunita Yadav and Stephen F. Matter

“The potential impact of global warming is predicted to be strongest at higher altitude and latitude. Alpine meadows are already limited in their spatial extent and are especially vulnerable to rising temperatures which may cause them to retract substantially or completely disappear due to invasion by woody forest species. It is generally believed, that during periods of warmer than average temperatures, tree-line increases in altitude. In our study, we analyzed the record from 1952 to 2009 of forest encroachment in the Alberta Rocky Mountains. We quantified the extent of meadow areas along two ridges in the front ranges of the Canadian Rockies to explore land cover change. Historical aerial photographs, image processing, and geographic information systems (GIS) tools were used to quantify the extent of forest encroachment over the past 50 years. Using an orthorectified base map, we co-registered the aerial photographs and classified forest and meadow areas. Actual areal extent was calculated in a GIS program.  The results clearly show a significant decrease in meadow area with the majority of the reduction occurring within the past two decades. The consequences of such dramatic landscape change have cascading effects on meadow populations leading to reduced overall species diversity and smaller individual species populations due to fragmentation and isolation. Further work on this system involves studying the effects of this fragmentation on the population structure of a Sedum species occurring in these meadows.”

ITT Launches Academic Partnership Program to Support Higher Education in Image and Data Analysis

In Education, Imagery on August 4, 2010 at 1:04 pm

Colleges and Universities will partner with ITT to make advanced image and data analysis technology readily available to students in preparation for the workforce.

ITT Visual Information Solutions, a subsidiary of ITT Corporation (NYSE: ITT), announced a new academic partnership program designed to help educators foster students’ careers in disciplines involving geospatial imagery and complex data analysis. The program, entitled “ITT Innovation Centers,” is available to any college or university in the United States and Canada offering courses that use image and data analysis software as a core component of the curriculum. Under the program, ITT will provide its partners with a number of educational benefits, including access to the company’s products for image and data analysis, ENVI and IDL software, for use in classroom instruction.  Other advantages include access to professional training resources, consultations with ITT representatives on course structure and curriculum, and the opportunity to preview and give feedback on future releases of ENVI and IDL.

As partners in the program, participating academic institutions will contribute to advances in data and image analysis within the ENVI and IDL product lines, and provide curriculum, research, papers, and other resources of value to the greater academic community.

“ITT is committed to supporting academic endeavors that further the growth of fields that help advance science and improve the human condition.” said Nigel Brown, director of academic programs for ITT Visual Information Solutions.  “By providing access to leading software technologies and curriculum and giving our academic partners input into our product development, we are able to contribute in ways that not only support these disciplines, but also advance the careers of professionals nationwide.”

ITT has been a significant contributor to academic initiatives since its flagship data analysis software product, IDL, was developed in 1977.  Both IDL and ENVI, ITT’s comprehensive software product for analyzing geospatial imagery, have been widely adopted across commercial, government and academic disciplines for their value in extracting meaningful information from data and imagery.  Both products are used extensively today in college and university programs around the world.

For more information about ITT Innovation Centers, visit www.ittvis.com/academic.

[Source: ITT VIS press release]

Analysis of Spatial and Temporal Evolution of the NDVI on Vegetated and Degraded Areas in the Central Spanish Pyrenees

In Environmental Science, Imagery, Spatial Analysis, Temporal Analysis on August 4, 2010 at 9:57 am

ISPRS Technical Commission VII Symposium: 100 Years ISPRS – Advancing Remote Sensing Science, 05-07 July 2010, Vienna, Austria

Luis Carlos Alatorre, and S. Beguería

“The temporal evolution of vegetation activity on various land cover classes in the Spanish Pyrenees was analyzed. Two time series of the normalized difference vegetation index (NDVI) were used, corresponding to March (early spring) and August (the end of summer). The series were generated from Landsat TM and Landsat ETM+ images for the period 1984-2007. An increase in the NDVI in March was found for vegetated areas, and the opposite trend was found in both March and August for degraded areas (badlands and erosion risk areas). The rise in minimum temperature during the study period appears to be the most important factor explaining the increased NDVI in the vegetated areas. In degraded areas, no climatic or topographic variable was associated with the negative trend in the NDVI, which may be related to erosion processes taking place in these regions.”

Seminar Spotlights How to Visualize and Analyze Imagery

In ESRI, Education, GIS, Imagery on August 4, 2010 at 7:58 am

Free Training Provides Overview of the New Imagery Tools Available in ArcGIS 10

Esri’s ArcGIS 10 technology provides new capabilities to quickly access, visualize, process, analyze, and exploit all forms of imagery. To familiarize users with these tools, Esri will host the free online seminar, Visualizing and Analyzing Imagery in ArcGIS 10, later this month.

The seminar will air live at www.esri.com/lts on Thursday, August 12, at 9:00 a.m., 11:00 a.m., and 3:00 p.m. Pacific daylight time.

Attendees will see a demonstration of the new Image Analysis window and process functions. They will learn how to quickly access common image enhancement and display tools including clipping, masking, dynamic range adjustment, and gamma and stretch adjustments. The Image Analysis window is also the platform for accessing new, on-the-fly image processing techniques such as filtering, Normalized Difference Vegetation Index (NDVI), pan sharpening, and creating composite bands. They will also be given a demonstration of the new Image Classification toolbar, which provides a single location for classifying imagery.

Attendees will also learn about

  • Creating viewsheds and shaded relief maps from digital elevation models
  • Using on-the-fly processing to orthorectify and pan sharpen images
  • Using enhanced images as input into standard geoprocessing tools

This live training seminar is geared toward geographic information system (GIS) and image analysts who visualize, interpret, and analyze imagery and for administrators who manage large volumes of images and need to make them accessible to others.

A broadband Internet connection and an Esri Global Account are needed to participate in the training seminar. Creating a global account is easy and free: visit www.esri.com/lts, click Login, and register your name and address. A few weeks after the live presentation, this seminar will be archived and available for viewing on the Esri Training Web site.

[Source: Esri press release]

The Effect of Biomass and Scanning Angle on the Laser Pulse Transmittance

In Environmental Science, GIScience, Imagery on August 3, 2010 at 6:14 am

ISPRS Technical Commission VII Symposium: 100 Years ISPRS – Advancing Remote Sensing Science, 05-07 July 2010, Vienna, Austria

Eero Ahokas, Juha Hyyppä, H. Kaartinen, Antero Kukko, Sanna Kaasalainen, and Anssi Krooks

“During the last decade, there have been numerous scientific studies verifying the accuracy of digital elevation models (DEM) derived from airborne laser scanning (ALS). Since ALS has increasingly been used for nationwide digital elevation model data acquisition, optimizing ALS acquisition parameters is a topic of interest to national land surveys. In particular, the effect of the scanning angle and biomass on elevation-model accuracy needs further study in heavily-forested areas. The elevation-model accuracy is affected by, for example, the number of pulses hitting the ground, footprint size, terrain slope and, especially, vegetation. In order to better understand the effect of the biomass and scanning angle on the penetration rate of ALS signal through canopy and give further support to ALS studies, especially for scanning angles beyond 15 degrees of the nadir point, we conducted an indoor experiment using small spruce trees to represent forest canopy. The indoor experiment allowed us to measure the biomass reference accurately.  We used manual thinning to produce various levels of biomass and scissor lift as the carrying platform. We measured the weight of every tree and the total biomass of trees after each thinning phase. We removed the material homogeneously from the trees, starting from the latest shoots. We used a FARO laser scanner in the experiment and attached it to the scissor lift. We scanned the experimental plot from four altitudes (about 3, 5, 7 and 9 m) and at six biomass levels (about 0, 6, 9, 14, 20 and 25 kg). The results show that signal transmittance through spruce trees is a function of biomass and scanning angle, but that the scanning angle only has a minor effect on the results. Biomass is the major parameter in determining the quality of the elevation model. While the results require further airborne experiments to be fully confirmed, they do imply that a scanning angle greater than 15 degrees can be applied in regions having low and moderate biomass, and due to the significant effect of the biomass on the transmittance, the airborne scanning missions must be carefully specified in heavily-forested terrain. We also found that terrestrial laser scanning experiments performed in an indoor laboratory-type setting yielded a relatively good understanding of the basic behaviour of and interaction between the target and laser scanning rather easily, but that it will be considerably more difficult to obtain similar results in a real-life experiment due to limited accuracy when collecting the reference data.”

Detecting Spatiotemporal Change of Land Use and Landscape Pattern in a Coastal Gulf Region, Southeast of China

In GIS, Imagery, Spatial Analysis, Temporal Analysis on July 29, 2010 at 9:00 am

Environment, Development and Sustainability, Volume 12, Number 1 / February, 2010

Jinliang Huang, Jie Lin, and Zhenshun Tu

“Geographic information system (GIS), remote sensing (RS), gradient analysis, and landscape pattern metrics were coupled to quantitatively characterize the spatiotemporal change of land use and landscape pattern over the period 1988–2007 in a coastal gulf region, southeast China. The results obtained show an increase in cropland, buildup land, and aquiculture area and decrease in orchard, woodland, and beach area during 1988–2007. Landscape fragmented processes were strengthened and landscape pattern structure became more complicated in the last two decades in Luoyuan gulf region. The dynamics intensity of landscape pattern is stronger during 2002–2007 than that during 1988–2002. Spatial difference of urban–rural landscape pattern can be detected distinctively in two transects in terms of landscape metrics. Urbanization processes and the policy developed to transfer seawater into buildup land are two driving forces leading to the spatiotemporal change of landscape pattern in Luoyuan gulf region in the last two decades.”

Landscape Pattern Changes of Desert Oasis Wetlands in the Middle Reach of the Heihe River, China

In Environmental Science, GIS, Imagery on July 29, 2010 at 8:21 am

Arid Land Research and Management, Volume 24, Issue 3 July 2010, pages 253-262

Shoubo Li and Wenzhi Zhao

“Desert oasis wetlands are distributed along the Heihe River, especially in lowland oases along the middle reach of the river, in northwestern China. Landscape maps of the wetlands in 1990, 1995, 2000, and 2006 were compiled based on data collected from Landsat TM and ETM+ images using GIS and analyzed in July 2008. Various landscape indices were calculated using the landscape structure analysis software FRAGSTATS, at both class and landscape levels. The results showed that floodplain wetland is the dominant type of wetlands in the middle reach of the Heihe River, followed by non-forested peatland, then river and reservoir wetland, with the proportion of shrub-dominated wetland low. During these 16 years, the area of wetlands in our study area decreased by 38.4%, or 107.8 km2. The major type of wetland lost in the study area was non-forested peatland during the first five years, but floodplain wetland since then. The landscape pattern shows that the fragmentation level is very high, especially in the floodplain wetlands: the patch density increased by 154% during the study period. It is clear that the wetlands along the middle reach of the Heihe River have become increasingly fragmental during the past 16 years.”

Geostatistical Analysis of Karst Landscapes

In GIS, Geography, Imagery, Statistics on July 23, 2010 at 6:27 am

Electronic Journal of Geotechnical Engineering, Vol. 15, 2010

Omar Al-Kouri, Husaini Omar, Mohammed Abu-Shariah, Ahmad Rodzi Mahmu, and Shattri Mansor

“Nowadays, geographical information system (GIS) and remote sensing are emerging as powerful techniques widely applicable in natural resource management and development virtual models. Recent developments in remote sensing, aerial photography and GIS make it possible to detect changes and devise strategies based on these changes. The study focuses on using aerial photography for the detection of changes and effects of mining on geomorphology using the ArcGIS9 extension, Geostatistical Analyst. In addition, the distinctive surface topography of karst landscapes can be characterized in order to compare them with non-karst landscapes, and to determine geological and/or climatic conditions that are responsible for the observed terrain of Kinta Valley Limestone formation at Perak, Malaysia. Geostatistical analyses of the karstic terrain are used in order to distinguish between karst and non-karst area and karst area to observe the variation from the deterministic sample. In contrast, if the range is less, that means the average distance between two points that are similar in height is less and therefore there is more variation in the area. The average range for karst area is 435, while the average range for non-karst area is 690 meters. The difference between the major range and minor range which indicates the degree of anisotropy is more for the karst area and this is an indicator of more variation in spatial structure and autocorrelation of the karst elevation.”

3-D Visualizations of Coastal Bathymetry by Utilization of Airborne TOPSAR Polarized Data

In Imagery, Visualization on July 21, 2010 at 7:35 am

International Journal of Digital Earth, Volume 3, Issue 2 June 2010 , pages 187 – 206

Maged Marghany; Arthur P. Cracknell; and Mazlan Hashim

“Multi-frequency C and L bands in the TOPSAR data have been utilized to reconstruct three-dimensional (3-D) bathymetry pattern. The main objective of this study is to utilize fuzzy arithmetic to reduce the errors arising from speckle in synthetic aperture radar (SAR) data when constructing ocean bathymetry from polarized SAR data. In doing so, two 3-D surface models, the Volterra algorithm and a fuzzy B-spline (FBS) algorithm, which construct a global topological structure between the data points, were used to support an approximation to the real surface. Volterra algorithm was used to express the non-linearity of TOPSAR data intensity gradient based on the action balance equation (ABC). In this context, a first-order kernel of Volterra algorithm was used to express ABC equation. The inverse of Volterra algorithm then performed to simulate 2-D current velocities from CVV and LHH band. Furthermore, the 2-D continuity equation then used to estimate the water depth. In order to reconstruct 3-D bathymetry pattern, the FBS has been performed to water depth information which was estimated from 2-D continuity equation. The best reconstruction of coastal bathymetry of the test site in Kuala Terengganu, Malaysia, was obtained with polarized L and C bands SAR acquired with HH and VV polarizations, respectively. With 10 m spatial resolution of TOPSAR data, bias of -0.004 m, the standard error mean of 0.023 m, r 2 value of 0.95, and 90% confidence intervals in depth determination was obtained with LHH band.”

Comparative Study of Land Cover using Multi-temporal Satellite Images

In Imagery, Temporal Analysis on July 20, 2010 at 9:11 am

3rd International Conferecne on Cartography and GIS

15-20 June, 2010, Nessebar, Bulgaria

Borislav Marinov and Margarita Mondeshka

“The comparative study of land cover and soil status are provided using space images with middle resolution. The Landsat TM+ and SPOT 5 images are included in analysis. The unsupervised and supervised classifications are applied for determination of different types of land cover. The terrain investigations are made by taking and analysing the soil samples for typical soil types presenting in the area of investigation. The analysed images are taken at different time moments in autumn and spring seasons to avoid the influence of crop stage of vegetation and snow coverage. The influence of used channels and space resolution of images on the reliability and accuracy of classified areas are investigated. The improvement of interpretation is established in the case of applying the combination of unsupervised and supervised classification. The recommendations are formulated for appropriate properties of utilised space images. The diversity and amount of terrain investigations are suggested for obtaining the reliable and representative results.”

Simulation of the Snowmelt Runoff Contributing Area in a Small Alpine Basin

In ESRI, Environmental Science, GIS, Imagery on July 16, 2010 at 8:07 am

Hydrology and Earth System Sciences, 14, 1205–1219, 2010

C. M. DeBeer and J. W. Pomeroy

“Simulation of areal snowmelt and snowcover depletion over time can be carried out by applying point-scale melt rate computations to distributions of snow water equivalent (SWE). In alpine basins, this can be done by considering these processes separately on individual slope units. However, differences in melt timing and rates arise at smaller spatial scales due to the variability in SWE and snowpack cold content, which affects the timing of melt initiation, depletionof the snowcover and spatial extent of the snowmelt runoff contributing area (SRCA). This study examined the effects of variability in SWE, internal energy and applied melt energy on melt rates and timing, and snowcover depletion in a small cold regions alpine basin over various scales ranging from point to basin. Melt rate computations were performed using a physically based energy balance snowmelt routine (Snobal) in the Cold Regions Hydrological Model (CRHM) and compared with measurements at 3 meteorological stations over a ridge within the basin. At the point scale, a negative association between daily melt rates and SWE was observed in the early melt period, with deeper snow requiring greater energy inputs to initiate melt. SWE distributions over the basin (stratified by slope) were measured using snow surveys and repeat LiDAR depth estimates, and used together with computed melt rates to simulate the areal snowcover depletion. Comparison with observations from georeferenced oblique photographs showed an improvement in simulated areal snowcover depletion curves when accounting for the variability in melt rate with depth of SWE in the early melt period. Finally, the SRCA was characterized as the product of the snowcovered area and the fraction of the SWE distribution undergoing active melt and producing an appreciable runoff quantity on each slope unit. Results for each slope were then aggregated to give the basin scale SRCA. The SRCA is controlled by the variability of melt amongst slope units and over individual SWE distributions, the variability of SWE, and the resulting snowcover depletion patterns over the basin.”

Application of Fuzzy Models for the Monitoring of Ecologically Sensitive Ecosystems in a Dynamic Semi-arid Landscape from Satellite Imagery

In Environmental Science, Imagery, Modeling on July 7, 2010 at 9:06 am

Engineering Computations, 2010, Volume 27, Issue 1, Pages 5 – 19

Meng-Lung Lin and Cheng-Wu Chen

“Purpose – The purpose of this paper is to better understand landscape dynamics in arid and semi-arid environments. Land degradation has recently become an important issue for land management in western China. The oasis ecosystem is especially sensitive to environmental disturbances, such as abnormal/extreme precipitation events, variations in the water supply from the upper watersheds, fluctuations in temperature, etc. Satellite remote sensing of terrestrial ecosystems can provide us with the temporal dynamics and spatial distributions of green cover over large areas of landscape. Seasonal green cover data are especially important in assessing landscape health (e.g. desertification, rate of urban sprawl, natural disturbances) in arid and semi-arid regions. In this study, green cover data are derived from vegetation indices retrieved from moderate resolution imaging spectroradiometer (MODIS) sensors onboard the satellite Terra.

“Design/methodology/approach – Satellite images recorded during the period from April 2000 to December 2005 are analyzed and the spatial distribution and temporal changes of the Ejin Oasis quantified.

“Findings – This study shows that it is possible to derive important parameters linked to landscape sensitivity from MODIS and the derived imagery, such as normalized difference vegetation index (NDVI) time-series data. Such a MODIS-based time-series monitoring system is particularly useful in arid and semi-arid environments. The results of landscape sensitivity analysis prove the effectiveness of the method in assessing landscape sensitivity from the years 2001-2005.

“Practical implications – The novel strategy used in this investigation is based on the T-S fuzzy model, which is in turn based on fuzzy theory and fuzzy operations.

“Originality/value – Simulation results based on fuzzy models will help to improve the monitoring techniques used to evaluate land degradation and to estimate the newest tendency in landscape green cover dynamics in the Ejin Oasis.”

Abraham Anson Memorial Scholarship for Geospatial Science and Technology

In Education, Imagery on June 30, 2010 at 1:16 pm

The American Society For Photogrammetry and Remote Sensing Scholarship  is dedicated to encourage students to pursue education in the areas of geospatial science or technology associated with remote sensing, photogrammetry, surveying and mapping.  The applicant is required to be enrolled or anticipating to enroll in a United States university or institution in the field of geospatical science, surveying and mapping, or a related field.   The applicant is required to submit with the application a list of all relevant courses taken, a statement of work experience including technical papers, special projects, internships, and courses taught that may reflect the student’s abilities in the field.  For more detailed information and online application, please visit the following Web site:  http://www.asprs.org/membership/scholar.html.

Academic Disciplines/Professional Aspirations: Engineering/Technology; Surveying; Surveying Technology, Geographical Information Science, or Cartography.

Award: This scholarship is for use during freshman, sophomore, junior, or senior years.  This scholarship is not renewable.  Number: The number of scholarships awarded is 1.  Amount: The amount of the scholarship awarded is $1,000.

Requirements for Eligibility: The applicant is required to be enrolled or anticipating to enroll at a four-year college or university.  This scholarship is accessible only to citizens of the United States.

Requirements for Application: Application, essay composition, school transcript, resume, and personal references. Deadline: December1.

U.S. Dept. of Interior Continues Leadership Role in Land Remote Sensing Under National Space Policy

In Imagery on June 30, 2010 at 11:18 am

The National Space Policy announced by the White House recognizes and endorses the Department of the Interior’s expertise and accomplishments in land imaging and remote sensing to advance global climate change research and provide data for science and natural resource management.

“The National Space Policy confirms Interior’s important role in land imaging and remote sensing in coordination with NASA,” said Interior Assistant Secretary Anne Castle. “The unbiased, comprehensive data this program provides is vital to our efforts to better understand and manage land, water, and our natural resources. We look forward to working with government agencies at all levels — Federal, State, local and tribal —to promote a broad, public understanding of land and water conditions in our Nation and around the globe.”

“Land remote sensing is a crucial tool in our efforts to develop broad, effective, holistic approaches to both mitigate and adapt to the environmental challenges of our day,” said Castle, who oversees Interior’s Water and Science agencies, including the U.S. Geological Survey. “In addition, remote sensing has critical event-specific uses, for example, in closely monitoring the BP oil spill in the Gulf of Mexico and establishing baseline and post-spill conditions.”

Since 1966, Interior has managed science data operations and applications development for Landsat and other national land imaging systems from its U.S. Geological Survey Earth Resources Observation and Science Center in Sioux Falls, SD. The Department currently operates Landsats 5 and 7 and is developing the Landsat Data Continuity Mission with NASA for launch in FY 2013. The Administration is currently discussing plans for Landsat 9.

With its historical consistency, continuous global coverage, and very high quality of data, Landsat has become a vital tool worldwide for understanding scientific issues related to land use and natural resources. International applications of Landsat data have become widespread for use in agriculture, forestry, mapping, land and water assessments and climate change study.

The Department of the Interior, through the U.S. Geological Survey, facilitates access by U.S. civil agencies to national security satellite data when this data can be used for environmental assessments and disaster management. The Landsat series of satellites also is considered a cornerstone of U.S. space cooperation with foreign nations. More than 20 nations on six continents collaborate in operating local receiving stations for Landsat data on behalf of their continental regions.

On behalf of the Department, USGS publishes the entire 38-year Landsat archive over the Internet at no cost to users. In the past two years, more than 2 million current and archived images taken by Landsat have been downloaded by users throughout the world.

[U.S. Department of the Interior press release]

Tidal Estuary Width Convergence: Theory and Form in North Australian Estuaries

In Environmental Science, GIS, Imagery on June 25, 2010 at 8:31 am

Earth Surface Processes and Landforms, Volume 35 Issue 7, Pages 737 – 749

Gareth Davies and Colin D. Woodroffe

“In order to better understand the relations between tidal estuary shape and geomorphic processes, the width profiles of 79 tidal channels from within 30 estuaries in northern Australia have been extracted from LANDSAT 5 imagery using GIS. Statistics describing the shape and width convergence of individual channels and entire estuaries (which can contain several channels) are analysed along with proxies for the tidal range and fluvial inputs of the estuaries in question. The width profiles of most individual channels can be reasonably approximated with an exponential curve, and this is also true of the width profiles of estuaries. However, the shape of this exponential width profile is strongly related to the mouth width of the system. Channels and estuaries with larger mouths generally exhibit a more pronounced funnel shape than those with narrower mouths, reflecting the hydrodynamic importance of the distance over which the channel or estuarine width converges. At the estuarine scale, this convergence length also tends to be higher in estuaries which have larger catchments relative to their size. No clear relation between the estuarine width convergence length and tidal range could be discerned within the Northern Australian estuaries although, when these data are combined with data from other studies, a weak relationship emerges.”

Comparing Landcover Patterns in Tokyo, Kyoto, and Taipei using ALOS Multispectral Images

In Imagery, Science on June 23, 2010 at 12:31 pm

Landscape and Urban Planning, 2010

Wei-Chun Hung, Yen-Ching Chen, and Ke-Sheng Cheng

“Understanding the landcover pattern in a region is essential for landuse planning and resources management. In this study ALOS multispectral images were used to compare landcover patterns in three study areas, namely Tokyo, Kyoto, and Taipei, of different degrees of urbanization. From the results of landuse/landcover classification, Shannon diversity index at cell level was used for landcover pattern analysis. Existing landcover pattern of the three study areas were also compared by investigating cell distribution in a landcover coverage-ratio space. Both the landcover type richness and evenness are low in the Tokyo study area and built-up is the single dominant landcover type in almost all cells. In comparison, landcover patterns of the Kyoto and Taipei study areas are more diversified, with significant amount of cells having mixed and non-dominant landcover types. Kyoto is least urbanized and enjoys a good mixture of different landcover types. It was found that cell-average NDVI alone can be used for delineating areas of certain dominant landcover types. Implementation of such method does not require an a priori LULC classification, and thus is particularly useful when good training data for LULC classification are not available. An urbanization index which integrates the coverage ratio of built-up landcover type and the cell-average NDVI was proposed and used to explore the spatial variation of degree of urbanization. Area-average urbanization indices of the Tokyo, Kyoto, and Taipei study areas were calculated to be 0.91, 0.55, and 0.72, respectively. Such results are consistent with the results of qualitative evaluation using different landscape metrics.”

High-resolution Remote Sensing and GIS Techniques for Geobase Data Supporting Archaeological Surveys: A Case Study of Ancient Doliche, Southeast Turkey

In Environmental Science, GIS, Imagery, Social Science on June 22, 2010 at 9:20 am

Geoarchaeology, Volume 25, Issue 3, May/June 2010, Pages 352-374

Torsten Prinz, Benedikt Lasar, and Karl Peter Krüger

“The detection, surveying, and analysis of ancient settlement structures using remote sensing techniques offer a unique opportunity to quickly map the locations of archaeological objects in a relatively short time. High-resolution images contribute information to the documentation and spatial relation of these objects, especially if Geographic Information Systems (GIS) and Web-based applications are used. The aim of this study was to assess the potential use of satellite data and aerial imagesacquired by a remote-controlled balloon to generate geospatial data with a range of resolutions and information depths. The study area was Doliche, in the landscape of ancient Commagene (Turkey), where conventional flight campaigns are impossible or strongly restricted. Recently generated data sets (i.e., topographic maps, ortho-images, terrain models) were combined with field observations to derive ancient and modern landscape patterns and their possible relation to an assumed ancient procession road between the village Doliche (Dülük) and the nearby sanctuary of theRoman divinity Iupiter Dolichenus.”

Soil Carbon Stocks, Deforestation and Land-cover Changes in the Western Ghats Biodiversity Hotspot (India)

In Environmental Science, GIS, Imagery, Modeling on June 21, 2010 at 7:41 am

Global Change Biology, Volume 16, Issue 6, Date: June 2010, Pages: 1777-1792

DANNY LO SEEN, B. R. RAMESH, K. M. NAIR, MANUEL MARTIN, DOMINIQUE ARROUAYS, and GÉRARD BOURGEON

“Habitat loss and soil organic carbon (SOC) stock variations linked to land-cover change were estimated over two decades in the most densely populated biodiversity hotspot in the world, in order to assess the possible influence of conservation practices on the protection of SOC. For a study area of 88 484 km2, 70% of which lie inside the Western Ghats Biodiversity Hotspot (WGBH), land-cover maps for two dates (1977, 1999) were built from various data sources including remote sensing images and ecological forest maps. SOC stocks were calculated from climatic parameters, altitude, physiography, rock type, soil type and land-cover, with a modelling approach used in predictive learning and based on Multiple Additive Regression Tree. The model was trained on 361 soil profiles data, and applied to estimate SOC stocks from predictor variables using a Geographical Information System (GIS). Comparison of 1977 and 1999 land-cover maps showed 628 km2 of dense forests habitat loss (6%), corresponding to an annual deforestation rate of 0.44%. This was found consistent with other studies carried out in other parts of the WGBH, but not with FAO figures showing an increase in forest area. This could be explained by the different forest definitions used, based on ecological classification in the former, and on percentage tree cover in the latter. Unexpectedly, our results showed that despite ongoing deforestation, overall SOC stock was maintained (∼0.43 Pg). But a closer examination of spatial differences showed that soil carbon losses in deforested areas were compensated by sequestration elsewhere, mainly in recent plantations and newly irrigated croplands. This suggests that more carbon sequestration in soils could be achieved in the future through appropriate wasteland management. It is also expected that increasing concerns about biodiversity loss will favour more conservation and reinforce the already prevailing protective measures, thus further maintaining C stocks.”

Assessing the Impact of Extreme Climatic Events on Aspen Defoliation using MODIS Imagery

In Environmental Science, Imagery on June 18, 2010 at 8:21 am

Geocarto International, Volume 25, Issue 2 April 2010, pages 133 – 147

Nate Currit and Samuel B. St Clair

“Recent studies document the decline of quaking aspen across large geographic areas of North America. Extreme climatic events are possible contributors to the decline, and drought is often cited as an important driver of aspen phenology. Little is known, however, about the effects of spring freeze events on aspen phenology, even though such events are projected to occur more frequently in future. This study uses moderate resolution imaging spectrometer (MODIS) imagery to assess the spatial pattern and magnitude of damage to aspen forests during spring freeze and summer drought events that occurred in Utah in 2007. The analysis finds above normal Normalized Difference Vegetation Index (NDVI) in early spring, and below normal NDVI following the freeze event and during the summer drought. Aspen damage is concentrated in certain terrain classes, depending on the type of extreme climatic event. These findings suggest there are predictable patterns of aspen defoliation that identify aspen stands vulnerable to extreme climatic events.”

Impact of Aquaculture on Mangrove Areas in the Northern Pernambuco Coast (Brazil) using Remote Sensing and Geographic Information System

In Environmental Science, GIS, Imagery on June 17, 2010 at 1:02 pm

Aquaculture Research, Volume 41, Issue 6, Date: May 2010, Pages: 828-838

Ariana Silva Guimarães, Paulo Travassos, Pedro Walfir Martins E Souza Filho, Fabrício Dias Gonçalves, and Francisco Costa

“The conversion of mangrove areas into shrimp farming ponds has been indicated as the main activity responsible for the reduction in the area of this ecosystem along the northeastern coast of Brazil. The present study was conducted using remote sensing methods and a geographical information system with the aim of quantifying the participation of this activity in the reduction of the mangrove areas along the northern coast of the State of Pernambuco (northeast, Brazil), where shrimp farming has been implanted in last recent years. From 1973 to 2005, there was reduction of about 2.052 ha of mangrove, 197 ha of which were converted into shrimp ponds. Thus, the real contribution of shrimp farming to this reduction was just 9.6% of the total area. Other anthropogenic activities, such as agriculture, urban expansion and tourism, contributed greatly to the reduction in the mangrove areas along the northern coast of the State of Pernambuco.”

Soil Erosion Assessment using Geomorphological Remote Sensing Techniques: An Example from Southern Italy

In ESRI, Environmental Science, GIS, Imagery on June 16, 2010 at 7:28 am

Earth Surface Processes and Landforms, Volume 35, Issue 3, Date: 15 March 2010, Pages: 262-271

Sergio Lo Curzio and Paolo Magliulo

“The aim of this study is to assess of the distribution and map the geomorphological effects of soil erosion at the basin scale identifying newly-formed erosional landsurfaces (NeFELs), by means of an integration of Landsat ETM 7+ remotely sensed data and field-surveyed geomorphological data. The study was performed on a 228·6 km2-wide area, located in southern Italy. The study area was first characterized from a lithological, pedological, land-use and morpho-topographic point of view and thematic maps were created. Then, the georeferenced Landsat ETM 7+ satellite imagery was processed using the RSI ENVI 4.0 software. The processing consisted of contrast stretching, principal component analysis (PCA), decorrelation stretching and RGB false colour compositing. A field survey was conducted to characterize the features detected on the imagery. Particular attention was given to the NeFELs, which were located using a global positioning system (GPS). We then delimited the Regions of Interest (ROI) on the Landsat ETM 7+ imagery, i.e. polygons representing the ground-truth, discriminating the NeFELs from the other features occurring in the imagery. A simple statistical analysis was conducted on the digital number (DN) values of the pixels enclosed in the ROI of the NeFELs, with the aim to determine the spectral response pattern of such landsurfaces. The NeFELs were then classified in the entire image using a maximum likelihood classification algorithm. The results of the classification process were checked in the field. Finally, a spatial analysis was performed by converting the detected landsurfaces into vectorial format and importing them into the ESRI ArcViewGIS 9.0 software. Application of these procedures, together with the results of the field survey, highlighted that some objects in the classified imagery, even if displaying the same spectral response of NeFELs, were not landsurfaces subject to intense soil erosion, thus confirming the strategic importance of the field-checking for the automatically produced data. During the production of the map of the NeFELs, which is the final result of the study, these objects were eliminated by means of simple, geomorphologically-coherent intersection procedures in a geographic information system (GIS) environment. The overall surface of the NeFELs had an area of 22·9 km2, which was 10% of the total. The spatial analysis showed that the highest frequency of the NeFELs occurred on both south-facing and southwest-facing slopes, cut on clayey-marly deposits, on which fine-textured and carbonate-rich Inceptisols were present and displaying slope angle values ranging from 12° to 20°. The comparison of two satellite imageries of different periods highlighted that the NeFELs were most clearly evident immediately after summer tillage operations and not so evident before them, suggesting that these practices could have played an important role in inducing the erosional processes.”

An Integrated Approach for Prioritization of Reservoir Catchment using Remote Sensing and Geographic Information System Techniques

In Environmental Science, GIS, Imagery on June 16, 2010 at 6:28 am

Geocarto International, Volume 25, Issue 2 April 2010 , pages 149 – 168

Sreenivasulu Vemu and P. Udayabhaskar

“This study is aimed at evolving a watershed prioritization of reservoir catchment based on vegetation, morphological and topographical parameters, and average annual soil loss using geographic information system (GIS) and remote sensing techniques. A large multipurpose river valley project, Upper Indravati reservoir, situated in the state of Orissa, India, has been chosen for the present work. Watershed prioritization is useful to soil conservationist and decision makers. This study integrates the watershed erosion response model (WERM) and universal soil loss equation (USLE) with a geographic information system (GIS) to estimate the erosion risk assessment parameters of the catchment. The total catchment is divided into 15 sub-watersheds. Various erosion risk parameters are determined for all the sub-watersheds separately. Average annual soil loss is also estimated for the sub-watersheds using USLE. The integrated effect of all these parameters is evaluated to recommend the priority rating of the watersheds for soil conservation planning.”

Urban Growth Monitoring and Projection using Remote Sensing and Geographic Information Systems: A Case Study in the Twin Cities Metropolitan Area, Minnesota

In GIS, Imagery, Modeling, Social Science on June 15, 2010 at 10:45 am

Geocarto International, Volume 25, Issue 3 June 2010 , pages 213 – 230

Fei Yuan

“This study investigates urban growth dynamics from regional to local scales in the Twin Cities Metropolitan Area and demonstrates how metropolitan growth can be driven by policies. Urban change from 1975 to 2006 was detected using Landsat imagery. Future growth in 2030 was modelled based on two scenarios with or without regional development policies incorporated. City- or township-level growth was examined by a zonal analysis. Results show urban grew 126,700 ha from 1975 to 2006. The Markov-Cellular Automata model projected at least another 67,000 ha of urban growth from 2006 to 2030. When regional development policies were incorporated, homogeneous and compact growth patterns were predicted along the urban periphery; however, actual land supplies within the cities along the urban edge are facing challenges to accommodate the projected growth as large portions of suitable lands are located outside of the 2030 Municipal Urban Service Area boundary.”

Embodied Spatial Cognition: Biological and Artificial Systems

In GIScience, Imagery on June 14, 2010 at 7:13 am

Image and Vision Computing, Volume 27, Issue 11, 2 October 2009, Pages 1658-1670

Hanspeter A. Mallot and Kai Basten

“In this paper, we sketch out a computational theory of spatial cognition motivated by navigational behaviours, ecological requirements, and neural mechanisms as identified in animals and man. Spatial cognition is considered in the context of a cognitive agent built around the action–perception cycle. Besides sensors and effectors, the agent comprises multiple memory structures including a working memory and a longterm memory stage. Spatial longterm memory is modelled along the graph approach, treating recognizable places or poses as nodes and navigational actions as links. Models of working memory and its interaction with reference memory are discussed. The model provides an overall framework of spatial cognition which can be adapted to model different levels of behavioural complexity as well as interactions between working and longterm memory. A number of design questions for building cognitive robots are derived from comparison with biological systems and discussed in the paper.”

Azavea Awarded NSF Grant to Explore Use of Graphics Processing Units for Faster Geographic Data Processing

In GIS, GIScience, Imagery on June 10, 2010 at 9:34 am

Azavea (formerly Avencia), an award-winning geospatial analysis (GIS) software development company was awarded a Phase I Small Business Innovation Research (SBIR) grant of  $150,000 by the National Science Foundation to test the feasibility of using graphics processing units (GPUs) to substantially increase the performance of raster-based geographic information systems (GIS) software operations.

Most contemporary work in GIS involves one or more of three major types of activity: a) database development; b) spatial analysis and map production; and c) web-based map display.  Applications of GIS analysis technology are enormously diverse:  land planning, climate change modeling, assessing the impact of sea level rise, natural hazard risk assessment, military scenario planning, cell phone tower placement, and business siting, and many more.  Currently, these applications, which involve large amounts of geographic data-processing are usually tied to desktop workstations because of the significant amount of time, memory, and processing power required to execute the operations.  Azavea’s GPU project seeks to achieve substantial improvement in the performance of operations on raster-based image data.  The research team is optimistic about prospects for achieving processing speeds that are 10 to 20 times faster than current commercial technology and thereby enabling a whole new class of software for web and mobile devices.

In the past, GPUs have been used almost exclusively for video games and movies.  In recent years, however, scientists and researchers have begun to apply the geometric calculation capabilities of GPUs in fields ranging from fluid dynamics to medical imaging and oil exploration.  In this project, Azavea is using the OpenCL language, originally developed by Apple and now managed by Khronos Group, the nonprofit technology consortium.  With OpenCL™, Azavea hopes to create a geographic data-processing framework that can use GPUs from multiple manufacturers.

In this Phase I SBIR project, Azavea is focusing on new algorithms for several types of “Map Algebra” calculations.  Map Algebra is a widely-used conceptual framework for raster-based geospatial analysis in all of the contemporary desktop GIS tools.  It was originally developed by Dr. C. Dana Tomlin, who is also serving as a consultant on the GPU project.  In 2006, Azavea began development of DecisionTree®, a distributed geographic data processing system to accelerate one particular Map Algebraic operation.  That work proved to be quite successful and has since been applied to problems in economic development, elections, public health, and sustainability.  The GPU project is a natural outgrowth of that effort and one that builds on Azavea’s expertise in creating distributed software systems.

“This is one of the most promising efforts in which I’ve ever been involved in terms of both the fundamental algorithms being developed and their implications for real-world applications that will have a direct and profound impact on our use of geospatial data.” – Dr. C. Dana Tomlin, Professor and Co-director of the Cartographic Modeling Laboratory at the University of Pennsylvania.

Azavea’s GPU-Based Raster Processing Algorithms project is supported by the Small Business Innovation Research (SBIR) program of the National Science Foundation, Directorate for Engineering, Division of Industrial Innovations and Partnerships, Award Number (IIP-0945742).

This is the sixth time that Azavea has been awarded an SBIR grant.  Previous awards were from the U.S. Department of Education (Phase I), the U.S. Department of Agriculture (Phase I for two projects), and the National Science Foundation (Phase I and Phase II to develop HunchLab, Azavea’s geographic crime visualization, early warning and risk forecasting software).

[Source: Avazea press release]

UNH Scientist to Estimate Pre-Columbian Amazonian Population using Satellite Imagery

In Geography, Imagery, Social Science on June 10, 2010 at 8:58 am

University of New Hampshire tropical ecologist Michael Palace has been awarded a $364K grant from NASA’s Space Archeology program to estimate the population of pre-Columbian indigenous peoples in the Amazon Basin lowlands by means of satellite remote sensing technology.

Currently, population estimates vary widely – from 500,000 to 10 million – and are the subject of much controversy and debate. Among other things, knowing with more accuracy how many people might have impacted the rainforest through agriculture and development prior to European contact will help scientists understand how the Amazon Basin might withstand current pressures from deforestation, selective logging, and development.

Palace, a research assistant professor at the Complex Systems Research Center (CSRC) within the Institute for the Study or Earth, Oceans, and Space, is an expert in using satellite-borne imagery to study various aspects of tropical forests. In this project he will use hyperspectral imagery taken by NASA’s Hyperion sensor onboard the Terra satellite.

The Hyperion camera “sees” in 242 spectral bands of light, allowing scientists to identify the chemical makeup of tree leaves, which in turn is related to nutrients in the underlying soil. The more nutrient-rich leaves or specific groups of tree species seen by Hyperion will be the signature for what Palace is looking for – Amazonian black earths – sites containing soil rich in organic matter, charcoal, and nutrients and frequently associated with large accumulations of potsherds and other artifacts of human origin.

Also known as “terra preta” soils, they were created hundreds of years ago when indigenous populations slowly burned trees to make soil equivalent to “biochar,” which is extremely efficient at storing carbon and nutrients and provides fertile, productive farmland.

“There are terra preta sites all over the Amazonian basin, particularly near rivers, but no one really knows their whole distribution,” says Palace, who will collaborate with Mark Bush, an ecologist from the Florida Institute of Technology, and Brazilian archeologist Eduardo Neves of the University of San Paulo. Also collaborating on the project are Stephen Hagen, a research scientist at Applied GeoSolutions of Newmarket who received his Ph.D. at UNH, and former CSRC faculty member Rob Braswell, now at Atmospheric Environmental Research, Inc. of Lexington, Mass.

Having identified terra preta sites in the Hyperion imagery, the researchers will then build a model to “scale up” the data and identify the location of other sites across the entire Amazon landscape. Says Palace, “This will allow archeologists to go to these sites and determine if they are indeed terra preta. We should then be able to accurately estimate the indigenous population prior to colonial contact.”

At six million square kilometers, the Amazon basin contains the largest continuous rainforest in the world and constitutes 40 percent of what remains of this ecotype. Current scientific knowledge of the forest views its past as pristine with little human influence. If Palace’s research indicates there was a large population of indigenous peoples using the forest to maintain a highly productive agricultural system, it is likely that Amazonian forest vegetation was significantly altered and may be thought of as a cultural artifact, resilient to human disturbance and not an undisturbed forest.

NASA’s little-known space archeology program is getting its share of headlines primarily through research being conducted in South and Central America, including recent work that uncovered one of the largest Mayan cities in Belize.

[Source: University of New Hampshire press release via All Points Blog/Directions magazine]

Changes in Croplands as a Result of Large Scale Mining and the Associated Impact on Food Security Studied Using Time-Series Landsat Images

In Environmental Science, Imagery, Social Science, Spatial Analysis, Temporal Analysis on June 9, 2010 at 6:43 am

Remote Sensing 2010, 2, 1463-1480

Lubos Matejicek and Veronika Kopackova

“Geographic information systems and satellite remote sensing information are emerging technologies in land-cover change assessment. They now provide an opportunity to gain insights into land-cover change properties through the spatio-temporal data capture over several decades. The time series of Landsat images covering the 1985–2009 period is used here to explore the impacts of surface mining and reclamation, which constitute a dominant force in land-cover changes in the northwestern regions of the Czech Republic. Advanced quantification of the extent of mining activities is important for assessing how these land-cover changes affect ecosystem services such as croplands. The images employed from 1985, 1988, 1990, 2000, 2002, 2003, 2004, 2005, 2006, 2007, 2008, and 2009 assist in mapping the extent of surface mines and mine reclamation for large surface mines in a few selected areas of interest. The image processing techniques are based on pixel-by-pixel calculation of the vegetation index, such as NDVI. The NDVI values are classified into the defined classes based on CORINE Land Cover 2000 data in a 3280 km2 strip of Landsat images. This distribution of NDVI values is used to estimate the land-cover classes in the local areas of interest (184 km2, 368 km2, 737 km2, and 1,474 km2). Thus, the approximate land-cover stability of the 3,280 km2 strip during the whole 1985–2009 period is used to explore land-cover disturbances in the local areas of surface mines. In the case of NDVI, it also includes variations, presumably caused by seasonal vegetation effects, and local meteorological conditions. However, the main trends related to mining activities during the long-term period can be clearly understood. As a result, other objectives can be explored in the 1985–2009 period, such as cropland changes to other land use classes, changes of cropland patterns, and their impacts on food security. The presented spatio-temporal modeling based on long time series from 12 satellite images provides considerable experience for processing NDVI in the framework of identification of land-cover classes and also, to a certain degree, cropland variability with its impact on food security.”

Characterization of Complex Fluvial Systems using Remote Sensing of Spatial and Temporal Water Level Variations in the Amazon, Congo, and Brahmaputra Rivers

In Environmental Science, Imagery, Spatial Analysis, Temporal Analysis on June 7, 2010 at 11:53 am

Earth Surface Processes and Landforms, Volume 35, Issue 3, Date: 15 March 2010, Pages: 294-304

Hahn Chul Jung, James Hamski, Michael Durand, Doug Alsdorf, Faisal Hossain, Hyongki Lee, A. K. M. Azad Hossain, Khaled Hasan, Abu Saleh Khan, and A.K.M. Zeaul Hoque

“The Surface Water and Ocean Topography (SWOT) satellite mission will provide global, space-based estimates of water elevation, its temporal change, and its spatial slope in fluvial environments, as well as across lakes, reservoirs, wetlands, and floodplains. This paper illustrates the utility of existing remote sensing measurements of water temporal changes and spatial slope to characterize two complex fluvial environments. First, repeat-pass interferometric SAR measurements from the Japanese Earth Resources Satellite are used to compare and contrast floodplain processes in the Amazon and Congo River basins. Measurements of temporal water level changes over the two areas reveal clearly different hydraulic processes at work. The Amazon is highly interconnected by floodplain channels, resulting in complex flow patterns. In contrast, the Congo does not show similar floodplain channels and the flow patterns are not well defined and have diffuse boundaries. During inundation, the Amazon floodplain often shows sharp hydraulic changes across floodplain channels. The Congo, however, does not show similar sharp changes during either infilling or evacuation. Second, Shuttle Radar Topography Mission measurements of water elevation are used to derive water slope over the braided Brahmaputra river system. In combination with in situ bathymetry measurements, water elevation and slope allow one to calculate discharge estimates within 2.3% accuracy. These two studies illustrate the utility of satellite-based measurements of water elevation for characterizing complex fluvial environments, and highlight the potential of SWOT measurements for fluvial hydrology.”

The Capabilities of Remote Sensing to Derive Urban Location Factors for Probability-based Spatial Growth Analysis

In Imagery, Social Science on June 3, 2010 at 1:08 pm

REAL CORP 2010 Proceedings/Tagungsband, Vienna, 18-20 May 2010

Hannes Taubenböck, Sebastian Clodt, Michael Wurm, Martin Wegmann, Carsten Jürgens

“Urbanization is arguably the most dramatic form of irreversible land transformation. Though urbanization is a worldwide phenomenon, it is especially prevalent in India, where urban areas have experienced an unprecedented rate of growth over the last 30 years (UN, 2007). This paper focuses on the capabilities of remote sensing to identify and derive spatial urban location factors which influence future urban growth. We utilize multitemporal remotely sensed data sets from Landsat and TerraSAR-X sensors as well as a digital elevation model (DEM) from the Shuttle Radar Topography Mission (SRTM).

“The land cover of the test site, the highly dynamic incipient mega city of Hyderabad in India, was classified and a change detection analysis was performed to monitor the dimension and the spatial configuration of urban growth since the 1970s. The results of the change detection as well as the DEM serve as basis to derive and develop spatial location factors influencing urban growth. Parameters like the slope, the major street network, continuous intra-urban open spaces, main direction of growth, etc. were calculated. Furthermore external data sets on locations of commercial centers, airports, etc. were integrated. Based on regional theory for every single parameter a specific hypothesis was stated. For example: We assumed that high slope gradients have a lower probability for future settlements or that new commercial centers have a positive influence for future settling. In addition, results from a comparative study of the 12 largest Indian cities (Taubenböck et al., 2009), like saturation effects for built-up density, were integrated as additional information.

“An approach combining all urban location factors for the metropolitan area of Hyderabad was developed to identify areas that are theoretically highly probable for future settlements. The approach was applied to the spatial physical extension of the urban area of 2001, the so called urban footprint. Accuracy was assessed for predicted areas of urban growth comparing the result to the actual urban footprint acquired in 2009. The results of the method basically showed high probabilities for those areas which actually have experienced growth, but the limitations of the approach revealed low absolute accuracy. This is due to the manifold parameters having an impact on spatial growth – e.g. socio-economic, physical, demographic or political parameters – which could not be derived using remotely sensed data. Thus, the method basically enables location study to differentiate between preferred and unlikely areas of future urbanization.”

Mapping Land-cover Change in a Haitian Watershed using a Combined Spectral Mixture Analysis and Classification Tree Procedure

In Environmental Science, Imagery on June 2, 2010 at 11:30 am

Geocarto International, Volume 25, Issue 2 April 2010 , pages 85 – 103

Anna Versluis and John Rogan

“Severe deforestation in the Caribbean nation of Haiti is a long-standing concern in Haiti and internationally. There are, however, few studies measuring the amount, type, rate or location of this deforestation and related land-cover changes. This study measures the loss of pine forest over three decades from one watershed in Haiti. The study employs an image processing method that draws on the strengths of spectral mixture and classification tree analyses. Results show 54% of the watershed was forested in 1979 compared with 22% in 2000. For the 2000 map, overall accuracies range from 81 to 91% and user’s mean per-class accuracies range from 71 to 90%. Overall map accuracies range from 73 to 83% for the 1979 land-cover map with user’s mean per-class accuracies ranging from 71 to 84%. For 2000, the combined classification procedure yields more accurate results than a classification tree alone.”

Sleeping Sickness in Southeastern Uganda: A Spatio-Temporal Analysis of Disease Risk, 1970-2003

In Environmental Science, Imagery, Spatial Analysis, Statistics, Temporal Analysis on June 1, 2010 at 7:28 am

Vector Borne Zoonotic Diseases, 2010 May 19. [Epub ahead of print]

Berrang-Ford L, Berke O, Sweeney S, and Abdelrahman L.

“Sleeping sickness is a major threat to human health in sub-Saharan Africa. Southeastern Uganda has experienced a number of significant epidemics in the past 100 years, most recently from 1976 to 1989. Recent and continued spread of the disease has highlighted gaps in the ability of current research to explain and predict the distribution of infection. Vegetation cover and changes in vegetation may be important determinants of transmission and disease risk because of the habitat preferences of the tsetse fly vector. This study examines the determinants of sleeping sickness distribution and incidence in southeastern Uganda from 1970 to 2003, spanning the full epidemic region and cycle, and focusing in particular on vegetation cover and change. Sleeping sickness data were collected from records of the Ugandan Ministry of Health, individual sleeping sickness treatment centers, and interviews with public health officials. Vegetation data were acquired from satellite imagery for four dates spanning the epidemic period, 1973, 1986, 1995, and 2001. Zero-inflated regression models were used to model predictors of disease presence and magnitude. Correlations between disease incidence and the normalized difference vegetation index (NDVI) at the subcounty level were evaluated. Results indicate that sleeping sickness infection is predominantly associated with proximity to water and spatial location, while disease incidence is highest in subcounties with moderate to high NDVI. The vegetation density (NDVI) at which sleeping sickness incidence peaked differed throughout the study period. The optimal vegetation density capable of supporting sleeping sickness transmission may be lower than indicated by data from endemic regions, indicating increased potential for disease spread under suitable conditions.”

Using Remote Sensing and GIS for Damage Assessment after Flooding, the Case of Muscat, Oman after Gonu Tropical Cyclone 2007: Urban Planning Perspective

In GIS, Imagery on May 28, 2010 at 7:30 am

REAL CORP 2010 Proceedings/Tagungsband, Vienna, 18-20 May 2010

Lotfy Kamal Azaz

“Natural Disasters occur frequently around the world, and their incidence and intensity seem to be increasing in recent years. The Disasters such as cyclones and floods often cause significant loss of life, large-scale economic and social impacts, and environmental damage. For example, Cyclone Gonu was the strongest tropical cyclone on record in the Arabian Sea, and tied for the strongest tropical cyclone on record in the northern Indian Ocean and was the strongest named cyclone in this basin. On June 5 2007 it made landfall on the eastern-most tip of Oman with winds of 150 km/h (90 mph). Gonu dropped heavy rainfall near the eastern coastline, reaching up to 610 mm (24 inches), which caused flooding and heavy damage. The cyclone caused about $4 billion in damage and nearly 50 deaths in Oman, where the cyclone was considered the nation’s worst natural disaster. Nowadays, we have access to data and techniques provided by remote sensing and GIS that have proven their usefulness in disaster management plan. Remote Sensing can assists in damage assessment monitoring, providing a quantitative base for relief operations. After that, it can be used to map the new situation and update the database used for the reconstruction of an area. Disaster management plan consists of two phases that takes place before disaster occurs, disaster prevention and disaster preparedness, a three phases that happens after the occurrence of a disaster i.e. disaster relief, rehabilitation and reconstruction. In the disaster rehabilitation phase GIS is used to organize the damage information and the post-disaster census information, and in the evaluation of sites for reconstruction. In this  study, two IKONOS satellite images of Muscat, Oman have been utilized; one image before the cyclone and one after. The two images have been geometrically corrected. Change detection has been applied to identify and assess the damages. The results of this study emphasize the importance of using remote sensing and GIS in damage assessment phase as part of effective Disaster Management Plan.”

Mapping Diversified Peri-urban Agriculture – Potential of Object-based Versus Per-field Land Cover/Land Use Classification

In Imagery on May 28, 2010 at 5:43 am

Geocarto International, Volume 25, Issue 3 June 2010 , pages 171 – 186

Dionys Forster; Tobias Walter Kellenberger; Yves Buehler; Bernd Lennartz

“High spatial resolution satellite data contribute to improving land cover/land use (LCLU) classification in agriculture. A classification procedure based on Quickbird satellite image data was developed to map LCLU of diversified agriculture at sub-communal and communal level (7 km2). Segmentation performance of the panchromatic band in combination with high pass filters (HPF) was tested first. Accuracy of field boundary delineation was evaluated by an object-based segmentation, a per-field and a manual classification, along with a quantitative accuracy assessment. Sub-communal classification revealed an overall accuracy of 84% with a κ coefficient of 0.77 for the per-field vector segmentation compared to an overall accuracy of 56-60% and a κ coefficient of 0.37-0.42 for object-based approaches. Per-field vector segmentation was thus superior and used for LCLU classification at communal level. Overall accuracy scored 83% and the κ coefficient 0.7. In diversified agriculture, per-field vector segmentation and classification achieved higher classification results.”

Automatic Cluster Identification for Environmental Applications using the Self-organizing Maps and a New Genetic Algorithm

In Environmental Science, GIS, Imagery on May 27, 2010 at 7:38 am

Geocarto International, Volume 25, Issue 1 February 2010, pages 53 – 69

Tonny J. Oyana and Dajun Dai

“A rapid increase of environmental data dimensionality emphasizes the importance of developing data-driven inductive approaches to geographic analysis. This article uses a loosely coupled strategy to combine the technique of self-organizing maps (SOM) with a new genetic algorithm (GA) for automatic identification of clusters in multidimensional environmental datasets. In the first stage, we employ the well-known classic SOM because it is able to handle the dimensional interactions and capture the number of clusters via visualization; and thus provide extraordinary insights into original data. In the second stage, this new GA rigorously delineates the cluster boundaries using a flexibly oriented elliptical search window. To test this approach, one synthetic and two real-world datasets are employed. The results confirm a more robust and reliable approach that provides a better understanding and interpretation of massive multivariate environmental datasets, thus maximizing our insights. Other key benefits include the fact that it provides a computationally fast and efficient environment to accurately detect clusters, and is highly flexible. In a nutshell, the article presents a computational approach to facilitate knowledge discovery of massive multivariate environmental datasets; as we are too familiar with their accelerating growth rate.”

Application of Pattern Recognition and Adaptive DSP Methods for Spatio-temporal Analysis of Satellite Based Hydrological Datasets

In GIScience, Imagery, Spatial Analysis, Temporal Analysis on May 20, 2010 at 11:51 am

Dissertation, 2010

Anish Chand Turlapaty

“Data assimilation of satellite-based observations of hydrological variables with full numerical physics models can be used to downscale these observations from coarse to high resolution to improve microwave sensor-based soil moisture observations. Moreover, assimilation can also be used to predict related hydrological variables, e.g., precipitation products can be assimilated in a land information system to estimate soil moisture. High quality spatio-temporal observations of these processes are vital for a successful assimilation which in turn needs a detailed analysis and improvement. In this research, pattern recognition and adaptive signal processing methods are developed for the spatio-temporal analysis and enhancement of soil moisture and precipitation datasets. These methods are applied to accomplish the following tasks: (i) a consistency analysis of level-3 soil moisture data from the Advanced Microwave Scanning Radiometer – EOS (AMSR-E) against in-situ soil moisture measurements from the USDA Soil Climate Analysis Network (SCAN). This method performs a consistency assessment of the entire time series in relation to others and provides a spatial distribution of consistency levels. The methodology is based on a combination of wavelet-based feature extraction and oneclass support vector machines (SVM) classifier. Spatial distribution of consistency levels are presented as consistency maps for a region, including the states of Mississippi, Arkansas, and Louisiana. These results are well correlated with the spatial distributions of average soil moisture, and the cumulative counts of dense vegetation; (ii) a modified singular spectral analysis based interpolation scheme is developed and validated on a few geophysical data products including GODAE’s high resolution sea surface temperature (GHRSST). This method is later employed to fill the systematic gaps in level-3 AMSR-E soil moisture dataset; (iii) a combination of artificial neural networks and vector space transformation function is used to fuse several high resolution precipitation products (HRPP). The final merged product is statistically superior to any of the individual datasets over a seasonal period. The results have been tested against ground based measurements of rainfall over our study area and average accuracies obtained are 85% in the summer and 55% in the winter 2007.”

A Geostatistically Weighted k-NN Classifier for Remotely Sensed Imagery

In Environmental Science, Imagery, Modeling, Statistics on May 20, 2010 at 6:14 am

Geographical Analysis, Volume 42 Issue 2 (April 2010) p 204-225

Peter M. Atkinson and David K. Naser

“This study aims to increase the accuracy with which remotely sensed data can be used to generate thematic maps of land cover classes. It explores the use of geostatistical models to characterize the inherent spatial variation between different land covers (woodland, rough grassland, managed grassland, and built land) and integrates these into a supervised, nonparametric, k-nearest neighbor (k-NN) per-pixel classifier. The study defines three geographical weighting methods, two of which are based on geostatistical functions. These produce a geographical weighting that is incorporated into two pure k-NN classifiers (inverse distance weighted and difference distance weighted) using a scheme that allows the weights for the information from feature space and geographical space to be varied. The relative merits of the enhanced approach are explored using a spatially and spectrally variable IKONOS subscene. Compared with the original k-NN classifications, which use only the information in the spectral response of pixels treated independently, a statistically significant increase in the overall accuracy was achieved, particularly for land cover classes with considerable within-class variation and between-class confusion.”

Monitoring Spatial and Temporal Pattern of Paneveggio Forest (Northern Italy) from 1859 to 2006

In Environmental Science, GIS, Imagery, Spatial Analysis, Temporal Analysis on May 19, 2010 at 7:32 am

iForest 3: 72-80. [online 2010-05-17]

C. Tattoni, M. Ciolli, F. Ferretti, and M.G. Cantiani

“This paper presents the results of a forest cover analysis over a time span of 150 years in a protected area of Eastern Trentino (Northern Italy), Paneveggio Pale di S. Martino Nature Park. With the aid of Grass GIS two historical maps (1859 and 1936) and a set of aerial photographs taken from 1945 to 2006 have been analysed, orthorectified and classified with a supervised method, in order to derive a series of forest cover maps. Techniques applied and problems encountered in using heterogeneous material are discussed. The research shows that from 1859 to the present the increase of forest cover is about 25%, due to the reduced impact of forestry and farming. Timberline dynamics have also been considered; an average growth of about 1 m/year has been estimated for the last 150 years and the data have been compared with the timberline cartography and to field surveys. Timberline estimation for recent years appears to be affected mainly by lower human pressure while the relationship with climate changes is difficult to evaluate. Landscape metrics were used to quantify the changes in forest fragmentation and to identify three core areas that have remained unchanged over time. This case study fills a gap of knowledge about the history of forest cover in the area, shows how multi temporal analysis can support protected area management. This study has been requested by the Park managers, a sign t that landscape planners are becoming aware of past landscape importance.”

Assessing Floodplain Forests: Using Flow Modeling and Remote Sensing to Determine the Best Places for Conservation

In Environmental Science, GIS, Imagery, Modeling, Spatial Analysis on May 18, 2010 at 8:41 am

Natural Areas Journal, Volume 30, Number 1 – January 2010

Mark G. Anderson, Charles E. Ferree, Arlene P. Olivero, and Feng Zhao

“Mature and diverse floodplain forests are among the world’s most diminished ecosystems and conservationists need a rapid method to identify the best remaining examples of these systems. Because large rivers and their dynamics bind the floodplain together, the method must go beyond simple inventory of remnant patches to evaluate flood processes and identify constraints in the surrounding watersheds. We develop such a method for a three million hectare watershed in New England using a combination of data types to evaluate key attributes of floodplain systems. Riparian and floodplain communities were modeled using a GIS analysis of river valley topography and riverine processes, and floodplain forest occurrences were identified in a classification and regression (CART) analysis. Current flooding was verified using overlays of remotely sensed imagery of spring and fall water levels. We evaluated the intactness of the floodplain occurrences using ratios of upstream dam storage to annual runoff, the length of the connected stream network, and the naturalness of surrounding land cover. Field-assigned ranks of forest quality were correlated with the occurrence size, percent verified flooding, and percent natural cover. Predicted quality ranks reinforced the importance of these factors. Results indicate that the twenty top-ranking streams collectively contain 75 high quality areas suitable for floodplain forest restoration and conservation. Independent verification of these areas strongly corroborated our results.”

Assessing the Implementation of Rawalpindi’s Guided Development Plan through GIS and Remote Sensing

In GIS, Imagery on May 17, 2010 at 9:43 am

REAL CORP 2010 Proceedings/Tagungsband, Vienna, 18-20 May 2010

Muhammad ADEEL

“Rawalpindi is the fourth largest city of Pakistan inhibiting 2 million people. Growth of Traffic in Rawalpindi city has acquired an alarming situation and put tremendous pressure on infrastructure of the city. Rawalpindi Development Authority conducted the series of traffic surveys in 1995, 1998 and a Guided Development Plan was formulated to develop proper road infrastructure, a series of main & sub-main traffic corridors. The plan is supposed to be implemented soon. But with the passage of time, road alignment plans are required to be updated with respect to the ongoing development activity in the area. Traffic and ground surveys were conducted in year 2007. But it 2009, the plan needs to be rechecked. Required cost, time and manpower for this purpose make this task virtually impossible, thus hindering the implementation of the project.

“In this paper, we have proposed a system of regularly monitoring on ground situation, using high resolution “Quickbird” satellite images of and Geographical Information Systems, at a relatively lower cost. Satellite images have been used to identify the exact on ground alignment of the proposed roads through spatial overlays of georeferenced data. The process will support authority to know whether the proposed development falls under the right of way of a proposed network. The system will thus help regularizing the development activity and help identify the unauthorized construction activity taking place in the area. The approach also helps identifying alternative route alignment more efficiently.”

Small Unmanned Aerial Vehicles in Teaching Geospatial Disciplines

In GIS, Geography, Imagery on May 17, 2010 at 8:32 am

ASPRS 2009 Annual Conference, Baltimore, Maryland, March 9-13, 2009

Eugene Levin, Robert Liimakka, and Stephen Curelli

“The latest developments in small unmanned air vehicle (SUAV) technologymake it possible to utilize SUAV platforms in geospatial disciplines research and teaching processes. Michigan Technological University is implementing a number of remotely controlled aircraft platforms in its photogrammetry course. The Surveying Engineering Program is working on a SUAV suite configuration that will make the following hands-on labs possible: project planning and potential accuracy analysis, implementation of project waypoints into the SUAV operational control unit, auto-pilot flight control over calibration sites and test-objects, and processing of gathered UAV imagery on softcopy photogrammetric workstations. The initial SUAV is equipped with autopilot and can carry up from 1 to 11 pounds of payload, and is currently fitted with a 7.1MP non-metric camera. Students use surveying grade GPS equipment to prepare calibration sites. Work on processing of the obtained datasets encompasses: bundle block adjustment, image co-registration, mosaicking, and finally feature extraction from UAV imagery. Comparison of the results obtained from the SUAV to respective results obtained from traditional aerial photogrammetry will provide an excellent opportunity for research investigation directed at accuracy and applicability of SUAV imagery for specific projects. Practical hands-on experience with SUAV control and imagery provides students a unique opportunity to participate in ongoing development and research activities in the geospatial science and industry.”

Windmill Site Selection Using Remote Sensing and GIS – A Case Study in Andaman, India

In ESRI, Environmental Science, GIS, Green Technologies, Imagery on May 12, 2010 at 9:46 am

K. Selvavinayagam

“The Andaman and Nicobar Islands are the summits of a submarine mountain range lying on the great tectonic suture zone that extends from the eastern Himalayas to the Arakan along the Myanmar border and finally to Sumatra and lesser Sundaes. This archipelago consists of a group of 572 islands, islets and rock outcrops, but there are a total of 352 important islands comprising the main chain of Andaman and Nicobar, Ritches Archipelago and the out laying volcanic islands of Narcondam and Barren. The islands are spread over an area of 8,249 sq.km, of which 6,408 sq. km of area is occupied by the Andaman group and 1,841 sq.km by the Nicobar groups of Islands. The Andaman group consists of 324 islands of which 24 are inhabited while the Nicobar group includes 28 islands of which 12 are inhabited. Undulating topography and intervening valleys characterize the physiography of this Archiepelago. There are several rain-fed streams, which dry up during summer. All the major islands support a luxuriant growth of evergreen, semi evergreen, moist deciduous and littoral forests from the water edge to the mountain top depending on the topography and nature of the soil. For administrative purposes, the Islands are divided into two districts, namely Andaman and Nicobar. There are a total of 204 revenue villages of which 197 are in the Andaman District. The Andaman and Nicobar is having a good economic turnover through Tourism Industry because of its rich natural scenic beauty and natural resources. At the same time these islands are facing problems such as population growth, commercial development etc and inturn facing acute power shortage.”

Estimate of Peatland Distribution in Estonia Using an Integrated GIS/RS Approach

In Climate Change, Environmental Science, GIS, Imagery on May 11, 2010 at 7:43 am

Proceedings of the 33rd International Symposium on Remote Sensing of Environment, 2009

Gardi C, Sommer S, Seep K, and Montanarella L.

“Determination of the spatial extent of peatland is important for the evaluation of soil carbon stocks. At European Level there is a need to provide accurate and updated estimate of the distribution of peatland. Comparison of national data with EU wide land cover mapping shows that there is limited compatibility between the different data sets. The aim of the present study is to test a methodology of standardized mapping and monitoring of peatlands at regional level (national to supra-national bio-climatic regions) based on the enhanced integration of existing thematic maps through GIS analysis in combination with remote sensing, using Estonia as study case. Existing national maps and field inventory of Estonian peatlands have been used for a GIS based evaluation of peatland relevant information contained in Corine Land Cover. Remote sensing has been employed in 2 ways: a multispectral approach using Landsat TM and a phenology oriented time series analysis of SPOT VEGETATION NDVI both implemented for the entire territory of Estonia. The remote sensing results are evaluated against the existing high resolution Estonian map of peatlands. In the case study it could be shown that peatlands are both spectrally and phenologically clearly distinct from other land cover types and therefore have a good potential to allow semiautomated mapping over large areas with relatively high accuracy, which lays the basis for efficient montoring and mapping of peatland change.”

Temporal Analysis of the Reduction in Gas Emission in Areas of Mechanically-harvested Sugarcane using Satellite Imagery

In Environmental Science, GIS, Imagery, Temporal Analysis on May 6, 2010 at 7:20 am

Ciencia e Investigación Agraria, 37(1):113-121, 2010

Christiano Luna Arraes, Jesús Camacho-Tamayo, Teresa Tarlé Pissarra, Célia P. Bueno, and Sergio Campos

“The primary objective of this study was to estimate the amount of gas not emitted into the air in areas cultivated with sugarcane (Saccharum officinarum) that were mechanically harvested. Satellite images CBERS-2/CCD, from 08-13-2004, 08-14-2005, 08-15-2006 and 08-16-2007, of northwestern São Paulo State were processed using the Geographic Information System (GIS)-IDRISI 15.0. Areas of interest (the mechanically-harvested sugarcane fields) were identified and quantified based on the spectral response of the bands studied. Based on these data, the amount of gas that was not emitted was evaluated, according to the estimate equation proposed by the Intergovernmental Panel on Climate Change (IPCC). The results of 396.65 km2 (5.91% for 2004); 447.56 km2 (6.67% for 2005); 511.54 km2 (7.62% in 2006); and 474.60 km2 (7.07% for 2007), calculated from a total area of 6,710.89 km2 with sugarcane, showed a significant increase of mechanical harvesting in the study area and a reduction of gas emissions of more than 300,000 t yr.”

Scientists to Speak on Global Environmental Issues

In Climate Change, ESRI, Environmental Science, GIS, Imagery on May 5, 2010 at 7:28 am

Redlands Forum Presents Woods Hole Research Center Scientists William Brown and Josef Kellndorfer

From mapping the Amazon River basin to promoting global climate change policy, scientists at the Woods Hole Research Center (the Center) are focused on keeping Planet Earth healthy. The next Redlands Forum event will feature William Brown, Ph.D., president and CEO of the Center, who will describe how the Massachusetts-based institute is working to help protect the global environment. His colleague, Josef Kellndorfer, Ph.D., associate scientist at the Center, will also speak. The presentations will take place in Redlands at the ESRI Conference Center, 380 New York Street, on Wednesday, May 19, at 5:30 p.m.

Brown will give an overview of the Center’s global activities with the talk Woods Hole Research Center: Science, Policy, and Education for a Healthy Planet. Then, Kellndorfer will drill down to describe a research project that uses satellite imagery technology to map the world’s forests. His presentation has the intriguing title Shooting with the Radar Gun: Another Radiological Tool to Diagnose and Monitor Patient Earth.

“Our planet’s climate and ecosystems are changing, and the scientists at the Center are leading authorities in understanding the causes and consequences of this as well as offering solutions that foster a healthy planet,” said Brown. With projects in the Amazon, the Arctic, Africa, Russia, Alaska, Canada, and New England, the Center collaborates with partners ranging from local nongovernmental organizations and research centers to national governments and the United Nations. Brown’s talk will include examples of the Center’s work around the globe.

Brown joined the Center in February 2010 and previously held posts as president and CEO of the Academy of Natural Sciences in Philadelphia, Pennsylvania, the nation’s oldest natural history museum, and as Department of the Interior science advisor during the Clinton administration. He also concurrently serves as chairman of the Global Heritage Fund, president of the Natural Science Collections Alliance, and a trustee of the Academy of Natural Sciences.

Kellndorfer’s research focuses on the monitoring and assessment of terrestrial and aquatic ecosystems. Using geographic information systems (GIS) and remote sensing, he studies land use, land cover, and climate change on a regional and global scale. Before joining the Center, he was an assistant research scientist in the Department of Electrical Engineering and Computer Science at the University of Michigan.

After May 19, the next Redlands Forum event will be a talk on recent projects and legislation affecting both Redlands and California open spaces, which will be presented by Pete Dangermond, president of The Dangermond Group. It will take place Wednesday, June 16, 2010, at 5:30 p.m.

Redlands Forum events are sponsored by ESRI and the University of Redlands through the university’s Town & Gown organization. Admission to both of these events is free. To guarantee seating, attendees should register via the Internet at www.esri.com/culturalseries or by calling 909-748-8011.

[Source: ESRI press release]

Mapping Understory Vegetation using Phenological Characteristics Derived from Remotely Sensed Data

In Environmental Science, Imagery on April 30, 2010 at 8:07 am

Remote Sensing of Environment, In Press, Available online 17 April 2010

Mao-Ning Tuanmu, Andrés Viña, Scott Bearer, Weihua Xu, Zhiyun Ouyang, Hemin Zhang, and Jianguo Liu

“Understory vegetation is an important component in forest ecosystems not only because of its contributions to forest structure, function and species composition, but also due to its essential role in supporting wildlife species and ecosystem services. Therefore, understanding the spatio-temporal dynamics of understory vegetation is essential for management and conservation. Nevertheless, detailed information on the distribution of understory vegetation across large spatial extents is usually unavailable, due to the interference of overstory canopy on the remote detection of understory vegetation. While many efforts have been made to overcome this challenge, mapping understory vegetation across large spatial extents is still limited due to a lack of generality of the developed methods and limited availability of required remotely sensed data. In this study, we used understory bamboo in Wolong Nature Reserve, China as a case study to develop and test an effective and practical remote sensing approach for mapping understory vegetation. Using phenology metrics generated from a time series of Moderate Resolution Imaging Spectroradiometer data, we characterized the phenological features of forests with understory bamboo. Using maximum entropy modeling together with these phenology metrics, we successfully mapped the spatial distribution of understory bamboo (kappa: 0.59; AUC: 0.85). In addition, by incorporating elevation information we further mapped the distribution of two individual bamboo species, Bashania faberi and Fargesia robusta (kappa: 0.68 and 0.70; AUC: 0.91 and 0.92, respectively). Due to its generality, flexibility and extensibility, this approach constitutes an improvement to the remote detection of understory vegetation, making it suitable for mapping different understory species in different geographic settings. Both biodiversity conservation and wildlife habitat management may benefit from the detailed information on understory vegetation across large areas through the applications of this approach.”

Spatio-temporal Analysis of Forests under Different Management Regimes using Landsat and IRS Images

In Environmental Science, Imagery, Spatial Analysis, Temporal Analysis on April 29, 2010 at 9:13 am

Institute for Social and Economic Change, Bangalore, Working paper 213, 2009

“Following the empirical study, cloud-free satellite data were used to study the forests in multi-temporal dimensions. Use of remote sensing data with visual observation/ground truth data is an advanced tool to study and understand the development patterns of the forests. Based on the vegetation index and land cover map a sound development has been observed in the community conserved forest (CCF) in comparison to other forests of the region. Community-based conservation would contribute to new conservation approaches that facilitate achieving the goal of sustainable landscape development in the mountains of the Indian Himalayan region.”

Predictive Mapping of Reef Fish Species Richness, Diversity and Biomass in Zanzibar using IKONOS Imagery and Machine-learning Techniques

In Environmental Science, Imagery, Modeling on April 26, 2010 at 2:27 pm

Remote Sensing of Environment, Volume 114, Issue 6, 15 June 2010, Pages 1230-1241

Anders Knudby, Ellsworth LeDrew, and Alexander Brenning

“During the last three decades, the large spatial coverage of remote sensing data has been used in coral reef research to map dominant substrate types, geomorphologic zones, and bathymetry. During the same period, field studies have documented statistical relationships between variables quantifying aspects of the reef habitat and its fish community. Although the results of these studies are ambiguous, some habitat variables have frequently been found to correlate with one or more aspects of the fish community. Several of these habitat variables, including depth, the structural complexity of the substrate, and live coral cover, are possible to estimate with remote sensing data. In this study, we combine a set of statistical and machine-learning models with habitat variables derived from IKONOS data to produce spatially explicit predictions of the species richness, biomass, and diversity of the fish community around two reefs in Zanzibar. In the process, we assess the ability of IKONOS imagery to estimate live coral cover, structural complexity and habitat diversity, and we explore the importance of habitat variables, at a range of spatial scales, in the predictive models using a permutation-based technique. Our findings indicate that structural complexity at a fine spatial scale (not, vert, similar 5 to 10 m) is the most important habitat variable in predictive models of fish species richness and diversity, whereas other variables such as depth, habitat diversity, and structural complexity at coarser spatial scales contribute to predictions of biomass. In addition, our results demonstrate that complex model types such as tree-based ensemble techniques provide superior predictive performance compared to the more frequently used linear models, achieving a reduction of the cross-validated root-mean-squared prediction error of 3–11%. Although aerial photographs and airborne lidar instruments have recently been used to produce spatially explicit predictions of reef fish community variables, our study illustrates the possibility of doing so with satellite data. The ability to use satellite data may bring the cost of creating such maps within the reach of both spatial ecology researchers and the wide range of organizations involved in marine spatial planning.”

Spatial Heterogeneity in the Shrub Tundra Ecotone in the Mackenzie Delta Region, Northwest Territories: Implications for Arctic Environmental Change

In Climate Change, Environmental Science, Imagery on April 26, 2010 at 10:49 am

Ecosystems, Volume 13, Number 2 / March, 2010

Trevor C. Lantz, Sarah E. Gergel and Steven V. Kokelj

“Growing evidence suggests that plant communities in the Low Arctic are responding to recent increases in air temperature. Changes to vegetation, particularly shifts in the abundance of upright shrubs, can influence surface energy balance (albedo), sensible and latent heat flux (evapotranspiration), snow conditions, and the ground thermal regime. Understanding fine-scale variability in vegetation across the shrub tundra ecotone is therefore essential as a monitoring baseline. In this article, we use object-based classifications of airphotos to examine changes in vegetation characteristics (cover and patch size) across a latitudinal gradient in the Mackenzie Delta uplands. This area is frequently mapped as homogenous vegetation, but it exhibits fine-scale variability in cover and patch size. Our results show that the total area and size of individual patches of shrub tundra decrease with increasing latitude. The gradual nature of this transition and its correlation with latitudinal variation in temperature suggests that the position of the shrub ecotone will be sensitive to continued warming. The impacts of vegetation structure on ecological processes make improved understanding of this heterogeneity critical to biophysical models of Low Arctic ecosystems.”

Remote Sensing of the Urban Heat Island Effect across Biomes in the Continental USA

In Environmental Science, Imagery, Spatial Analysis on April 21, 2010 at 6:29 am

Remote Sensing of Environment, Volume 114, Issue 3, 15 March 2010, Pages 504-513

Imhoff, M.L., Zhang, P., Wolfe, R.E. and Bounoua, L.

“Impervious surface area (ISA) from the Landsat TM-based NLCD 2001 dataset and land surface temperature (LST) from MODIS averaged over three annual cycles (2003–2005) are used in a spatial analysis to assess the urban heat island (UHI) skin temperature amplitude and its relationship to development intensity, size, and ecological setting for 38 of the most populous cities in the continental United States. Development intensity zones based on %ISA are defined for each urban area emanating outward from the urban core to the non-urban rural areas nearby and used to stratify sampling for land surface temperatures and NDVI. Sampling is further constrained by biome and elevation to insure objective intercomparisons between zones and between cities in different biomes permitting the definition of hierarchically ordered zones that are consistent across urban areas in different ecological setting and across scales.

“We find that ecological context significantly influences the amplitude of summer daytime UHI (urban–rural temperature difference) the largest (8 °C average) observed for cities built in biomes dominated by temperate broadleaf and mixed forest. For all cities combined, ISA is the primary driver for increase in temperature explaining 70% of the total variance in LST. On a yearly average, urban areas are substantially warmer than the non-urban fringe by 2.9 °C, except for urban areas in biomes with arid and semiarid climates. The average amplitude of the UHI is remarkably asymmetric with a 4.3 °C temperature difference in summer and only 1.3 °C in winter. In desert environments, the LST’s response to ISA presents an uncharacteristic “U-shaped” horizontal gradient decreasing from the urban core to the outskirts of the city and then increasing again in the suburban to the rural zones. UHI’s calculated for these cities point to a possible heat sink effect. These observational results show that the urban heat island amplitude both increases with city size and is seasonally asymmetric for a large number of cities across most biomes. The implications are that for urban areas developed within forested ecosystems the summertime UHI can be quite high relative to the wintertime UHI suggesting that the residential energy consumption required for summer cooling is likely to increase with urban growth within those biomes.”

An Automated Image Analysis Approach for Classification and Mapping of Woody Vegetation from Digital Aerial Photograph

In Environmental Science, GIS, Imagery on April 16, 2010 at 8:35 am

World Review of Science, Technology and Sustainable Development, 2010 – Vol. 7, No.1/2 pp. 13 – 23

Xihua Yang and David Tien

“This paper presents a recent study on woody vegetation delineation and mapping using digital aerial photograph and geographic information system (GIS) in Hunter Region, Australia. The aim of the study was to develop automated and repeatable digital image processing methods for woody vegetation classification and mapping using aerial photograph or high-resolution satellite images and GIS. Parallelepiped classification or density slice method was used to classify woody and non-woody vegetation, and ancillary GIS data were used as quality controls in the classification processing. Specific scripts were developed for automated image processing in a GIS environment. The classification accuracy was assessed against traditional aerial photograph interpretation using adequate random points. The automated process reached an overall classification accuracy of 94% and 97% after post-classification correction. The automated approach can be applied to any other type of high-resolution imagery such as SPOT 5, ALOS, IKONOS and QuickBird images.”

Multitemporal Monitoring of Water Resources Degradation at Al-Azraq Oasis, Jordan, Using Remote Sensing and GIS Techniques

In Climate Change, Environmental Science, GIS, Imagery, Statistics, Temporal Analysis on April 15, 2010 at 7:02 am

International Journal of Global Warming, 2010 – Vol. 2, No.1 pp. 1 – 16

Naser Kloub, Mohammed Matouq, Monzer Krishan, Saeid Eslamian, and Monther Abdelhadi

“The historical topographic maps and satellite images of Al-Azraq Oasis of Jordan were collected from 1953 to 2005. These images are demonstrated for the first time. The satellite land image for 2005 is considered to be the most significant one. This is considered to be the highest level of degradation since 1953. The water degradation in the lake was fitted by linear regression and the best fitting for the calculated surface area for the water can be presented by a polynomial equation.”

Estimating the Frequency and Extent of Bloodworm Digging in Maine from Aerial Photography

In ESRI, Environmental Science, GIS, Imagery on April 14, 2010 at 7:17 am

Fisheries Research, Volume 101, Issues 1-2, 5 January 2010, Pages 87-93

Eben Sypitkowski, Curtis Bohlen, and William G. Ambrose Jr.

“The extent and frequency of bloodworm digging in northeast North America has never been investigated, making bloodworm fishery management difficult and an assessment of ecological impact impossible. We examined the spatial and temporal patterns of bloodworm digging by surveying 13 mudflats in mid-coast Maine using monthly aerial photography. We used ArcGIS to “georeference” spatial information into the photographs, allowing us to quantify the area of the mudflat disturbed by digging. Of the 122 ha of flats we monitored, almost 48% was dug in 2006, and 24% was dug in 2007, corresponding to 57.9 ha and 24.8 ha, respectively. Individual flats in this study were dug as much as 155% and as little as 0% annually, but rarely were they dug more than once a year as studies assessing the impact of digging on soft-sediment communities have assumed. Digging activity peaked in early spring with a smaller peak in August. On average, 3% of the visual evidence of digging faded each month. Except for those erased by winter storms and ice scour, no dug strip faded before 5 months of age, therefore flats could be monitored every 4–5 months for an accurate estimate of digging activity. Our results allow us, for the first time, to estimate the impact of digging on the bloodworm resource and to design realistic experiments to measure the impact of digging on the soft-sediment community and non-target species.”

The Mapping of Soil Attributes of Volcanic Ash Soils Using a GIS and Remote Sensing-Based Approach

In Environmental Science, GIS, Imagery on April 6, 2010 at 6:12 am

Paper accepted for presentation at the 2010 European Space Agency Living Planet Symposium, Bergen, Norway, 28 June to 2 July 2010:

Kýlýç, Kenan; Doðan, Hakan Mete; Bilim, Mehmet

“The mapping of soil attributes of volcanic ash soils is very important for land use and agricultural practices. An extensive survey was conducted in the soils formed on parent materials erupted from the Erciyes strato volcano, using a systematic sampling strategy with a sampling density of total 192 sampling points. Following the determination of soil variability with geographical information system (GIS), soil maps and geologic maps, soil samples were taken from three different depths (0-30 cm, 30-60 cm and 60-90 cm soil depths) for each sampling location. The maps of soil attributes (Organic matter, pH, calcium carbonate content, cation exchange capacity, exchangeable cations, clay content, silt content and sand content) were produced based on GIS and remote sensing (RS) technologies. A significant spatial relationship was found between soil attributes and soil parent materials using GIS and RS-based analysis.”

River Channel Migration: A Remote Sensing and GIS Analysis

In ESRI, Environmental Science, GIS, Imagery, Spatial Analysis on April 2, 2010 at 6:56 am

Paper accepted for presentation at the 2010 European Space Agency Living Planet Symposium, Bergen, Norway, 28 June to 2 July 2010:

Islam, Md. Tariqul

“Remote sensing and geographic information system provide tools for quantitative and qualitative river morphological analysis. Bangladesh is a riverine, flood prone country and, the Padma and the Jamuna are two of major three rivers in the country. The aim of this research is to monitor the channel migration of the Padma and the Jamuna rivers since 1977 to 2004 using remote sensing and GIS. The Landsat images were processed using PCI Geomatica and ArcGIS 9.3 was used for GIS analysis. The Landsat images were visualized and identified nine locations to investigate the channel migration. The images were classified into two broad categories, i.e. water and non-water body. ArcGIS 9.3 was used to transfer these classified images into GIS layers. A standard measurement tool of ArcGIS was applied to measure the movement of river channel based on initial river channel in 1977. General trend of the Padma and the Jamuna River channel migration at locations A, B, C, D, F, G, H and I towards north, northeast and southwest eventually, north, northeast, east, east, west and west respectively. The confluence point of the Padma and Jamuna (at location E) migrated toward southeast with high rate. During 1977-2004, it migrated about 9000m toward southeast. Trend of migration of the confluence point was faster than any other locations in the channel of the Padma River.”

Spatial Dependence of Predictions from Image Segmentation: A Variogram-based Method to Determine Appropriate Scales for Producing Land-management Information

In Environmental Science, Imagery, Statistics on April 1, 2010 at 7:31 am

Ecological Informatics, In Press, Accepted Manuscript, Available online 1 March 2010

Jason W. Karl, Brian A. Maurer

“A significant challenge in ecological studies has been defining scales of observation that correspond to the relevant ecological scales for organisms or processes of interest. Remote sensing has become commonplace in ecological studies and management, but the default resolution of imagery often used in studies is an arbitrary scale of observation. Segmentation of images into objects has been proposed as an alternative method for scaling remotely-sensed data into units having ecological meaning. However, to date, the selection of image object sets to represent landscape patterns has been largely subjective. Changes in observation scale affect the variance and spatial dependence of measured variables, and may be useful in determining which levels of image segmentation are most appropriate for a given purpose. We used observations of percent bare ground cover from 346 field sites in a semi-arid shrub-steppe ecosystem of southern Idaho to look at the changes in spatial dependence of regression predictions and residuals for 10 different levels of image segmentation. We found that the segmentation level whose regression predictions had spatial dependence that most closely matched the spatial dependence of the field samples also had the strongest predicted-to-observed correlations. This suggested that for percent bare ground cover in our study area an appropriate scale could be defined. With the incorporation of a geostatistical interpolator to predict the value of regression residuals at unsampled locations, however, we achieved consistently strong correlations across many segmentation levels. This suggests that if spatial dependence in percent bare ground is accounted for, a range of appropriate scales could be defined. Because the best analysis scale may vary for different ecosystem attributes and many inquiries consider more than one attribute, methods that can perform well across a range of scales and perhaps not at a single, ideal scale are important. More work is needed to develop methods that consider a wider range of ways to segment images into different scales and select sets of scales that perform best for answering specific management questions. The robustness of ecological landscape analyses will increase as methods are devised that remove the subjectivity with which observational scales are defined and selected.”

GIS/Remote Sensing Techniques for Resource Management and Biodiversity Protection in Mountainous Regions

In Climate Change, Environmental Science, GIS, Imagery on March 29, 2010 at 8:10 am

Botanica Orientalis: Journal of Plant Science, 6: 93-99 (2009)

John All

“Biodiversity protection in mountainous regions requires effective fact-driven resource management techniques. Geoinformatic tools including GIS and remote sensing can be integrated to provide regional-scale data products across time for use in strategic and management level policymaking. Several principles are discussed to ensure that geoinformatics data and analysis can effectively contribute to resource management by clarifying issues and minimizing misinterpretation. A case study in the Chilean Andes elucidates these principles. Biological impacts of recent climate changes have not been equal across different ecosystems and stable forest ecosystems provide the best response to climate change. Geoinformatics is used to differentiate functional ecological groups and evaluate long-term resilience to climate change.”

Delineating a Managed Fire Regime and Exploring its Relationship to the Natural Fire Regime in East Central Florida, USA: A Remote Sensing and GIS Approach

In Environmental Science, GIS, Imagery on March 29, 2010 at 7:20 am

Forest Ecology and Management, 258 (2), p.132-145, Jun 2009

Duncan, B.W. / Shao, G. / Adrian, F.W.

“A managed fire regime on John F. Kennedy Space Center, Florida and surrounding federal properties was mapped using time series satellite imagery and GIS techniques. Our goals were to: (1) determine if an image processing technique designed for individual fire scar mapping could be applied to an image time series for mapping a managed fire regime in a rapid re-growth pyrogenic system; (2) develop a method for labeling mapped fire scar confidence knowing a formal accuracy analysis was not possible; and (3) compare results of the managed fire regime with regional information on natural fire regimes to look for similarities/differences that might help optimize management for persistence of native fire-dependent species. We found that the area burned by managed fire peaked when the drought index was low and was reduced when the drought index was high. This contrasts with the expectations regarding the natural fire regime of this region. With altered natural fire regimes and fire-dependent species declining in many pyrogenic ecosystems, it is important to manage fire for the survival of fire-adapted native species. The remote sensing and GIS techniques presented are effective for delineating and monitoring managed fire regimes in shrub systems that grow rapidly and may be appropriate for other fire-dependent systems world wide.”

Investigation of Aggregation Effects in Vegetation Condition Monitoring at a National Scale

In Environmental Science, GIS, Imagery on March 19, 2010 at 6:35 am

International Journal of Geographical Information Science, Volume 24, Issue 4 April 2010 , pages 507 – 521

T. K. Alexandridis;  T. Katagis;  I. Z. Gitas;  N. G. Silleos;  K. M. Eskridge; G. Gritzas

“Monitoring vegetation condition is an important issue in the Mediterranean region, in terms of both securing food and preventing fires. Vegetation indices (VIs), mathematical transformations of reflectance bands, have played an important role in vegetation monitoring, as they depict the abundance and health of vegetation. Instead of storing raster VI maps, aggregated statistics can be derived and used in long-term monitoring. The aggregation schemes (zonations) used in Greece are the forest service units, the fire service units, and the administrative units. The purpose of this work was to explore the effect of the modifiable areal unit problem (MAUP) in vegetation condition monitoring at the above-mentioned aggregation schemes using 16 days Normalized Difference Vegetation Index (NDVI) composites acquired by the moderate resolution imaging spectroradiometer satellite sensor. The effects of aggregation in the context of MAUP were examined by analyzing variance, from which the among polygon variation (objects’ heterogeneity) and the within polygon variation (pixels’ homogeneity) were derived. Significant differences in objects’ heterogeneity were observed when aggregating at the three aggregation schemes; therefore there is a MAUP effect in monitoring vegetation condition on a nationwide scale in Greece with NDVI. Monitoring using the fire service units has significantly higher pixels’ homogeneity; therefore there is indication that it is the most appropriate for monitoring vegetation condition on a nationwide scale in Greece with NDVI. Results were consistent between the two major types of vegetation, natural and agricultural. According to the statistical validation, conclusions based on the examined years (2003 and 2004) are justified.”

Ensemble Extraction for Classification and Detection of Bird Species

In Environmental Science, Imagery, Temporal Analysis on March 18, 2010 at 9:42 am

Ecological Informatics, In Press, Accepted Manuscript, Available online 1 March 2010

Eric P. Kasten, Philip K. McKinley, Stuart H. Gage

“Advances in technology have enabled new approaches for sensing the environment and collecting data about the world. Once collected, sensor readings can be assembled into data streams and transmitted over computer networks for storage and processing at observatories or to evoke an immediate response from an autonomic computer system. However, such automated collection of sensor data produces an immense quantity of data that is time consuming to organize, search and distill into meaningful information. In this paper, we explore the design and use of distributed pipelines for automated processing of sensor data streams. In particular, we focus on the detection and extraction of meaningful sequences, called ensembles, from acoustic data streamed from natural areas. Our goal is automated detection and classification of various species of birds.”

Augmented Reality and Photogrammetry: A Synergy to Visualize Physical and Virtual City Environments

In Imagery, Visualization on March 17, 2010 at 6:01 am

ISPRS Journal of Photogrammetry and Remote Sensing, Volume 65, Issue 1, January 2010, Pages 134-142

Cristina Portalés, José Luis Lerma, Santiago Navarro

“Close-range photogrammetry is based on the acquisition of imagery to make accurate measurements and, eventually, three-dimensional (3D) photo-realistic models. These models are a photogrammetric product per se. They are usually integrated into virtual reality scenarios where additional data such as sound, text or video can be introduced, leading to multimedia virtual environments. These environments allow users both to navigate and interact on different platforms such as desktop PCs, laptops and small hand-held devices (mobile phones or PDAs). In very recent years, a new technology derived from virtual reality has emerged: Augmented Reality (AR), which is based on mixing real and virtual environments to boost human interactions and real-life navigations. The synergy of AR and photogrammetry opens up new possibilities in the field of 3D data visualization, navigation and interaction far beyond the traditional static navigation and interaction in front of a computer screen.

“In this paper we introduce a low-cost outdoor mobile AR application to integrate buildings of different urban spaces. High-accuracy 3D photo-models derived from close-range photogrammetry are integrated in real (physical) urban worlds. The augmented environment that is presented herein requires for visualization a see-through video head mounted display (HMD), whereas user’s movement navigation is achieved in the real world with the help of an inertial navigation sensor. After introducing the basics of AR technology, the paper will deal with real-time orientation and tracking in combined physical and virtual city environments, merging close-range photogrammetry and AR. There are, however, some software and complex issues, which are discussed in the paper.”

Classifying Historical Remotely Sensed Imagery Using a Tempo-spatial Feature Evolution (T-SFE) Model

In Imagery, Modeling, Spatial Analysis, Temporal Analysis on March 16, 2010 at 8:45 am

ISPRS Journal of Photogrammetry and Remote Sensing, Volume 65, Issue 2, March 2010, Pages 182-190

Yichun Xie, Zongyao Sha, Yongfei Bai

“Large and growing archives of orbital imagery of the earth’s surface collected over the past 40 years provide an important resource for documenting past and current land cover and environmental changes. However uses of these data are limited by the lack of coincident ground information with which either to establish discrete land cover classes or to assess the accuracy of their identification. Herein is proposed an easy-to-use model, the Tempo-Spatial Feature Evolution (T-SFE) model, designed to improve land cover classification using historical remotely sensed data and ground cover maps obtained at later times. This model intersects (1) a map of spectral classes (S-classes) of an initial time derived from the standard unsupervised ISODATA classifier with (2) a reference map of ground cover types (G-types) of a subsequent time to generate (3) a target map of overlaid patches of S-classes and G-types. This model employs the rules of Count Majority Evaluation, and Subtotal Area Evaluation that are formulated on the basis of spatial feature evolution over time to quantify spatial evolutions between the S-classes and G-types on the target map. This model then applies these quantities to assign G-types to S-classes to classify the historical images. The model is illustrated with the classification of grassland vegetation types for a basin in Inner Mongolia using 1985 Landsat TM data and 2004 vegetation map. The classification accuracy was assessed through two tests: a small set of ground sampling data in 1985, and an extracted vegetation map from the national vegetation cover data (NVCD) over the study area in 1988. Our results show that a 1985 image classification was achieved using this method with an overall accuracy of 80.6%. However, the classification accuracy depends on a proper calibration of several parameters used in the model.”

Managing Uncertainty when Aggregating from Pixels to Objects: Habitats, Context-sensitive Mapping and Possibility Theory

In GIScience, Imagery, Statistics on March 5, 2010 at 7:42 am

International Journal of Remote Sensing, Volume 31, Issue 4 April 2010 , pages 1061 – 1068

Alexis Comber; Katie Medcalf; Richard Lucas; Peter Bunting; Alan Brown; Daniel Clewley; Johanna Breyer; Steve Keyworth

“Object-oriented remote sensing software provides the user with flexibility in the way that remotely sensed data are classified through segmentation routines and user-specified fuzzy rules. This paper explores the classification and uncertainty issues associated with aggregating detailed ‘sub-objects’ to spatially coarser ‘super-objects’ in object-oriented classifications. We show possibility theory to be an appropriate formalism for managing the uncertainty commonly associated with moving from ‘pixels to parcels’ in remote sensing. A worked example with habitats demonstrates how possibility theory and its associated necessity function provide measures of certainty and uncertainty and support alternative realizations of the same remotely sensed data that are increasingly required to support different applications.”

Post Doc Opprotunity: Remote Sensing in Forest Ecosystems, Istituto Agrario San Michele all’Adige

In Climate Change, Education, Environmental Science, Imagery, Modeling, Science on February 24, 2010 at 7:57 am

“Primary responsibility is to analyse high resolution hyperspectral and Lidar data of forest ecosystems located in the complex alpine region. The scientific activity aims to understand the sensitivity of carbon and nitrogen cycles to climate and land use changes using spatially processbased models, remote sensing and other spatial techniques on a range of different spatial scales. Models development and analysis, parameter estimation, sensitivity analysis and simulations of different scenarios are other objectives.

“Experience with Lidar and hyperspectral data analysis in complex areas and previous work with large database are required. Candidates will be preferably familiar with a programming language such as C, FORTRAN, or MATLAB and have prior experience or training in forest ecosystems classification and analysis of Lidar data for forest structure and biophysical parameter estimation.

“The candidate should also have experience in planning and implementing scientific projects, including writing research proposals, and have a good written scientific record.”

Workshop on Workflows for Earth Observation Systems, University of Nottingham, on 21-22 June 2010

In Conferences, GIS, Imagery on February 24, 2010 at 7:17 am

“International initiatives such as the Global Earth Observation System of Systems (GEOSS) and the Global Monitoring for Environment and Security (GMES) are making significant progress towards providing resources for the access, discovery, processing and publishing of earth observation data. It is necessary for organisations to develop capabilities within their workflows for applying earth observation data from satellite-based, airborne and in situ sensors.

“A workflow can be defined as a collection of tasks, carried out by software systems, humans, or a combination of both, and organized to accomplish some business process.[http://dx.doi.org/10.1016/S0268-4012(01)00005-6]. Within Earth Observation Systems and Geographic Information Systems (GIS), workflows are enacted through the orchestration or chaining of services.”

“This workshop will bring together researchers from various projects to exchange knowledge on strategies for earth observation workflows and to identify areas for future collaboration and development. The workshop will be hosted by the Open Source GIS UK conference, to be held at the University of Nottingham on 21st-22nd June 2010. Visit the website here.”

Satellite Observations Help Assess Future Earthquake Risk in Haiti

In Environmental Science, Geography, Imagery on February 12, 2010 at 7:16 am

Startling images of ground motion in Haiti during the recent earthquake are helping scientists understand the risk of aftershocks and even the possibility of a major new earthquake

According to the new data, the earthquake rupture did not reach the surface—unusual for an earthquake this size. More importantly, the images confirm that only the western half of the fault segment that last ruptured in 1751 actually ruptured in the current earthquake. “We’re still waiting for the other shoe to drop,” says Tim Dixon, professor of geology and geophysics at the University of Miami Rosenstiel School of Marine & Atmospheric Science.

The images reveal other startling facts, “Given the plate tectonic setting scientists expected mainly sideways motion, yet there was a large amount of vertical motion during the earthquake,” says Falk Amelung, professor of geology and geophysics at Rosenstiel School. “This explains how such a relatively small rupture was able to generate such a large earthquake.”

The data shows the earthquake occurred on or near the Enriquillo Fault, where most scientists suspected but until now did not have enough evidence to prove it. “This is a relief, because it shows that our current ideas about the tectonics of the area are correct,” Amelung said.

Dixon is looking at every bit of evidence to try to understand the possibility of another major quake hitting Port au Prince in the near future.  “There’s a reasonable probability of another large quake, similar to the January 12 event, striking Port au Prince within the next 20 to 30 years,” Dixon says. “I’d like to see them re-locate critical infrastructure such as government buildings, schools and hospitals, farther north out of the danger zone.”

In 1986, at the dawn of the GPS age, scientists from the National Aeronautics Space Administration (NASA) Jet Propulsion Lab, including Dixon began, a set of geodetic measurements on the island of Hispaniola.  A decade later, those measurements would reveal that the Enriquillo fault in southern Haiti was a significant earthquake hazard.  “In a very real sense, those early measurements set the stage for our current understanding of this dangerous fault zone.  Scientists have been studying this fault and others on the island, ever since,” Dixon says.

Shimon Wdowinski and Guoqing Lin, professors of geology and geophysics at RSMAS; Fernando Greene, graduate student at RSMAS and Sang-Hoon Hong,  post-doctoral research scientist at RSMAS and at Florida International University also contributed to the analysis of the new images.

The work of RSMAS in active tectonics is supported by NASA, the National Science Foundation (NSF) and the National Earthquake Hazard Reduction Program (NEHRP). Other institutions involved in the analysis of the images included JAXA (the Japanese Space Exploration Agency) and NASA’s Jet Propulsion Lab.

[Source: Rosenstiel School of Marine and Atmospheric Science, University of Miami press release]

Using Satellite Imagery to Identify Active Magma Systems in East Africa’s Rift Valley

In Environmental Science, Geography, Imagery on February 11, 2010 at 8:15 am

Surface deformation of four active volcanoes captured on InSAR underscore possibility for human hazard, potential of geothermal resources

A team from the University of Miami, University of El Paso and University of Rochester have employed Interferometric Synthetic Aperture Radar (InSAR) images compiled over a decade to study volcanic activity in the African Rift. The study, published in the November issue of Geology, studies the section of the rift in Kenya.

“The Kenyan Rift volcanoes are part of a larger Great Rift Valley complex that extends all the way from Mozambique to Djibouti; their presence in East Africa attests to the presence of magma reservoirs within the Earth’s crust,” said Lead Author Dr. Juliet Biggs, Rosenstiel Postdoctoral Fellow at the University of Miami. “Our study detected signs of activity in only four of the 11 volcanoes in the area — Suswa, Menengai, Longonot and Paka — all within the borders of Kenya.”

Small surface displacements, which are not visible to the naked eye, were captured using InSAR, a sophisticated satellite-based radar technique. Using images from European Space Agency satellites ERS and Envisat, the team was able to detect the smallest ((<1 cm) of surface displacements at a very high resolution. From 1997 – 2000 they discovered that the volcanoes at Suswa and Menengai subsided 2 – 5 cm, and between 2004 and 2006 the Longonot volcano experienced uplift of ~9 cm.  However, the most dramatic uplift unfolded at Paka, which had uplift of ~21 cm during a nine month period in 2006-2007.  This pulse of  activity was preceded by transient uplift and subsidence at a second source, associated with the magma flow through the complex underground plumbing system. Overall the events were short in duration and episodic rather than continuous, which means discrete pulses of magma were arriving at the crust, similar to a stop valve that is being turned on and off intermittently.

“The fact that these areas are so close to a major metropolitan area pose a challenge in terms of a large volcanic or seismic event” says co-author Cindy Ebinger. Suswa, Menengai and Longonot are all located in densely populated areas within 100 km of Nairoibi.

The study also provides insight as to the geothermal potential of the region. Kenya was the first African country to build geothermal energy plants to generate this renewable, environmentally friendly alternative to coal and oil.  The impact of harnessing such a resource could provide an important economic engine for the region.

Geothermal energy is generated by drilling deep holes into the Earth’s crust, pumping cold water through one end so by the time it resurfaces it is steam, which is then used to fuel a turbine, which in turn drives a generator, and creates power.

“This study demonstrates the potential for using InSAR to measure active magmatic and tectonic phenomena in Africa, allowing us to watch the processes by which continents break apart” says lead author Juliet Biggs, who has just begun a 2-year project at the Univeristy of Oxford, funded by the European Space Agency, to map the pattern of volcanic activity, dike intrusion and active faulting along the whole of the East African Rift.

[Source: Rosenstiel School of Marine and Atmospheric Science, University of Miami press release]

Meeting Tomorrow’s Challenges: Start with Science

In Climate Change, Environmental Science, Geography, Imagery on February 6, 2010 at 8:55 am

The President’s FY 2011 Budget Proposal for the USGS

In a fiscally responsible budget that emphasizes cost containment, management efficiencies and program savings, the President’s proposed $1.1 billion budget for the U.S. Geological Survey (USGS) in fiscal year 2011 reflects his commitment to use science as the basis for natural resource management decisions.

“Science is a cornerstone for sound decision making,” said Marcia McNutt, USGS director. “Today’s complex, interrelated natural resource issues—such as climate change, energy conservation and development, and water quality and availability—demand that policy makers and managers start with timely, unbiased science. The President’s budget supports that vital perspective.”

Because of the significant role USGS plays in climate change monitoring and adaptation, energy, ecosystems, and other priorities, the 2011 budget represents an increase of $21.6 million from the FY 2010 enacted level. Major USGS program increases proposed are summarized below. For more detailed information on the President’s proposed USGS FY 2011 budget, visit the FY 2011 Budget and Related Information Web site.

New Energy Frontier
$3.0 million

The USGS will work closely with Department of the Interior bureaus to provide the scientific information needed to make decisions concerning permitting, implementing, and operating wind facilities on public lands by using USGS research, modeling, and monitoring to assess the ecological impacts to fish and wildlife. In 2011, USGS efforts will begin in the Great Plains and offshore Cape Cod region and will work toward developing an assessment methodology that can be applied nationwide.

Climate Change Adaptation
$11.0 million

Management and policy decisions made in response to climate change impacts must be informed by science. The USGS will continue to assist the Department of the Interior in the development of regional climate science centers that provide climate change impact data and analysis geared to the needs of the fish and wildlife management community, in partnership with other Federal, State, university and other non-governmental partners. Additionally, the USGS will continue to assess biological carbon sequestration options and develop decision-support tools through the USGS Global Change program.

WaterSMART
$9.0 million

Water shortages and water-use conflicts have become more commonplace in many areas of the United States. Water is essential to the economic security of individual communities and the economic vitality and environmental health of our nation as a whole. The USGS will begin an assessment of the availability and use of water resources in the United States in FY 2011. The information will provide tools to address a new set of water resource challenges, including aging infrastructure, rapid population growth, depletion of groundwater resources, water quality impairments associated with land uses, and climate variability.

Treasured Landscapes: The Chesapeake Bay
$3.6 million

President Obama issued an Executive Order in May 2009 directing Federal agencies to use their expertise and resources to protect and restore the Chesapeake Bay and its watershed. The USGS will support restoration strategies by providing tools and science for assessing climate change impacts and adaptation, for conserving landscapes, and for restoring habitats, fish and wildlife, in partnership with the Fish and Wildlife Service and the National Park Service.

Increasing Resilience to Natural Hazards
$4.0 million

The USGS Multi-Hazards Demonstration Project in Southern California will continue to support emergency planning by developing earthquake early warning capabilities and conducting impact analysis of environmental, human-health and ecosystem responses to earthquakes and other hazards. This project will be expanded into the coastal communities of Alaska, and the USGS will invest in earthquake, tsunami and volcano science to support community planning in the Pacific Northwest. Additionally, the USGS proposes to add a volcanic earthquake detection role to the USGS National Earthquake Information Center, which will provide critical early warning to give observatories and affected communities time to plan and prepare for an eruption.

Landsat Data Continuity
$13.4 million

Scientists, educators and the general public around the globe use USGS Landsat data for a wide array of activities ranging from supporting disaster relief efforts to making agricultural crop assessments to identifying sites for cell phone towers. The USGS will accommodate ground-system requirement changes for the Landsat Data Continuity Mission associated with moving the Operational Land Imager to a free-flying satellite and the addition of a Thermal Infrared Sensor on board the spacecraft. These activities are required to meet the mission launch in December 2012.

Coastal and Marine Spatial Planning
$4.0 million

The Department of the Interior has substantial coastal and ocean resource management responsibilities and a critical role in implementing the Administration’s National Ocean Policy. USGS mapping, monitoring and research provide information to assess the status and vulnerability of ocean, coastal and Great Lakes resources. The USGS will engage with other Department of the Interior bureaus and Federal agencies to make available an information framework that provides critical information for coastal and marine planning.

[Source: USGS press release]

GEO Announces Call for Participation in GEOSS Pilot

In Environmental Science, GIS, Geography, Imagery on February 2, 2010 at 6:04 am

The Open Geospatial Consortium, Inc. (OGC®) announces a Call for Participation (CFP) in Phase 3 of the GEOSS (Global Earth Observation System of Systems) Architecture Implementation Pilot (AIP) issued by the Group on Earth Observations (GEO). The CFP documents are available at: http://earthobservations.org/geoss_call_aip.shtml.

AIP-3 will build on previous project phases and is coordinated with other GEO Tasks. Specific areas of emphasis for AIP-3 include increasing the capacity for GEOSS to support Societal Benefit Areas; building on the AIP Service Architecture and the GEOSS Common Infrastructure; and increasing availability of data in GEOSS in accordance with the GEOSS Data Sharing Guidelines. AIP-3 will be conducted in 2010 with support to the Earth Observation Summit, November 2010.

The AIP-3 CFP invites GEO Members and Participating Organizations to participate in activities involving: registering components and services; testing of services; and participating in refinement of Societal Benefit Area scenarios to guide testing, demonstrations and operations of the identified interoperable services.

CFP responses are requested by 3 March 2010. Organizations responding to the CFP should plan to attend the kickoff workshop to begin development of AIP-3 to be held 11-12 March 2010, at the European Space Agency facility in Frascati, Italy.

Discussion and clarification of the CFP will be the topic of several teleconferences before the Kickoff Workshop. Agenda and logistics for these teleconferences are posted at http://www.ogcnetwork.net/AIPtelecons.

The point of contact for the AIP task is George Percivall percivall@opengeospatial.org.

The OGC® is an international consortium of more than 385 companies, government agencies, research organizations, and universities participating in a consensus process to develop publicly available geospatial standards. OGC Standards empower technology developers to make geospatial information and services accessible and useful with any application that needs to be geospatially enabled. Visit the OGC website at http://www.opengeospatial.org.

GEO (Group on Earth Observations) is a voluntary partnership of 124 governments and international organizations, launched in response to calls for action by the 2002 World Summit on Sustainable Development and by the G8 (Group of Eight) leading industrialized countries. GEO is coordinating efforts to build a Global Earth Observation System of Systems, or GEOSS. See http://earthobservations.org/about_geo.shtml.

[Source: OGC press release]

U.S. National Agricultural Statistics Service Releases New Geospatial Data Products

In GIS, Imagery on January 29, 2010 at 1:16 pm

New Satellite Images Show Ag Land Cover for 2009 Crop Year

The U.S. Department of Agriculture’s National Agricultural Statistics Service (NASS) today announced the release of new satellite images depicting agricultural land cover across most of the nation for the 2009 crop year. The images, referred to as cropland data layers (CDL), are a useful tool for monitoring crop rotation patterns, land use changes, water resources and carbon emissions.

These crop-specific, digital data layers are suitable for use in geographic information systems (GIS) applications. They can be used by agribusinesses, farmers, government agencies, researchers and academic institutions to study pesticide risk, epidemiology, transportation, fertilizer usage, carbon dioxide flux and other topics.

NASS produced the CDLs using satellite images observed at 56-meter (0.775 acres per pixel) resolution and collected from the Resourcesat-1 Advanced Wide Field Sensor (AWiFS), Landsat Thematic Mapper and Moderate Resolution Imaging Spectroradiometer (MODIS). The collection of images was then categorized using on-the-ground farm information including field location, crop type, land cover, elevation, tree canopy and urban infrastructure.

For the first time, the CDL images are available for 47 of the 48 contiguous states. Data for the final state, Florida, will be available this spring pending the availability of certified farm data required to produce the images. NASS is also making available, for the first time, the New Mexico CDL for 2008.

The entire inventory of CDL products, including metadata and accuracy assessments, is available online at the USDA Natural Resources Conservation Service’s Geospatial Data Gateway: http://datagateway.nrcs.usda.gov and at this NASS website: http://www.nass.usda.gov/research/Cropland/SARS1a.htm.

[Source: NASS press release]

Darkness on the Edge of Town: Mapping Urban and Peri-Urban Australia Using Nighttime Satellite Imagery

In Geography, Imagery on January 29, 2010 at 8:41 am

The Professional Geographer, Volume 62, Issue 1 February 2010 , pages 119 – 133

Paul C. Sutton; Andrew R. Goetz; Stephen Fildes; Clive Forster; Tilottama Ghosh

“This article explores the use of nighttime satellite imagery for mapping urban and peri-urban areas of Australia. A population-weighted measure of urban sprawl is used to characterize relative levels of sprawl for Australia’s urban areas. In addition, the expansive areas of low light surrounding most major metropolitan areas are used to map the urban-bush interface of exurban land use. Our findings suggest that 82 percent of the Australian population lives in urban areas, 15 percent live in peri-urban or exurban areas, and 3 percent live in rural areas. This represents a significantly more concentrated human settlement pattern than presently exists in the United States.”

Ghost Peaks Emerge from Antarctic Ice

In Geography, Imagery on January 27, 2010 at 9:22 am

…from National Geographic…

“Hidden miles beneath the surface of an ice sheet (shown in blue), the so-called ghost peaks in the middle of Antarctica are finally coming into view, researchers announced last month.

“Ground-penetrating radar results from 2008 and 2009 have made possible the most detailed images yet (such as the one above) of the Gamburtsev Mountains—and it’s a surprisingly serrated range, the experts say.”

World Bank Awards Contract for Spatial Analysis of Natural Hazard and Climate Change Risks in Vietnam

In Climate Change, Environmental Science, GIS, Imagery, Spatial Analysis, Statistics on January 22, 2010 at 7:17 am

Spatial Analysis of Natural Hazard and Climate Change Risks in Can Tho, Dong Hoi, and Hanoi cities in Viet Nam

Under a contract from the World Bank, GeoVille has performed a spatial analysis of natural hazard and climate change risks for disaster risk reduction into overall urban development in Can Tho, Dong Hoi, and Hanoi cities, Vietnam. The assessment covers satellite, topographical and multi-level GIS based generation of natural hazards and climate change hazard potential maps, description of methods and provision of statistics and description of hazard potential profiles.

The scope of the contract includes project management; satellite, topographical, and multi-level GIS based generation of natural hazards and climate change hazard potential maps; and description of methods and provision of statistics and description of hazard potential profiles.

About GeoVille

GeoVille Group is an internationally operating company providing products, services and consultancy in the environmental and geo-spatial domain, specializing in Earth observation and GIS applications.

We are dedicated to customer satisfaction and delivering quality controlled geo-information products.

We have successfully carried out projects in over 60 countries.

GeoVille Information Systems GmbH and GeoVille Environmental Services sàrl are based in Austria and Luxemburg.

Post Doctoral Fellow: Remote Sensing and Forest Resource Inventory

In Environmental Science, Imagery on January 18, 2010 at 6:14 am

Laboratory for Remote Sensing of Earth and Environmental Systems (LaRSEES)
Department of Geography
Queen’s University
Kingston, Ontario Canada

“We are seeking an individual with a Ph.D. in one of the following disciplines: geography, forestry, environmental science, environmental engineering; with an emphasis on remote sensing, spatial data analysis and/or modeling for forestry. Experience with light detection and ranging (LiDAR) data analysis is a definite asset. Other skills and background of the applicant should include some of the following:

  • Knowledge of forest mensuration and field techniques (i.e., with an ability to lead the design, implementation and collection of forest inventory data);
  • Computer programming skills/experience;
  • Familiarity with the application of statistics/biostatistics;
  • Knowledge of image processing and GIS software; and
  • Ability to communicate effectively both verbally and in writing.

“The focus of the project is to derive accurate estimates of forest inventory variables (e.g., tree height, stem density, diameter and breast height, volume, biomass, etc.) using lidar and high resolution digital photos. The individual will be involved in the development of algorithms and procedures for extracting forest structural and terrain variables from the LiDAR data collected for over one million hectares of boreal forest near Hearst Ontario. The PDF will coordinate activities of the project, specifically the field-based activities during two summer field campaigns and the development and application of LiDAR height and density metrics to the LiDAR data collected for Hearst. The PDF will be responsible for supervising the application of the individual tree crown (ITC) method to the ADS40 imagery collected for the same forest. The successful candidate will have the opportunity to define their own research goals within the scope of the overall project (i.e., enhanced forest inventory using LiDAR and/or high resolution digital photography). The successful candidate will also assist the principal investigator with the administration and management of the project. The fellowship holder will be expected to collaborate and work closely with the research team at Queen’s and Nipissing Universities as well as government (e.g., OMNR, CFS) and industrial partners (Hearst Forest Management Inc., Tembec Inc., etc.).”

A Hybrid Approach for Land Use/Land Cover Classification

In Geography, Imagery on January 13, 2010 at 2:40 pm

GIScience & Remote Sensing, Volume 46, Number 4 / October-December 2009

Yanbing Tang, Clifton W. Pannell

“Atlanta has continuously changed its physical landscape as well as its socioeconomic appearance over the past decades. A hybrid image processing approach, which integrated unsupervised, supervised, and spectral mixture analysis (SMA) classification methods, was used to identify urban land use/land cover changes over a decade (from 1990 to 2000) in the Atlanta metropolitan area. During this process, SMA was proven to be an effective analytical approach for characterizing mixed feature areas, such as a metropolitan area. According to accuracy assessment, the classification results were acceptable.”

NSF Awards SDSC, Arizona State University $1.7 Million for National OpenTopography LiDAR Facility

In Imagery, Science on January 13, 2010 at 1:17 pm

The San Diego Supercomputer Center ( SDSC ) at UC San Diego and Arizona State University have been awarded a $1.7 million grant from the National Science Foundation ( NSF ) to operate an internet-based national data facility for high-resolution topographic data acquired with LiDAR ( Light Detection and Ranging ) technology.  The facility will also provide online processing tools and act as a community repository for information, software and training materials.

The three-year project, which includes a grant of $1.4 million to SDSC and $300,000 to the School of Earth and Space Exploration at Arizona State University, will be based on SDSC’s OpenTopography portal, which will be scaled up to a national facility to make topography data available in multiple formats. This includes “raw” LiDAR point cloud data, standard LiDAR-derived digital elevation models, and easily accessible Google Earth products to better serve LiDAR users at various levels of expertise.

OpenTopography currently hosts and distributes a limited number of data sets acquired with funding from the NSF, NASA, and the U.S. Geological Survey ( USGS ). It is the product of the NSF-funded GEON ( GeoSciences Network ) project that has developed cyberinfrastructure for the integration of three- and four-dimensional earth science data.

“The fundamental goal of this project is to provide centralized access to community earth science LiDAR topography data,” said Christopher Crosby, SDSC’s project manager for the OpenTopography Facility.  “There is wealth of public domain LiDAR data available, but much of it is not yet easily accessible. We intend to leverage available cyberinfrastructure to make these powerful data sets, as well as online processing tools and knowledge resources, accessible to a large and diverse user community.”

The OpenTopography Facility will be primarily focused on large, community-oriented, scientific data sets, while building collaborations with existing LIDAR topography data providers and hosts such as the USGS and the NSF-funded National Center for Airborne Laser Mapping ( NCALM ) to link to their data archives and/or to host and distribute their data. An advisory committee representing OpenTopography users will prioritize which data sets are of greatest value to the community.

As one of the most powerful tools available to study the earth’s surface, overlying vegetation and man-made structures, high-resolution LiDAR data sets are widely regarded as revolutionary for earth science, environmental and engineering applications, as well as natural hazard studies. LiDAR makes it possible to generate digital elevation models ( DEMs ) at resolutions that are more than one order of magnitude better than those currently available. Moreover, large geographic areas can be surveyed at relatively low expense.

“LiDAR topography data is revolutionizing the way we study the geomorphic processes acting along the Earth’s surface,” said Ramon Arrowsmith, associate professor in the School of Earth and Space Exploration at Arizona State University and project co-investigator. “From earthquake hazards research to examining the impact of human development on natural systems, LiDAR is emerging as a fundamental tool.”

“High-resolution topographic data collection is burgeoning for research, planning and regulatory activities, yet the massive size of the data sets has made online community access to them difficult,” said Chaitan Baru, SDSC Distinguished Scientist and principal investigator for OpenTopography and GEON. “LiDAR is an interesting test case because of those data volumes and the on-demand access our users require, but ultimately the strategies developed in this work could be applied to all types of scientific data over a very wide range of domains.”

OpenTopography addresses the basic challenge of how to efficiently manage, archive, distribute process and integrate tens of terabytes of community geospatial data. Many organizations that acquire LiDAR topography do not have the disk space, bandwidth, and in-house expertise necessary to make these data available via the Internet for community-level access and analysis.

The OpenTopography LiDAR Facility is funded under NSF award number 0930731 ( SDSC ) and 0930643 ( ASU ).

About SDSC

As an organized research unit of UC San Diego, SDSC is a national leader in creating and providing cyberinfrastructure for data-intensive research. Cyberinfrastructure refers to an accessible and integrated network of computer-based resources and expertise, focused on accelerating scientific inquiry and discovery. SDSC recently doubled its size to 160,000 square feet with a new, energy-efficient building and data center extension, and is a founding member of TeraGrid, the nation’s largest open-access scientific discovery infrastructure.

[Source: SDSC press release]

USFWS Biological Science Technician (Wildlife) in Bismarck, North Dakota

In Environmental Science, GIS, Imagery, Statistics on January 13, 2010 at 10:36 am

U.S. Fish & Wildlife Service
Vacancy Announcement
R6-10-310487-D

Open Period:  January 07-21, 2010

BIOLOGICAL SCIENCE TECHNICIAN – WILDLIFE

The U.S. Fish and Wildlife Service, Region 6, Habitat and Population Evaluation Team (HAPET), Bismarck ND, will be hiring a biological science technician to assist staff biologists with the collection and processing of wildlife population and habitat data in an ongoing breeding waterfowl survey.

The candidates primary duties will involve the processing of aerial photography using specialized software and photo interpretation techniques for the delineation of wetlands, entry of field data into databases, and the building of spatial data using GIS software. These duties will require extended periods of sitting and viewing computer and video monitors.  The candidate will also be involved in collection of field data for several ongoing wildlife and habitat surveys.  A valid drivers license is necessary.  Basic GIS and statistics background a plus.

Salary range is $31,315 to $40,706, depending on qualifications and experience.  This is a full-time, TERM position not to exceed 13 months.

This position may be extended for a total appointment of 4 years.  Position will be based in Bismarck, North Dakota. This position offers a great opportunity to experience the wildlife of the Prairie Pothole Region and to work with waterfowl and non-game biologists who are conserving wetland and grassland habitat in the region.  Candidate will be stationed at a leading landscape ecology and conservation GIS facility.

Apply for the job at http://www.usajobs.gov/.  Search Jobs for R6-10-310487-D; position is Biological Science Technician (Wildlife).

Application period ends January 21, 2010.

For more information, contact Brian Wangler (701-355-8536,
Brian_Wanlger@fws.gov) or Ron Reynolds (701-355-8535, Ron_Reynolds@fws.gov).

Fishing Ground Prediction Using a Knowledge-based Expert System Geographical Information System Model in the South and Central Sulawesi Coastal Waters of Indonesia

In GIS, Imagery, Modeling on January 8, 2010 at 7:30 am

International Journal of Remote Sensing, Volume 30, Issue 24 2009 , pages 6429 – 6440

M. Sadly;  N. Hendiarti;  S. I. Sachoemar; Y. Faisal

“A knowledge-based expert system model working on the basis of a geographical information system (GIS) was applied to predict fishing ground spots in the coastal waters of South and Central Sulawesi. The model is designed by the integration of multisource data to answer ‘what?’, ‘where?’, and ‘why?’ questions of the fishing ground location. Despite the fact that GIS is a powerful tool for dealing with the first two questions, GIS is inferior for answering the ‘why?’ question in geo-studies. One of the possible ways of overcoming the inferiority of GIS for answering the ‘why?’ question of geo-studies is by integrating an expert system in a GIS to form a knowledge-based expert system GIS model. In this study, we used a series of sea surface temperature (SST) satellite data, sea surface chlorophyll-a (SSC) and turbidity derived from MODIS Aqua in the period 2003-2005 as input data, to understand the temporal and seasonal variability of the marine environment of the study area, and identified the oceanographic phenomena, i.e. upwelling, front or eddy. A spatial configuration map of the predicted fishing ground spots was then developed and integrated using a knowledge-based expert system GIS model generated by the Erdas Macro Language (EML) of Erdas Imagine 9.0 software. To verify this result, a series of in situ fishing ground spot data of the study area were collected for similar periods, and they were then analysed using a simple statistical method. The result shows that the predicted fishing ground spots generated by the knowledge-based expert system GIS model corresponded well with in situ data with a high accuracy level of 85%. This result has demonstrated that the knowledge-based expert system GIS model can be applied to predict, localize and determine fishing ground spots in which their accuracy level will be determined by the completeness of spatial knowledge of the domain expertise and the sophistication level of the programming utilities being used.”

Directory of GIS Conference Proceedings

In Conferences, ESRI, Environmental Science, GIS, GIScience, Geography, Imagery, Modeling, Science on January 5, 2010 at 1:01 pm

[Source: ESRI GIS Bibliography,  http://training.esri.com/campus/library]

AAG Annual Meetings
2007 2002 2000 1999 1998 1995 1993 1991 1990 1989 1987 1978 1971 1970 1969

ACM CIKM Proceedings
2003 2002 2001

ACM Symposium on Advances in Geographic Information Systems
2006 2003 2002 2001 2000 1999 1998 1997 1996

ACM/IEEE-CS Proceedings
2002

ACSM/ASPRS Proceedings
2002 1997 1996 1995 1994 1993 1992 1991 1990 1989 1988 1985 1982

Advances in Spatial Databases (SSD)
1995 1993

AGI Conferences
1997

ASPRS Proceedings
2006 2001 2000 1998 1995 1994

ASPRS/ISPRS Proceedings
2003 2002

Association of Geographic Information Laboratories Europe (AGILE)
2007 2006 2005 2004 2003 2002 2001 2000

AutoCarto Proceedings
2008 2006 2005 1997 1995 1993 1991 1989 1987 1986 1983 1979 1975

COSIT Proceedings
2007 2005 2003 2001 1999 1997 1995 1993 1992

Earth Observation & Geo-Spatial Web and Internet Workshop (EOGEO)
1998

ESRI Education User Conferences
2009 2008 2007 2006 2005 2004 2003 2002 2001

ESRI European User Conferences
2006 2003 2002 1999 1998 1997 1996

ESRI International User Conferences
2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 1995 1994 1993 1992 1991 1990 1989

ESRI Survey & Engineering GIS Summits
2009 2008 2007 2006

European Conference on Geographical Information Systems (EGIS)
1994 1993 1992 1991 1990

European GIS Education Seminar (EUGISES)
2004 2002 2000

Geo-Spatial Education
2000

GeoComputation
2003 2000 1999 1998 1997 1996

GeoTec
2006

GIS Planet
2005

GIS/LIS Proceedings
1998 1997 1996 1995 1994 1993 1992 1991 1990 1989 1988 1987 1986

GIScience
2004 2002 2000

GITA
2007 2006 2005 2004 2003 2002 2001 2000 1999

Harvard Library of Computer Graphics Mapping Collection
1981 1980 1979

Harvard Papers on Geographic Information Systems
1978

ICA abstracts
2007 2006 2005 2003 2001 1999 1997 1989

IEEE Proceedings
1997

Integrating GIS and Environmental Modeling
2000 1996 1993

International Federation of Surveyors
2007 2006 2005 2002

International Symposia on Spatial Data Handling
2004 1994 1992 1990 1988 1986 1984

Interop ’99
1999

Symposia on Geographic Information Systems for Transportation (GIS-T)
1998 1996 1995 1994

Urban and Regional Information Systems Association (URISA)
2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 1995 1994 1993 1992 1991 1990 1989 1988 1987 1967

URISA GIS in Addressing
2007 2006 2005 2004 2000

URISA GIS/CAMA Technologies
2004

URISA Integrating GIS and CAMA
2007 2006 2005 2004 2003 2002 2001 2000

URISA IT/GIS in Public Works
2004 2002 2001

URISA Public Participation GIS (PPGIS)
2005 2004 2003

Generative Statistical 3D Reconstruction of Unfoliaged Trees from Terrestrial Images

In Environmental Science, Imagery, Statistics on January 5, 2010 at 6:58 am

Annals of GIS, Volume 15, Issue 2 December 2009 , pages 97 – 105

Hai Huang; Helmut Mayer

“This article presents a generative statistical approach for the automatic three-dimensional (3D) extraction and reconstruction of unfoliaged deciduous trees from terrestrial wide-baseline image sequences. Unfoliaged trees are difficult to reconstruct from images because of partially weak contrast, background clutter, occlusions, and particularly the possibly varying order of branches in images from different viewpoints. This work combines generative modeling by L-systems and a statistical approach for maximum a posteriori estimation for the reconstruction of the 3D branching structure of trees. Background estimation is conducted by means of gray scale morphology to provide a good basis for generative modeling. A Gaussian likelihood function based on intensity differences is used to evaluate the hypotheses. The target tree is classified into three typical branching types after the extraction of the first level of branches and specific production rules of an L-system are used. Generic prior distributions for parameters are refined based on already extracted branches in a Bayesian framework and are integrated into the maximum a posteriori estimation. By these means most of the branching structure besides the tiny twigs can be reconstructed. The results are presented in the form of virtual reality modeling language models and show the potential of the approach.”

On Three-dimensional Visualization of Geospatial Information: Graphics Based or Imagery Based?

In GIS, Imagery, Visualization on January 4, 2010 at 9:10 am

Annals of GIS, Volume 15, Issue 2 December 2009 , pages 75 – 84

Li Deren;  Wang Mi;  Hu Qingwu; Hu Fen

“The three-dimensional (3D) visualization of geospatial information constitutes a fundamental property of the geo-information services nowadays, along with the requirements of popularity, openness and capabilities of target measuring and knowledge mining. Accordingly, in this article, the two major technical routines now applied to 3D visualization of geospatial information, that is the graphics-based approaches and the imagery-based approaches, are both described and discussed. After a comparative analysis of both advantages and disadvantages of the two manifestation modes, an optimized integrative strategy for 3D visualization of geospatial information is proposed finally.”

Evaluating Indiana Bat Summer Habitat on Surface Coal Mine Sites in Southwestern Indiana Using Remote Sensing

In Environmental Science, Geography, Imagery on December 30, 2009 at 10:41 am

Shunfu Hu, Michael J. Starr, Randall Pearson, Department of Geography, Southern Illinois University Edwardsville

“Indiana bat is among first endangered species list by the federal government due to fragmentation or the loss of its summer habitat. Forest canopy, certain degree of “patchiness”, and summer roosting sites (i.e., snags) appear to be key elements in habitat quality for the Indiana bat. This paper presents a methodology of evaluating Indiana bat summer habitat on or near surface coal mine sites in southwestern Indiana. Three levels of evaluation on Indiana bat summer habitat were performed using remotely sensed data. Level 1 evaluation was based on Landsat 7 Enhanced Thematic Mapper Plus (ETM+) satellite imagery with 30-meter spatial resolution to obtain a general idea of land use and land cover in the study area, which helps to eliminate areas with low bat habitat potential (e.g., urban and agricultural areas). Level 2 evaluation was based on QuickBird satellite imagery with 2.44-meter spatial resolution, which enables us to identify the characteristics of forest canopy such as edges and patchiness and to again eliminate areas with low bat habitat potential (e.g., low patchiness or immature forest). Level 3 evaluation was based on high resolution digital aerial multispectral imagery with a spatial resolution of 0.323-meter (1 foot), which enables us to identify a much greater detail (e.g., individual trees). It is anticipated that the three levels of evaluation of Indiana Bat summer habitat will allow us to develop a “suitability index” that can be used to better assess and monitor Indiana summer habitat.”

Source: Proceedings of the 32nd Annual Applied Geography Conference, October 28-31, 2009.

Evaluation of the Self-Organizing Map Classifier for Building Detection from Lidar Data and Multispectral Aerial Images

In GIScience, Imagery on December 28, 2009 at 9:28 am

Journal of Spatial Science, Vol. 54, No. 2

M.  Salah, J. Trinder, A. Shaker

“Integration of aerial images and lidar data compensate for the individual weaknesses of each data set when used alone, thus providing more accurate classification of terrain cover, such as buildings, roads and green areas, and advancing the potential for automation of large scale digital mapping and GIS database compilation. This paper presents work on the development of automatic feature extraction from multispectral aerial images and lidar data. A total of 22 feature attributes have been generated from the aerial image and the lidar data which contribute to the detection of the features. The attributes include those derived from the Grey Level Co-occurrence Matrix (GLCM), Normalized Difference Vegetation Indices (NDVI), and standard deviation of elevations and slope. A Self-Organizing Map (SOM) was used for fusing the aerial image, lidar data and the generated attributes for building detection. The classified images were then processed through a series of image processing techniques to separate the detected buildings. Results show that the proposed method can extract buildings accurately. Compared with a building reference map, 95.5 percent of the buildings were detected with a completeness and correctness of 83 percent and 80 percent respectively for buildings around 100m2 in area; these measures increased to 96 percent and 99 percent respectively for buildings around 1100m2 in area. Further, the contributions of lidar and the individual attributes to the quality of the classification results were evaluated.”

An Improved Approach for DSM Generation from High-Resolution Satellite Imagery

In GIScience, Imagery on December 28, 2009 at 8:44 am

Journal of Spatial Science, Vol. 54, No. 2

C. Zhang, C. S. Fraser

“This paper develops an improved approach to digital surface model (DSM) generation from high-resolution satellite imagery (HRSI).  The approach centres upon an image matching strategy that integrates feature point, grid point and edge matching algorithms within a coarse-to-fine hierarchical process. The starting point is a knowledge of precise sensor orientation, achieved in this case through bias-compensated rational polynomial coefficients (RPCs), and the DSM is sequentially constructed through a combination of the matching results for feature and grid points, and edges at different image pyramid levels. The approach is designed to produce precise, reliable and very dense DSMs which preserve information on surface discontinuities. Following a brief introduction to sensor orientation modelling, the integrated image matching algorithms and DSM generation stages are described. The proposed approach is then experimentally tested through the generation of a DSM covering the Hobart area from a stereo pair of IKONOS Geo images. The accuracy of the resulting surface model is assessed using both ground checkpoints and a lidar DSM, with the results indicating that for favourable imagery and land cover, a heighting accuracy of 2 – 4 pixels can be readily achieved. This result validates the feasibility of the developed approach for DSM production from HRSI.”

Development of an Object-based Framework for Classifying and Inventorying Human-dominated Forest Ecosystems

In Environmental Science, Imagery on December 28, 2009 at 6:48 am

International Journal of Remote Sensing, Volume 30, Issue 23 2009 , pages 6343 – 6360

Weiqi Zhou; Austin Troy.

“This paper presents the development of a framework for classifying and inventorying Eastern US forestland based on the level of anthropogenic disturbance and fragmentation using high spatial resolution remote sensing data and a multiscale object-based classification system. We implemented the framework using a suburban area in Baltimore County, Maryland, USA as a case study. We developed a three-level hierarchical scheme of image objects. The object-based, multiscale classification and inventory framework provides an effective and flexible way of showing different mixes of human development and forest cover in a hierarchical fashion for human-dominated forest ecosystems. At the finest scale (level 1), the classification nomenclature describes basic land cover feature types, which are divided up into trees and individual features that fragment forests. The overall accuracy of the classification was 91.25%. At level 2, forest patches were delineated and classified into different categories based on the degree of human disturbance. At level 3, major roads were used to segment the study area into larger objects, which were classified on the basis of relative composition and spatial arrangement of forests and fragmenting features. This study provides decision makers, planners and the public with a new methodological framework that can be used to more precisely classify and inventory forest cover. The comparisons of the estimates of forest cover from our analyses with those from the 2001 National Land Cover Dataset (NLCD) show that aggregated figures of forest cover are misleading and that much of what is mapped as forest is highly degraded and is more suburban than natural in its land use.”

Use of Remote Sensing Coupled with a Vegetation Change Tracker Model to Assess Rates of Forest Change and Fragmentation in Mississippi, USA

In Environmental Science, Imagery, Modeling on December 23, 2009 at 7:14 am

International Journal of Remote Sensing, Volume 30, Issue 24 2009 , pages 6559 – 6574

Mingshi Li;  Chengquan Huang;  Zhiliang Zhu;  Weisong Wen;  Da. Xu; Anxing Liu.

“Mapping forest disturbance history is essential for assessing forest fragmentation conditions and the effectiveness of management approaches, and it is crucial for the understanding of terrestrial and atmospheric carbon flux. In this study, our analysis maps and characterizes the wall-to-wall forest change patterns in Mississippi over the time period 1987-2005, by interpreting 132 Landsat Thematic Mapper (TM) or Enhanced Thematic Mapper Plus (ETM+) scenes using a vegetation change tracker (VCT) model. Our analysis revealed that a gradual decelerating forest fragmentation during the time period 1987-1993 gave way to an accelerating fragmentation during the period 1994-2005. This unique trend in forest fragmentation was a consequence of forest logging, regeneration practices and natural disturbance regimes. In addition, for the most part of the 1990s and between 2000 and 2005, Mississippi lost about 2% of its forest on an annual basis, but many of the losses were offset by forest regeneration from previous disturbances. Forest spatial change information derived from this analysis has provided valuable insights regarding regional forest management practices and socioeconomic impacts, which will be beneficial for land managers to develop ecologically sustainable forest management strategies and biodiversity conservation practices.”

Lineament Mapping in a Tropical Environment using Landsat Imagery

In Environmental Science, Imagery on December 22, 2009 at 7:25 am

International Journal of Remote Sensing, Volume 30, Issue 23 2009 , pages 6277 – 6300

M. F. Ramli;  N. K. Tripathi;  N. Yusof;  H. Z. M. Shafri; Z. Ali Rahman.

“Remote sensing has proved to be a useful tool in lineament identification and mapping. This study demonstrates the use of multispectral Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM +) satellite data obtained over two acquisition dates in 1990 and 2002 for lineament interpretation in a Malaysian tropical environment. A digital elevation model (DEM) was generated to improve the interpretation. We found that most of the major orientations in the field station could be successfully detected from the remotely sensed imagery. The results from the study show that the remote sensing technique is capable of extracting lineament trends in an inaccessible tropical forest.”

  • More information

2010 IEEE International Geoscience and Remote Sensing Symposium, Honolulu, Hawaii, 25-30 July 2010

In Conferences, Imagery on December 21, 2009 at 8:48 am

“On behalf of the IEEE Geoscience and Remote Sensing Society and the IGARSS 2010 Organizing Committee, we are pleased to invite you to Honolulu for IGARSS 2010. We are thrilled to be returning to Hawaii to host IGARSS on its 30th anniversary! In the true spirit of an international event, we will continue our tradition of gathering world-class scientists, engineers, and educators engaged in the fields of geosciences and remote sensing from around the world. We anticipate well over one thousand participants to enjoy a week of technical sessions, tutorials, exhibits and social activities.

“For this 30th anniversary IGARSS we will celebrate our accomplishments over three decades of leadership in remote sensing instrumentation, techniques, and applications development. But perhaps more importantly we will look ahead to the future of our field with some fresh approaches and perspectives through our conference theme: Remote Sensing: Global Vision for Local Action. One such activity will be embodied in our plenary session, which will focus on the emerging field of Community Remote Sensing. We hope this plenary session, along with special tutorials and technical sessions, will inspire and excite our community for what is possible in the coming decade. We look forward to seeing you in Honolulu in July 2010!”

Estimating Aboveground Biomass of Grassland Having a High Canopy Cover: An Exploratory Analysis of In Situ Hyperspectral Data

In Environmental Science, Imagery on December 21, 2009 at 6:53 am

International Journal of Remote Sensing, Volume 30, Issue 24 2009 , pages 6497 – 6517

Jin Chen;  Song Gu;  Miaogen Shen;  Yanhong Tang; Bunkei Matsushita.

“To improve the estimation of aboveground biomass of grassland having a high canopy cover based on remotely sensed data, we measured in situ hyperspectral reflectance and the aboveground green biomass of 42 quadrats in an alpine meadow ecosystem on the Qinghai-Tibetan Plateau. We examined the relationship between aboveground green biomass and the spectral features of original reflectance, first-order derivative reflectance (FDR), and band-depth indices by partial least squares (PLS) regression, as well as the relationship between the aboveground biomass and narrow-band vegetation indices by linear and nonlinear regression analyses. The major findings are as follows. (1) The effective portions of spectra for estimating aboveground biomass of a high-cover meadow were within the red-edge and near infrared (NIR) regions. (2) The band-depth ratio (BDR) feature, using NIR region bands (760-950 nm) in combination with the red-edge bands, yields the best predictive accuracy (RMSE = 40.0 g m-2) for estimating biomass among all the spectral features used as independent variables in the partial least squares regression method. (3) The ratio vegetation index (RVI2) and the normalized difference vegetation index (NDVI2) proposed by Mutanga and Skidmore (Mutanga, O. and Skidmore, A.K., 2004a, Narrow band vegetation indices solve the saturation problem in biomass estimation. International Journal of Remote Sensing, 25, pp. 1-6) are better correlated to the aboveground biomass than other VIs (R2 = 0.27 for NDVI2 and 0.26 for RVI2), while RDVI, TVI and MTV1 predicted biomass with higher accuracy (RMSE = 37.2 g m-2, 39.9 g m-2 and 39.8 g m-2, respectively). Although all of the models developed in this study are probably acceptable, the models developed in this study still have low accuracy, indicating the urgent need for further efforts.”

Mapping Urban Areas on a Global Scale: Which of the Eight Maps Now Available is More Accurate?

In Geography, Imagery on December 18, 2009 at 7:35 am

International Journal of Remote Sensing, Volume 30, Issue 24 2009 , pages 6531 – 6558

David Potere;  Annemarie Schneider;  Shlomo Angel; Daniel L. Civco.

“Eight groups from government and academia have created 10 global maps that offer a ca 2000 portrait of land in urban use. Our initial investigation found that their estimates of the total amount of urban land differ by as much as an order of magnitude (0.27-3.52 times106 km2). Since it is not possible for these heterogeneous maps to all represent urban areas accurately, we undertake the first global accuracy assessment of these maps using a two-tiered approach that draws on a stratified random sample of 10 000 high-resolution Google Earth validation sites and 140 medium-resolution Landsat-based city maps. Employing a wide range of accuracy measures at different spatial scales, we conclude that the new MODIS 500 m resolution global urban map has the highest accuracy, followed by a thresholded version of the Global Impervious Surface Area map based on the Night-time Lights and LandScan datasets.”

NSF Awards SDSC, Arizona State University $1.7 Million for National OpenTopography LiDAR Facility

In GIS, Imagery, Science on December 16, 2009 at 7:32 am

The San Diego Supercomputer Center (SDSC) at UC San Diego and Arizona State University have been awarded a $1.7 million grant from the National Science Foundation (NSF) to operate  an internet-based national data facility for high-resolution topographic data acquired with LiDAR (Light Detection and Ranging) technology.  The facility will also provide online processing tools and act as a community repository for information, software and training materials.

The three-year project, which includes a grant of $1.4 million to SDSC and $300,000 to the School of Earth and Space Exploration at Arizona State University, will be based on SDSC’s OpenTopography portal, which will be scaled up to a national facility to make topography data available in multiple formats. This includes “raw” LiDAR point cloud data, standard LiDAR-derived digital elevation models, and easily accessible Google Earth products to better serve LiDAR users at various levels of expertise.

OpenTopography currently hosts and distributes a limited number of data sets acquired with funding from the NSF, NASA, and the U.S. Geological Survey (USGS). It is the product of the NSF-funded GEON (GeoSciences Network) project that has developed cyberinfrastructure for the integration of three- and four-dimensional earth science data.

“The fundamental goal of this project is to provide centralized access to community earth science LiDAR topography data,” said Christopher Crosby, SDSC’s project manager for the OpenTopography Facility.  “There is wealth of public domain LiDAR data available, but much of it is not yet easily accessible. We intend to leverage available cyberinfrastructure to make these powerful data sets, as well as online processing tools and knowledge resources, accessible to a large and diverse user community.”

[Source: SDSC press release]

Michigan Tech Research Institute Image Analyst Receives Top Honor in Field

In Imagery on December 8, 2009 at 7:49 am

…from Michigan Tech News…

“Chuck Olson has been doing image interpretation and analysis for more than half a century.  Now the senior image analyst at the Michigan Tech Research Institute (MTRI) in Ann Arbor has been recognized for his contributions with one of the highest honors his professional society can confer: Honorary Member of the American Society for Photogrammetry and Remote Sensing (ASPRS).

““This is a very big deal,” said Colin Brooks, research scientist and manager of the Environmental Science Laboratory at MTRI.  “It is ASPRS’s highest award, and there are only 25 honorary members at any one time.”

“The lifetime award is given to recognize individuals who have rendered distinguished service to ASPRS or who have attained distinction in advancing the science and use of geospatial information. Olson qualifies on both counts.”

Representing Reality: Imagery in the Cognitive, Social and Natural Sciences–12-15 May 2010, University at Buffalo

In Conferences, GIS, GIScience, Imagery, Science on December 4, 2009 at 7:25 am

A Conference presented by the University at Buffalo IGERT in GIScience

Deadline for submitting an abstract is 31 January 2010

“The use of imagery in representing reality has become pervasive throughout our world. With the advent of publicly-available geographic services such as Google Maps, advanced medical technologies for rendering genes and cells, and a multitude of satellites amassing data from remote locations, spaces and objects that were once abstractions can now be perceived in new and tangible ways.

“The GIScience IGERT at the University at Buffalo will be hosting a conference May 12-15, 2010 at the Adams Mark Hotel in downtown Buffalo, NY to address the theory and application of imagery across academic disciplines. In particular, this conference aims to attract Ph.D. students and faculty from IGERT programs, as well as researchers from a wide range of subjects, who incorporate innovative image resources into their research or address the conceptualization of reality as a digital format. The agenda will include featured speakers, research presentations, poster sessions and specialized breakout discussions.

“Additional target objectives of the conference include providing a forum for future multi-disciplinary collaborations in this genre and facilitating discussions on the advantages and disadvantages of an interdisciplinary approach to image analysis. The unique challenges and opportunities facing interdisciplinary researchers in an academic workforce will also be addressed.”

Lidar Solutions in ArcGIS: Three New Web-based Lidar Courses

In ESRI, GIS, Imagery on November 30, 2009 at 8:36 am

Due to the demand for lidar training, ESRI’s Training Center now offers three web-based courses on lidar. First is a free training seminar that provides an overview of lidar capabilities in ArcGIS and introduces high level concepts. The other two include hands-on exercises and are geared toward data managers and analysts.

Using AIRS Data with ArcGIS

In ESRI, GIS, Imagery on November 30, 2009 at 7:41 am

…from NASA/JPL/Cal tech…

“Geographic Information Systems (GIS) are computer applications that incorporate geographical features with tabular data in order to map and analyze real-world problems. ArcGIS is a system introduced by a company called Environmental Systems Research Institute, Inc. (ESRI) to meet the needs of a wide range of GIS users.

“On the blog titled ‘GIS and Science’ maintained by the GIS and Science Program Manager for ESRI, a number of ‘how-to’ videos are outlined that detail using AIRS data with ESRI GIS tools. The tools are developed on top of ESRI’s ArcGIS suite of GIS products utilizing ArcObjects.

“These videos demonstrates a component of a series of tools developed by the Redlands Institute at the University of Redlands, CA as part of a collaborative project with JPL to download, visualize, and analyze source AIRS satellite sounder data.”

Satellite Data Detects Ozone Hole

In Climate Change, Environmental Science, Imagery, Video, Visualization on November 18, 2009 at 6:33 am

…from NOAA’s Environmental Visualization Laboratory…

ozone

“The ozone layer protects Earth from harmful ultraviolet solar radiation. Ozone is a gas made of three oxygen atoms, and just like any other gas it circulates in the atmosphere. During the fall months, chemical reactions combine with circulation patterns high in the atmosphere to reduce the concentration of ozone over Antarctica. Areas with ozone concentrations less than 220 Dobson Units are called “holes” in the layer. NOAA’s polar orbiting satellites are used to monitor the ozone hole and the data taken from the POES satellites over the past year is show in this animation. In 2009, the ozone hole reached its 10th largest measured size since careful measurements began in 1979. It appears, though, that the ozone hole is repairing itself after passage of the Montreal Protocol in 1989 that banned the use of ozone-depleting compounds such as chlorofluorocarbons(CFC’s) and hydrofluorocarbons (HFCs).”

Free U.S. Earth Imagery Sharpens Shared View of Global Challenges

In Citizen Science, Geography, Imagery, Science on November 17, 2009 at 8:59 am

USGS Director McNutt a Leader in U.S. Delegation at International Conference

Free, easily accessible U.S. satellite data enables any citizen, scientist, or analyst who can use the information to contribute to a shared vision of the challenges facing our planet.

That’s the message the newly-appointed director of the U.S. Geological Survey, Dr. Marcia McNutt, plans to deliver when representatives of 80 governments and over 50 participating organizations convene at the international Group on Earth Observations (GEO-VI) meeting, November 16-17, in Washington, D.C.

“Our policy of providing free Landsat data supports a central GEO goal: to promote global distribution of earth observation data,” said McNutt. “With a continuous record of earth observation since 1972, Landsat provides the most complete set of land surface information as well as a vital historical perspective for researchers, decision makers, and commercial users around the world.”

From over 400 miles above Earth, the scale of Landsat imagery makes it particularly useful in understanding natural and human-induced changes to the planet. The data enable a wide array of investigations — from supporting disaster relief efforts to making agricultural crop assessments to correlating environmental conditions with famine, biodiversity, and human health.

Beginning with the launch of Landsat 1 in 1972, Landsat, a joint operation of USGS and NASA, has produced over two million space-based, moderate-resolution, land remote sensing images. The massive data archive is maintained at the USGS-EROS facility in Sioux Falls, S.D.

“As the world’s increasing population is compelled to face the effects of climate change and the limitations of water, petroleum, and other vital resources, the broad availability of images from Landsat and other earth observation satellites benefits both developing and developed countries,” said Dr. McNutt. McNutt became the 15th USGS Director on November 5.

USGEO, the American contribution to GEO, is sponsored by 15 federal agencies and two White House offices.

“I am very pleased to note that it was the agency I now direct, USGS, that opened the Landsat archive to the world free of charge,” McNutt continued. “Since the archive was opened, over 1 million images have been provided to users from 180 countries — a resounding success.”

For further information, visit:

[Source: USGS news release]

Free Training Seminar: Getting Started with Lidar in ArcGIS

In ESRI, GIS, Imagery on November 17, 2009 at 8:13 am

esriThis seminar introduces lidar in general, discusses how to manage lidar data using ArcGIS, and also addresses the needs of those who would like to know the benefits of using lidar data in ArcGIS.

Lidar datasets are massive and contain three-dimensional spatial information about features such as buildings, trees, power lines, etc. Lidar datasets are raw point cloud formats that are not easily interpreted. ArcGIS Spatial Analyst and ArcGIS 3D Analyst provide the functionality and tools you need to represent and extract feature information from lidar data.

The presenter will discuss:

  • Introduction to lidar
  • Understanding and interpreting lidar data using ArcGIS
  • Lidar applications and derived products using ArcGIS

More information

Arctic Sea Ice Reaches Third Lowest Minimum Extent

In Climate Change, Environmental Science, Imagery, Video, Visualization on November 17, 2009 at 8:13 am

…from NOAA’s Environmental Visualization Laboratory…

seaice

“On Sept 12, 2009, the extent of sea ice in the Arctic reached the third lowest level ever recorded since satellite records began in 1979. The National Snow and Ice Data Center estimates that the overall extent dropped to 5.1 million square kilometers, well below the average minimum extent of 6.71 million square kilometers (1979-2000). Only 2007 and 2008 have had lower ice extents. The small increase in 2009 was mostly due to ice spreading caused by strong polar winds. Ice concentration and thickness, however, have not increased, making predictions about a rebound in Arctic ice premature at this moment.”

Celebrate Geography Awareness Week

In Education, GIS, Geography, Imagery on November 16, 2009 at 8:57 am

logo_gaw“Get Lost in Mapping: Find Your Place in the World

“Maps are all around us. New technologies like sophisticated satellite imagery and geographic information systems (GIS) have taken maps out of atlases and into the palm of your hand. Discover maps where you never expected to find them—GPS devices, online sites, news broadcasts, social networking, and maybe even your own phone.

“Geography Awareness Week 2009 explores the world through mapping. Find your continent in giant tile maps, find your country in political outline maps, find your local area through community mapping tools like FieldScope and find your place in the world!

“Teachers, take advantage of National Geographic’s Geography Action! program. This year, your students can build a free wall-sized map of Europe or America right in their own classroom.

“At home, get in the sprit of adventure and discovery by tuning into National Geographic Channel’s Expedition Week, starting November 15.”

The Watchful Eye of GOES

In Environmental Science, Imagery, Video, Visualization on November 16, 2009 at 7:31 am

…from NOAA’s Environmental Visualization Laboratory…

geos

“The Geostationary Operational Environmental Satellite (GOES) is one of NOAA’s most useful tools for understanding our planet. Situated 35,000km above the equator in outer space, the satellite provides a constant stream of data and imagery back to Earth as it observes clouds, ocean temperatures, winds, atmospheric properties, severe storm systems, fires and many other environmental parameters. NOAA uses two GOES satellites to provide coverage of the Western Hemisphere, including the U.S. territories in the Pacific. This visualization uses a variety of datasets from GOES to demonstrate the versatility and importance of these satellites.”

Salt Lake City Solar Energy Potential Modeling: An Ignite-Style Presentation

In Environmental Science, GIS, Imagery, Modeling on November 3, 2009 at 5:45 am

slc…from the Utah GIS Portal…

“One of the challenges that GIS professionals and the GIS field as a whole face is communicating the complexity of GIS technologies (in general and specifically), effectively to non GIS audiences. Ignite style-presentations forces us to refine our messages and get them across efficiently. After all, if it takes more than 5 minutes and 20 slides to get a point across, just who are you going to be able to sell it too?”

Socioeconomic Indicators of Heat-related Health Risk Supplemented with Remotely Sensed Data

In Geography, Imagery, Social Science on November 2, 2009 at 7:18 am

International Journal of Health Geographics 2009, 8:57

Daniel P Johnson, Jeffrey S Wilson, George C Luber

Background

Extreme heat events are the number one cause of weather-related fatalities in the United States. The current system of alert for extreme heat events does not take into account intra-urban spatial variation in risk. The purpose of this study is to evaluate a potential method to improve spatial delineation of risk from extreme heat events in urban environments by integrating sociodemographic risk factors with estimates of land surface temperature derived from thermal remote sensing data.

Results

Comparison of logistic regression models indicates that supplementing known sociodemographic risk factors with remote sensing estimates of land surface temperature improves the delineation of intra-urban variations in risk from extreme heat events.

Conclusion

Thermal remote sensing data can be utilized to improve understanding of intra-urban variations in risk from extreme heat. The refinement of current risk assessment systems could increase the likelihood of survival during extreme heat events and assist emergency personnel in the delivery of vital resources during such disasters.

Read the article [PDF]

Podcast: GIS and Remote Sensing for Wildlife Conservation

In ESRI, Environmental Science, GIS, Imagery on October 30, 2009 at 12:51 pm

Auralie Shapiro, Remote Sensing Specialist in the Conservation Science Program, talks about how GIS and remote sensing are used to study land use change, migration patterns, and natural threats to species to facilitate conservation efforts.

Status of the National Land Remote Sensing Outreach Act (H.R. 2489)

In Imagery on October 28, 2009 at 7:27 am

Yesterday, 27 October 2009, the U.S. House of Representatives passed the National Land Remote Sensing Outreach Act on a vote of 379 to 33.  The bill will now be forwarded to the Senate.

“The National Land Remote Sensing Outreach Act (H.R. 2489) would authorize $100 million over the FY 2010 through 2019 for the Department of Interior to establish a new national land remote sensing outreach program within the U.S. Geological Survey.  According to the legislation, the program’s mission would be to “advance the availability, timely distribution, and widespread use of geospatial imagery for education, research, assessment, and monitoring purposes in each State and the lands of an Indian tribe.”"

A summary of the bill can be found here.

Congressional Budget Office cost estimates for the bill can be found here.

Your representative: how did they vote?

Coverage in Prairie Business magazine.

Mapping Iraq’s Ancient Cities

In Geography, Imagery on October 28, 2009 at 7:03 am

…from DVIDS…

“While many Soldiers head home in the late hours of the second shift, Sgt. Ronald Peters sits at his desk scanning over imagery, maps and the Internet, sometimes as late as 5 a.m., looking for answers.

“Peters, a geospatial analyst from Fort Lewis, Wash., with Multi-National Corps-Iraq C-7, is undertaking the largest mapping projects of his career. His work is helping to resolve a concern shared by both the U.S. military and the Iraqi government as troops have pulled out of cities and continue the drawdown.”

China Expected to Complete World’s First Land Cover Map of Antarctica

In Geography, Imagery, Science on October 26, 2009 at 9:25 am

…from China View…

“Chinese scientists from the country’s 26th Antarctic expedition are expected to complete the world’s first land cover map of the Antarctica at the end of this year.

“It will be the most accurate map of the continent, presenting various land features, they told Xinhua correspondent aboard Xuelong (Snow Dragon) icebreaker in a recent interview.

“The research team will conduct wide range of field spectral collection on the Antarctica to provide data for the map.

“The map, with the application of high resolution remote sensing technology, will for the first time in the history show the distribution of key features on the continent, including sea ice, snow, blue ice, rocks, soil marshes, lakes and ice crevasse.”

LizardTech Introduces Free MrSID Plug-in for ArcGIS 3D Analyst

In ESRI, GIS, Imagery on October 20, 2009 at 10:45 am

LizardTech, a division of Celartem Inc. and a provider of software solutions for managing and distributing geospatial content, announced the release of the MrSID Plug-in for ArcGIS 3D Analyst at the GEOINT 2009 Symposium in San Antonio, Texas, hosted by the United States Geospatial Intelligence Foundation (USGIF) October 19-21, 2009. LizardTech is exhibiting in booth #517.

Until now, LizardTech’s customers, who widely use ArcGIS 3D Analyst, were not able to load point cloud datasets that were compressed to MrSID Generation 4 using LiDAR Compressor into ESRI’s 3D Analyst product. However, with the release of this free plug-in, 3D Analyst users can load point cloud datasets compressed to MrSID Generation 4 to create surfaces for use in line-of-sight and terrain modeling, visualization, and spatial analysis.

“LizardTech’s goal is to give customers tools for using their point cloud data compressed with LiDAR Compressor in the applications they use every day,” said Jon Skiffington, LizardTech director of marketing. “Many of our customers use ArcGIS, but were not able to use it with MrSID files created in LiDAR Compressor. Now our customers can easily load point cloud datasets compressed to MrSID Generation 4 into ESRI’s 3D Analyst product.”

The free MrSID Plug-in for ArcGIS 3D Analyst is available for download here: http://www.lizardtech.com/MrSID.html

Satellite Images of Nighttime Lights Give Clues to GDP

In Geography, Imagery, Social Science on October 15, 2009 at 7:24 am

gajitz…from gajitz.com…

“Economists are always interested in tracking the economic progress of countries around the world. However, that’s a difficult thing to do in undeveloped countries where records are rarely kept. Many countries do not even appear in the Penn World Tables, one of the most trusted compendiums of world economic data. Researchers at Brown University think that they’ve come up with an ingenious way of tracking the gross domestic product (GDP) of developing countries: they’ll do it from space.”

Silvilaser 2009: 9th International Conference on Lidar Applications for Assessing Forest Ecosystems

In Conferences, Environmental Science, Geography, Imagery on October 13, 2009 at 9:34 am

silvilaser-logo14-16 October 2009

Texas A&M University

Interdisciplinary Life Sciences Building (ILSB)

College Station, TX, USA

Automating Counts of Photographed Indiana Bats Using the ArcGIS Feature Analyst Extension

In ESRI, Environmental Science, GIS, Imagery on October 9, 2009 at 7:53 am

bats“The Indiana bat (Myotis sodalis) is a Federally listed endangered species found in the Midwest and eastern United States. Its population has profound implications for forest management throughout its range. Declining populations could lead to timber harvest restrictions and changes to other land management practices in Midwestern and eastern forests. The Forest Plan and Biological Opinion of the Hoosier National Forest (Indiana) require hibernacula (i.e., winter hibernation sites) occupied by the Indiana bat to be monitored regularly to assess changes in population numbers. State and U.S. Fish and Wildlife Service biologists survey the bats every other winter while the bats are hibernating. Because management decisions and recovery action priorities are based on the population estimates and trends determined from these surveys, it is critical that they are accurate. During the surveys, individual bats and small clusters are counted directly, but those in larger clusters are estimated by multiplying the approximate area of the cluster by an assumed bat packing density. Unfortunately, estimates derived by these techniques can be highly inaccurate. In many hibernacula, using a digital camera to document bat numbers could reduce stress to the bats and also increase the accuracy of the population estimate by allowing the bats to be counted manually on a computer screen in an office setting. Nevertheless, this is a very tedious and labor-intensive task that some state and federal agencies cannot afford. An accurate, rapid, and more cost-effective way to count photographed bats is needed. With sponsorship from the U.S. Department of Agriculture, Forest Service Remote Sensing Steering Committee, the Remote Sensing Applications Center conducted a study to investigate the feasibility of rapidly deriving accurate counts of photographed bats using Feature Analyst, an extension for ArcGIS. Counts derived with Feature Analyst were typically within one to nine percent of manually interpreted counts and processing times of less than four minutes per photo were achieved. This represents a significant improvement over traditional in-cave estimates and has the potential for high-volume use, which could further reduce the per photo processing time.”

Satellite Images and GIS Aid in Disease Mapping and Surveillance

In GIS, Imagery, Social Science on October 8, 2009 at 7:38 am

“Satellite images and Geographical Information Systems (GIS) can provide public health officials with vital information needed to detect and manage certain disease outbreaks. In order to properly plan, manage and monitor any public health system, it is very important to have up to date, relevant information available to decision-makers at all levels throughout all regions of the world.

“Also known as Landscape Epidemiology, which involves the identification of geographical areas where disease is transmitted. By knowing the vegetation and geologic conditions necessary for the maintenance of specific pathogens in nature, one can use the landscape to identify the spatial and temporal distribution of disease risk. Key environmental elements, including elevation, temperature, rainfall, and humidity, influence the presence, development, activity, and longevity of pathogens, vectors, zoonotic reservoirs of infection, and their interactions with humans.”

[Source: Satellite Imaging Corporation]

Video: Layers of Our World

In ESRI, GIS, Geography, Imagery on October 8, 2009 at 7:00 am

In this salute to GIS Day ESRI uses ArcGlobe 3D Analyst and ArcMap to provide multiple perspectives of Earth. Special thanks to Digital Globe and EarthSat for their images used in this video.

DigitalGlobe Satellite Imagery Helps Expose Atrocities Around the Globe

In Imagery, Science on October 4, 2009 at 6:05 pm

…from the Longmont Times-Call…

“Human rights violators around the globe, take note: You’re being watched.

“In Darfur, for example, groups such as Amnesty International have used satellite imagery to track atrocities, providing visual evidence contradicting claims that no crimes have been committed.

“Lars Bromley, the American Association for the Advancement of Science’s project director for its science and human rights program, said his organization provides ‘geo-spatial support’ to groups such as Amnesty International and Human Rights Watch.”

MESSENGER Flyby to Capture Additional Images of Mercury

In Imagery, Planetary GIS, Science on October 2, 2009 at 8:07 am

M3_coverage_ver4_med2…from Science@NASA…

“As the spacecraft approaches Mercury, cameras will photograph previously unseen terrain, and as the spacecraft departs it will take high-resolution images of the southern hemisphere. Scientists expect the spacecraft’s imaging system to take more than 1,500 pictures. So far, more than 90 percent of the planet’s surface has been photographed. These new pictures will fill in some of the gaps and provide high-resolution imagery of targets of interest.”

Mapping Bird Habitat with Lasers in Central California

In Environmental Science, Geography, Imagery on September 30, 2009 at 8:57 am

…from Psyorg.com…

“Lasers are providing scientists with new tools for mapping, protecting, and restoring bird habitat along rivers. In a paper published in the October issue of Ecological Applications, scientists from PRBO Conservation Science and the Information Center for the Environment at UC Davis used aerial laser technology known as LiDAR (short for Light Detection And Ranging) to predict where different bird species occur in the Cosumnes River Preserve in central California, USA.”

The FullCAM Carbon Accounting Model: Development, Calibration, and Implementation for the National Carbon Accounting System

In Climate Change, GIS, Imagery, Modeling, Spatial Analysis on September 25, 2009 at 8:55 am

aus_greenhouse“The Australian National Carbon Accounting System (NCAS) : supports Australia’s position in the international development of policy and guidelines on sinks activity and greenhouse gas emissions mitigation from land based systems; reduces the scientific uncertainties that surround estimates of land based greenhouse gas emissions and sequestration in the Australian context; provides monitoring capabilities for existing land based emissions and sinks, and scenario development and modelling capabilities that support greenhouse gas mitigation and the sinks development agenda through to 2012 and beyond; and provides the scientific and technical basis for international negotiations and promotes Australia’s national interests in international flora.

“Subsequent to the development of the Excel based CAMFor model for the Australian Greenhouse Office, work commenced on the development of an integrated model which combined the CAMFor model with the 3PG forest growth model, the GENDEC litter decomposition model and the Rothamsted soil carbon model (Roth C). A parallel version of the CAMFor model (CAMAg) was developed for agricultural systems and is also integrated with GENDEC and the Roth C model.

“The model developed, known as FullCAM, integrates the CAMFor and CAMAg based routines to a single C code model capable of carbon accounting in transitional (afforestation, reforestation and deforestation) and mixed (e.g. agroforestry) systems.

“The FullCAM model can be run in a spatial mode which will integrate information drawn from the remotely sensed land-cover-change program, productivity surfaces and other ancillary data to perform various accounting routines.”

Rome Digitally Rebuilt in Hours

In Imagery, Science on September 24, 2009 at 2:20 pm

Photo-Tourism2…from futurity.org…

“Using a new computer algorithm, researchers were able to take 150,000 tourist photos tagged “Roma” or “Rome” downloaded from the photo sharing Web site Flickr and combine them into a single 3-D digital model in about 21 hours.

““How to match these massive collections of images to each other was a challenge,” says Sameer Agarwal, acting assistant professor of computer science and engineering at the University of Washington.”

Texas City Proposes Tree-counting Initiative

In Environmental Science, GIS, Imagery, Spatial Analysis on September 23, 2009 at 4:02 pm

…from Pegasus News…

“The city of Denton is trying to protect its shade-bearing friends through the use of satellite imaging.

“The City Council discussed a possible survey at last week’s meeting that would determine the average number of trees and how to add more to the city.

“If the proposal is approved, the city of Denton will collaborate with UNT faculty and a graduate student to head up the research side of the project.”

Satellite Imagery Shows World’s River Deltas Sinking Due to Human Activity

In Climate Change, Environmental Science, Geography, Imagery on September 21, 2009 at 12:36 pm

Figure 2 Mekong & Myanmar & Pearl…from Futurity.org…

“Of the world’s 33 major deltas, 24 are sinking, in large part due to human activity, and 85 percent experienced severe flooding in recent years, a new study finds.

“The flooding resulted in the temporary submergence of roughly 100,000 square miles of land.  About 500 million people in the world live on river deltas.

“Using satellite data from NASA’s Shuttle Radar Topography Mission, which swept more than 80 percent of Earth’s surface during a 12-day mission of the space shuttle Endeavour in 2000, the  researchers compared the SRTM data with historical maps published between 1760 and 1922.”

Analysing, Mapping, and Evaluating Spatio-temporal Water Scarcity Problems, February 1st to 11th, 2010 in Salzburg, Austria

In Conferences, Environmental Science, GIS, Imagery, Spatial Analysis, Temporal Analysis, Visualization on September 21, 2009 at 6:25 am

“The Z_GIS Winter School 2010 is dedicated to the theme of analysing, mapping and evaluating spatio-temporal water scarcity problems and is hosted by Salzburg University’s Centre for Geoinformatics (Z_GIS).

“Participants with an interest in GIS, Remote Sensing and Hydrology are welcome to attend the short intensive course in the world cultural heritage city of Salzburg.”

Uncertainty Management in Remote Sensing of Climate Data: Workshop Summary

In Books, Climate Change, Environmental Science, Imagery, Science on September 17, 2009 at 7:28 am

0309139589…new from The National Academies Press…

“Great advances have been made in our understanding of the climate system over the past few decades, and remotely sensed data have played a key role in supporting many of these advances. Improvements in satellites and in computational and data-handling techniques have yielded high quality, readily accessible data. However, rapid increases in data volume have also led to large and complex datasets that pose significant challenges in data analysis. Uncertainty characterization is needed for every satellite mission and scientists continue to be challenged by the need to reduce the uncertainty in remotely sensed climate records and projections. The approaches currently used to quantify the uncertainty in remotely sensed data lack an overall mathematically based framework. An additional challenge is characterizing uncertainty in ways that are useful to a broad spectrum of end-users.

“In December 2008, the National Academies held a workshop, summarized in this volume, to survey how statisticians, climate scientists, and remote sensing experts might address the challenges of uncertainty management in remote sensing of climate data. The workshop emphasized raising and discussing issues that could be studied more intently by individual researchers or teams of researchers, and setting the stage for possible future collaborative activities.”

Update: Lidar Solutions in ArcGIS

In ESRI, GIS, Imagery, Science on September 16, 2009 at 6:56 am

lidar[Update: since first posting this back on May 1st, Clayton has added three new posts in this series.]

Clayton Crawford, Product Engineer in ESRI’s Software Products Group’s 3D Team.   He has been writing a series of posts on the Geoprocessing blog called “Lidar solutions in ArcGIS”.  These posts cover Lidar processing tasks and workflows, and will show how to manage these vast point collections and outline approaches for mining information from them.

Here is a list of topics Clayton plans to cover, with links to the seven posts already completed:

MIT Students Take Pictures “from Space” on $150 Budget

In Geography, Imagery on September 14, 2009 at 2:18 pm

ireport…from iReport.com…

“Two MIT students have successfully photographed the earth from space on a strikingly low budget of $148. Perhaps more significantly, they managed to accomplish this feat using components available off-the-shelf to the average layperson, opening the doors for a new generation of amateur space enthusiasts. The pair plan to launch again soon and hope that their achievements will inspire teachers and students to pursue similar endeavors.

“Justin Lee and Oliver Yeh have always dreamed of seeing the earth from space, but until recently, they believed that they had neither the budget nor the technical expertise to get a camera into the stratosphere.”

Measuring Water from the Sky: Satellites Track Consumption

In Environmental Science, Geography, Imagery on September 14, 2009 at 2:14 pm

…from the Washington Post…

“Water management is serious business in the American West, where precipitation is scarce, irrigated agriculture is a major industry, new housing subdivisions spread across arid landscapes and water rights are allocated in a complicated seniority system.  “If you can’t measure it, you can’t manage it,” water officials are fond of saying.  But measurement — trying to determine how much water is diverted from rivers and how much is pumped from hundreds of thousands of wells — has been an inexact and expensive science.”

Graduate Research Assistantship in Remote Sensing for Quantitative Ecosystem Studies at Michigan Technological University

In Education, Environmental Science, Imagery on September 10, 2009 at 11:28 am

michtech“A Ph.D. research assistantship in remote sensing for quantitative ecosystem studies is available in the School of Forest Resources and Environmental Science at Michigan Technological University. The position will focus on further developing emerging remote sensing technologies (e.g., LiDAR) for ecosystem assessment and inventory. The ideal candidate will be highly motivated, innovative, and posses a MS degree in Forest Science, Ecology, Biology, Geography or related field. Start date is negotiable; however, spring semester 2010 is ideal. The assistantship includes a full tuition wavier and a competitive stipend.

“The School of Forest Resources and Environmental Science is located in a 93,000-square-foot teaching and research facility, and has state-of-the-art computing equipment, including remote sensing/GIS teaching and research laboratories (http://forest.mtu.edu/). Michigan Tech is also home to the Earth, Planetary, and Space Sciences Institute (EPSSI), which is comprised of over twenty faculty focused upon promoting interdisciplinary research and education in various aspects of remote sensing (http://www.epssi.mtu.edu/). The University’s close proximity to vast expanses of Northern Hardwood Forest make it an ideal location to conduct research on remote sensing of forested ecosystems.

“Interested persons should e-mail GRE scores, a statement of professional interests, curriculum vitae including names and contact information for three references, a writing sample, and any other relevant materials to Dr. Michael Falkowski (mjfalkow@mtu.edu). Review of applications will begin on September 15th, 2009. Please consult the following web page for additional information regarding the graduate program and associated application procedures (http://forest.mtu.edu/gradstudies/prospective.htm).”

A Fast Clonal Selection Algorithm for Feature Selection in Hyperspectral Imagery

In GIScience, Imagery on September 9, 2009 at 6:26 am

geo-spatial…from Geo-spatial Information Science…

“Clonal selection feature selection algorithm (CSFS) based on clonal selection algorithm (CSA), a new computational intelligence approach, has been proposed to perform the task of dimensionality reduction in high-dimensional images, and has better performance than traditional feature selection algorithms with more computational costs. In this paper, a fast clonal selection feature selection algorithm (FCSFS) for hyperspectral imagery is proposed to improve the convergence rate by using Cauchy mutation instead of non-uniform mutation as the primary immune operator. Two experiments are performed to evaluate the performance of the proposed algorithm in comparison with CSFS using hyperspectral remote sensing imagery acquired by the pushbroom hyperspectral imager (PHI) and the airborne visible/infrared imaging spectrometer (AVIRIS), respectively. Experimental results demonstrate that the FCSFS converges faster than CSFS, hence providing an effective new option for dimensionality reduction of hyperspectral remote sensing imagery.”

GIS and Remote Sensing Help Maintain India’s Forests: Podcast Interview with Dr. Devendra Pandey

In ESRI, Environmental Science, GIS, Imagery, Interviews on September 4, 2009 at 12:30 pm

podcast_iconESRI Podcast: Dr. Devendra Pandey, director general of the Forest Survey of India and one of the keynote speakers at the 2008 ESRI Remote Sensing and GIS Summit, discusses the impact of remote sensing and GIS in managing India’s forests, including how the technology has been used to mitigate encroachment conflicts.

  • Listen or download: MP3 [14:14 | 6.55 MB]

Road Extraction from Satellite Images using a Fuzzy-Snake Model

In Geography, Imagery on September 3, 2009 at 7:09 am

caj…from The Cartographic Journal…

“This paper proposes a developed approach to extract roads from optical remotely sensed images. The approach is based on the following steps. First, a window with size of 5 × 5 pixels is moved over the image to calculate the features: mean (x1), standard deviation (x2), skewness (x3) and kurtosis (x4). Then, the roads are identified based on the converted features to the specific fuzzy sets of the linguistic variables. The used linguistic variables are Mean, Standard deviation, Skewness, Kurtosis and Grey-scale with trapezoid and triangle membership functions. Next, the skeleton of the identified roads is extracted using two structure elements from the mathematical morphology. Finally, a snake model is employed to extract the road vector form from the skeletons. The results of the accuracy evaluation demonstrate that the developed road extraction approach can provide both good visual and high positional accuracy. The approach is tested over the samples of SPOT-4 panchromatic images from areas in Iran.”

Satellites Used to Predict Infectious Disease Outbreaks

In Imagery, Science, Spatial Analysis on August 26, 2009 at 7:37 pm

…from Scientific American…

“From avian flu to cholera, infectious diseases may not be able to hide for long.  Some researchers have their sights trained on predicting their every move with detailed satellite data.”

Mapping Antarctica: Latest Satellite Imagery Brings Continent into High-Res Focus

In GIS, Geography, Imagery on August 26, 2009 at 10:12 am

antsun…from The Antarctic Sun…

“Maps of Antarctica date back to when Roman geographer and astronomer Ptolemy envisioned a land in the southern hemisphere to counterbalance that in the north to satisfy an ancient sense of proportion. Terra Australis would remain terra incognita for more than 1,500 years, though that didn’t stop cartographers from drawing fanciful depictions of the southern continent, varying widely in size and location.

“Today, the average person can zoom across Antarctica with Google Earth. It’s even possible to download high-definition images of ice and mountaintops thanks to an International Polar Year External U.S. government site project that created a map mosaic of the continent from more than 1,000 satellite images — the Landsat Image Mosaic of Antarctica (LIMA) External U.S. government site. [See previous story: Getting on the map.]

“But Paul Morin knows those images and the maps created from them can get even better, practically proselytizing about a new promised land of high-resolution imagery in which one can literally count the boulders on the ground.”

Third International Conference on Cartography & GIS: 15-20 June 2010, Nessebar, Bulgaria

In Conferences, GIS, Imagery, Visualization on August 26, 2009 at 9:40 am

icaConference topics include:

  • Early Warning and Crises Management
  • Planetary Cartography
  • Marine Cartography
  • Cartographic Visualization
  • Remote Sensing Technologies

Read the invitation

Research Positions Open for Work on Bio-Resource Ecology and Climate Change in the Sikkim, Himalayas

In Climate Change, Education, Environmental Science, GIS, Imagery, Social Science on August 21, 2009 at 9:43 am

ncsbSeveral long-term research positions are available as part of a Department of Biotechnology (DBT), Government of India, funded project on “Technological Innovations and Ecological Research for the Sustainable Use of Bioresources in Sikkim”. The project is jointly implemented by the National Centre for Biological Sciences (NCBS) (Tata Institute for Fundamental Research, http://www.ncbs.res.in), Bangalore, and the Ashoka Trust for Research in Ecology and the Environment (ATREE) (http://www.atree.org), Bangalore.

We seek qualified, highly motivated candidates for various research and technical positions at the Junior Research Fellow (JRF), Senior Research Fellow (SRF), Post-Doctoral Fellow levels, and in GIS/Remote Sensing.  The research positions can potentially lead to a PhD based at the two institutions. All salaries will be in accordance with DBT specified norms.

The areas of research encompass both basic and applied ecology and include the mapping and monitoring of faunal and floral biodiversity, field and laboratory measurements of biodiversity and ecosystem services (carbon, hydrology, pollination, bio-resources) and their response to climate change, and work on sustainable use of bio-resources by local communities.  Investigators on the project include Dr. Robert John (forest ecology), Dr. Jagdish Krishnaswamy (hydrology & landscape ecology), Dr. Soubadra Devy (pollination ecology) and Mr. Suman Rai (bioresource management) from ATREE, and Dr. Mahesh Sankaran (community ecology), Dr. Ajith Kumar (small-mammal ecology), Dr. Suhel Quader (behavioural and population ecology) and Dr. Uma Ramakrishnan (conservation genetics) from NCBS.

Candidates with backgrounds in life sciences, botany, zoology, geo-sciences, ecology, environmental science, social sciences and remote sensing/GIS and with demonstrated field experience and interest in working in Sikkim and the Northeastern India will be considered.  Depending on the position, laboratory work in Bangalore will be combined with field measurements and observations in Sikkim.  The GIS/RS position will be based in Bangalore. Short-listed candidates will be interviewed by project Scientists in Bangalore or Sikkim.

Interested candidates should send their CV and statement of interest by email to: sikkimdbt@ncbs.res.in.  Applications will be reviewed until suitable candidates are found.
With regards,
Dr. A. Kumaraguru,
Project Post-Doctoral Fellow, Dr. Shivaji Group, Uppal Road, CCMB – LaCONES, Hydrabad.

Managing Disasters with High-Tech Imaging could Save Lives

In GIS, Imagery on August 19, 2009 at 1:14 pm

rit…from PhysOrg.com…

“Improving disaster response is one of the goals of the Information Products Laboratory for Emergency Response, a partnership between Rochester Institute of Technology and the University at Buffalo. The collaboration will foster research to improve disaster mitigation planning, real-time response and recovery efforts, and to create potential business opportunities for industry.

“The incubator, funded with $600,000 from the National Science Foundation, will focus on technology, policy and business-development and bring together university researchers, private sector service and product providers, and emergency response decision makers.”

Geography Prof. Receives President’s Leadership Fund Award

In Climate Change, Education, Environmental Science, GIS, Geography, Imagery on August 18, 2009 at 2:18 pm

stow2“Department of Geography professor Douglas Stow, an internationally recognized leader in remote-sensing analysis of terrestrial environments, has been named one of the recipients of The President’s Leadership Fund Awards for Faculty and Staff Excellence.

“Stow says he’ll use his award to seed or augment projects. For example, he plans to process and analyze 10 years of satellite data from the North Slope of Alaska to assess whether snow is melting earlier and shrubs are expanding within Arctic tundra lands.”

Planet Action Grants: Submit your Project by September 30, 2009

In Climate Change, Environmental Science, GIS, Geography, Grants, Imagery on August 14, 2009 at 10:22 am

planetactionlogoPlanet Action provides satellite imagery, geographic information and technology support to local projects that investigate and assess climate change issues focusing on human issues, drought & desertification, water resources, forestry, biodiversity, oceans, ice, and awareness.

This year, Planet Action will support additional projects while following up on current projects and their results on the ground.

Submit your project by September 30, 2009.

Eligibility and Selection Criteria

Planet Action supports projects involved at least in one of the following domains:

  • Awareness
  • Biodiversity & Conservation
  • Drought & Desertification
  • Human Issues
  • Forest & Deforestation
  • Ice & Snow
  • Oceans & Coastlines
  • Water Resources

To be eligible for support from Planet Action, projects must:

  • Deal with a climate change related issue and propose a course of actions.
  • Deal with at least one of the Planet Action “domains”.
  • Have a member of the organization who resides in the country where the project takes place or at least during the duration of the projects
  • Be proposed by a non-profit organization such as NGO’s, a public laboratory or a university.
  • Confirm that the project has no commercial, religious or ideological content or objective.

More information

Using GIS and Satellites to Study Lyme Disease

In Education, GIS, Imagery, Science on August 14, 2009 at 7:47 am

uab-logoSix University of Alabama at Birmingham (UAB) students and two students from other universities are using satellite imagery to identify possible habitats in Alabama for the black-legged tick that carries and transmits Lyme disease.

The students are interns with the NASA-Marshall Space Flight Center DEVELOP Program. DEVELOP is a competitive internship in which students work with NASA and partner-agency scientists to carry out innovative research projects.

GeoTech 2009 Conference: October 5–6, Silver Spring, Maryland USA

In Conferences, GIS, GIScience, Imagery, Science on August 14, 2009 at 7:46 am

prThe Potomac Region of the American Society for Photogrammetry and Remote Sensing is pleased to announce the 16th annual GeoTech: The Premiere Mid-Atlantic Imagery and Geospatial Conference, exploring “Geospatial Infrastructure: Looking to the Future” on October 5-6, 2009.  The two-day event features a day of Workshops led by experts and a day of Technical Sessions.  Co-hosted by the National Geodetic Survey (NGS) of the National Oceanic and Atmospheric Administration (NOAA), GeoTech 2009 will be held at NOAA’s Auditorium and Science Center in Silver Spring, MD.

The GeoTech 2009 Conference will provide workshops covering Terrain Mapping, Fundamentals of Automated Feature Extraction (AFE), Accessing and Processing Public Domain Landsat Data, and An Overview of Airborne and Terrestrial Data Sources for Disaster Response.  The Technical Program will include sessions on Coastal Mapping Applications, Sensors and Systems, and Spotlight on Emerging Issues.

Mr. Ernie Reith, Deputy Director of the National Geospatial-Intelligence Agency’s (NGA) InnoVision Directorate, will give the Keynote address.

Continuing Education Credits will be offered for those professionals requiring recertification.

Representatives from the Geospatial industry will be on-hand to exhibit their latest tools and offerings.

Details, registration, and contact info are available at: http://www.asprspotomac.org/geotech09/.  On-line registration ends Noon EST 2nd October 2009.

ArcGIS Integration with ENVI Geospatial Imagery Processing and Analysis Software

In ESRI, GIS, Imagery, Video on August 14, 2009 at 7:45 am

This video shows functionality in the ENVI software environment specifically designed for ArcGIS users, and features step-by-step workflows to walk users through the processes of feature extraction, change detection, classification, and orthorectification.

Latest Archaeological Digs May Revamp Qatar’s Entire History

In GIS, Imagery, Science, Social Science on August 13, 2009 at 7:28 am

“Recent excavations conducted in Qatar has resulted in a substantial number of new sites being discovered and significantly more archaeological research in the region, which may revamp the whole history of the nation written so far.

“According to a report in The Peninsula On-line, there has been a notable increase in the amount of archaeological field work being conducted in Qatar covering the ancient to the Islamic periods.

“The research is bringing important new information to light.

“In October last year, Qatar had become the first country in the region to implement the Global Imagery System for archeological studies as part of a research by QMA and the University of Birmingham, United Kingdom.

“This research involved the use of remote sensors and geospatial modelling to reconstruct the former onshore and offshore landscape environments in Qatar.”

New Imagery Enhancements in ArcGIS 9.4

In Conferences, ESRI, GIS, Imagery, Video on August 13, 2009 at 7:28 am

This video demonstrates new imagery enhancements that will be available in ArcGIS 9.4.

Visualization of Thermal Pollution from a Nuclear Plant

In Environmental Science, Imagery, Video, Visualization on August 12, 2009 at 8:34 am

This video animates a series of thermal infrared LANDSAT images that visualize what a year of thermal pollution from Oyster Creek Nuclear Generating Station looks like. The pink represents temperatures above ambient levels. The imagery was provided by the Center for Remote Sensing and Spatial Analysis at Rutgers University, and was produced by the Environmental Health Clinic.

Collecting LiDAR Data for Rainwater Basin Project on the Platte River

In Environmental Science, GIS, Imagery on August 11, 2009 at 9:02 pm

Merrick & Company, working for Optimal Geomatics under a contract with the U.S. Army Corps of Engineers, is collecting light detection and ranging (LiDAR) data over a 17,677-square-mile area in order to create a digital elevation model.  The digital elevation model will be used in natural resources,  agricultural planning and management, and to update the flood maps in the area.  More specifically, it will serve as part of the wetland restoration index, a tool that is being used to prioritize habitat protection and restoration activities to achieve the greatest wetland biological return for the habitat investment dollar and for stream restoration on the Platte River as part of the Platte River Recovery Implementation Program.  The project area covers almost all of south central Nebraska and four counties in north central Kansas.

Imagery: A Core Component of GIS

In ESRI, GIS, Imagery on August 11, 2009 at 9:48 am

ESRI has long supported use, exploitation, and analysis of imagery across our product line. Several years ago we launched ArcGIS Image Server, a product which allowed our users to manage and disseminate vast quantities of imagery very quickly and easily. This technology has continued to mature, and last year became an extension to ArcGIS Server. At the same time, image services, which optimize the delivery of imagery over the Web, were built into the core ArcGIS Server product.

At ArcGIS 9.4, we are continuing to further integrate image services and at the same time improve the performance and capabilities of all our products with regards to imagery. Our desktop product will include basic image analysis with focused imagery tools, and very fast image display capabilities. This will allow intuitive and high performance capabilities for navigating imagery integrated with map displays inside of ArcMap. We are improving our image data modeling, management, and visualization, and adding dynamic analytic tools. We have done this in a way that supports the typical workflows associated with geospatial imagery.

With the additional imagery capabilities in ArcGIS 9.4, ESRI is making imagery a fundamental component of ArcGIS.  ESRI’s strategy for providing you with increased imagery support includes highly-scalable image data management, new desktop image display and analysis tools, and leveraging the strengths of key technology partners.

Highly-Scalable Image Data Management

At 9.4 we’ve created a new type of raster catalog called a mosaic. Mosaic lives in the geodatabase for working with large image catalogs. Mosaic allows you to keep your imagery in its native format and then dynamically access your original source imagery with on-the-fly orthorectification, mosaicking, and pan sharpening. This dynamic approach to image data management, which underpins our entire image strategy, creates a foundation upon which you can build a highly-scalable solution and which greatly reduces the latency or the time required between initial imagery acquisition and its operational use.

New Desktop Image Display and Analysis Tools

At 9.4, ArcGIS Desktop becomes an image analyst workstation, and includes a very powerful new image display capability featuring a real-time roam, zoom, and rotation across imagery of virtually any size, any resolution, and any location.  9.4 also includes a new image analysis window which contains a number of new image enhancement and analysis tools that you’ve asked us for. These tools are all very easy to use, they’re all in one place, and they operate in real time. You can perform image processing tasks, such as vegetation analysis, with a single click of a button.

Leveraging the Strengths of Key Technology Partners

We are also working to further extend the ArcGIS desktop, geodatabase and server platforms with technology from our imagery partners. We are very fortunate to have a large number of technology partners in the imagery world. Working with them allows you to unlock the powerful information contained in your imagery. One such partner is ITT Visual Information Solutions and their ENVI software suite. ENVI combines the latest spectral image processing and image analysis technology with an intuitive, user-friendly interface.  The new ENVI EX product—unveiled at the 2009 ESRI International user Conference, and tightly integrated with ArcGIS—delivers the accurate, scientifically proven processes that ENVI is known for in revolutionary step-by-step workflows that quickly and easily guide GIS users through advanced image processing tasks.

Highly-scalable image data management, desktop image analysis tools, and close ties with key partners will provide you with a complete imagery platform that brings imagery full circle as a core component of ArcGIS.

ESRI Lauds Dr. Krishnaswamy Kasturirangan for Making a Difference

In Conferences, ESRI, GIS, Imagery, Science on July 28, 2009 at 3:31 pm

Award Goes to Astrophysicist for Launching Remote-Sensing and Geographic Information System Technology in India and Beyond

Many people in India know Dr. Krishnaswamy Kasturirangan as an esteemed space scientist who spearheaded the development and use of the Indian Remote Sensing (IRS) satellites. Others know him as a Member of Parliament.

But few may realize his contributions in bringing agencies the technology needed to help estimate crop yields in the world’s most populous nation, identify new groundwater sources, monitor and manage forests, and plan where to build housing developments and roads. These represent only a handful of the many applications for the mapping and analysis conducted in India and several other countries using satellite imagery and geographic information system (GIS) software, an integration of technologies that Kasturirangan championed. Kasturirangan believes the technologies must bring value and benefit to society and individuals.

For these achievements, the former chairman of the Indian Space Research Organization (ISRO) received a Making a Difference Award at the 2009 ESRI International User Conference, held July 13–17 at the San Diego Convention Center in California.

“He makes an enormous difference because of the integration of remote sensing into GIS and also the tremendous focus he has created on applications,” ESRI president Jack Dangermond said, presenting the award.

Kasturirangan spent many years working in the space program, serving as project director for his nation’s first two experimental earth observation satellites, Bhaskara I and II. He also headed ISRO’s Satellite Center, where he supervised the development of the Indian National Satellite (INSAT-2) and four of India’s civilian IRS satellites.

Kasturirangan later became chairman of the ISRO and the country’s Space Commission, a position he held for nine years. He was then named a Member of Parliament, serving until early July 2009, when Indian Prime Minister Dr. Manmohan Singh appointed him to India’s Planning Commission. As a member of the commission, he will oversee planning and program development in science and technology. He will work with agencies that use satellite imagery and GIS data and applications.

“Dr. Krishnaswamy Kasturirangan is going to be a master of bringing geography to virtually everywhere in India and will be an example for all of us. Thank you,” Dangermond said as he handed him the award.

In an interview after the ceremony, Kasturirangan said he accepted the Making a Difference Award on behalf of the dedicated team at the ISRO, the GIS and remote-sensing technology agencies and users throughout India, and government and other leaders who, as far back as the 1980s, could see how the combination of GIS and remote sensing could benefit Indian society.

“They had tremendous foresight into what imagery and GIS could do for the country in the context of development,” he said.

To watch a video of Kasturirangan receiving the Making a Difference Award, visit www.esri.com/uc.

2009 ESRI User Conference Proceedings Now Online

In Climate Change, Conferences, ESRI, Education, Environmental Science, GIS, GIScience, Geography, Imagery, Modeling, Science, Social Science, Spatial Analysis, Statistics, Temporal Analysis on July 24, 2009 at 6:49 pm

Scientific Value of Arctic Sea Ice Imagery Derived Products

In Climate Change, Environmental Science, Imagery, Science on July 23, 2009 at 7:52 am

0309137632A new report authored by Committee on the Scientific Value of Arctic Sea Ice Imagery Derived Products; Committee on Climate, Energy, and National Security; National Research Council.

“During the 1990s, a government program brought together environmental scientists and members of the intelligence community to consider how classified assets and data could be applied to further the understanding of environmental change. As part of the Medea program, collection of overhead classified imagery of sea ice at four sites around the Arctic basin was initiated in 1999, and two additional sites were added in 2005. Collection of images during the summer months at these six locations has continued until the present day. Several hundred unclassified images with a nominal resolution of 1 meter have been derived from the classified images collected at the 6 Arctic sites.

“To assist in the process of making the unclassified derived imagery more widely useful, the National Research Council reviewed the derived images and considered their potential uses for scientific research. In this book, we explore the importance of sea ice in the Arctic and illustrate the types of information–often unique in its detail–that the derived images could contribute to the scientific discussion.”

ITT VIS Announces ENVI EX

In ESRI, GIS, Imagery on July 14, 2009 at 7:13 am

enviex_screenshot1“Satellite and airborne imagery, once considered a simple backdrop to maps, is now readily available, more affordable, and a great source of valuable data to add to your GIS applications. Imagery enables and enhances operational decision making. The challenge to unlocking the information in imagery and its associated data has been to make image processing and analysis easier and less time consuming, while still delivering accurate results.

“Now, there is a solution to easily add information from imagery to your GIS – ENVI EX.”

Spatial Analysis of Urban Tree Canopy for Brunswick, Maryland

In Environmental Science, Imagery, Science, Spatial Analysis on July 8, 2009 at 6:48 am

uvm…from The Frederick News-Post…

“Tree canopy cover in Brunswick is good compared to Frederick , and even when compared with the cities of Baltimore and Washington.

“It stands at 38 percent, according to a recent study by the University of Vermont. That means 38 percent of land area in Brunswick has shade provided by trees, known as urban tree canopy.

“The University of Vermont conducted the study using satellite imagery taken in 2007, combined with LiDAR, which is similar to radar. DNR commissioned the imagery for the entire state. UVM’s Spatial Analysis Laboratory does the analysis in consultation with the U.S. Forest Service Northern Research Station.”

Science Projects to Receive Free Satellite Imagery

In Climate Change, Environmental Science, Imagery, Science on July 2, 2009 at 1:04 pm

glglaciercropDMCii announced the selection of five science projects that will receive free satellite imagery from the DMC satellite constellation.

Greenland GlacierIn December 2008, scientists were invited to compete for the opportunity to use the DMC multi-spectral satellite image data in their research projects.

Applications were judged on their contribution to international environmental research by a panel of scientists chaired by Professor Alan O’Neill, Director of the UK’s National Centre for Earth Observation (NCEO) the panel included Dr Arwyn Davies, Head of Earth Observation at the British National Space Centre (BSNC), Dr Paul Aplin (Chairman of RSPSoc and Associate Professor Nottingham University), Dr Steve Mackin, Chief Scientist DMCii and David Hodgson, Managing Director DMCii.

The winning projects cover a wide range of important topics: from monitoring changes in the Greenland Ice Sheet and the UK wetlands and forests, to pioneering new techniques for integrating satellite Earth observations with computer models to improve measurements of how the Earth’s vegetation ‘breathes’ carbon dioxide. Congratulations to the following winning science teams:

  • Monitoring Dynamic Change in the Greenland Ice Sheet
    A. Luckman (Swansea University)
  • Testing Data Assimilation Schemes
    JJ Settle (University of Reading), P North (University of Swansea), T Quaife (University College London)
  • Assessing Seasonal Water and Restoration Status of Wetland Habitats
    Dr G Smith (Specto Natura Ltd), Dr F Hughes & Dr P Stroh (Anglia Ruskin University), Dr P Aplin (University of Nottingham)
  • Validation of MODIS NPP (Net Primary Productivity) Product for Tropical Areas
    Dr M Cutler (University of Dundee), Prof A Cracknell, Assoc Prof AL Ibrahim, Dr K Haron
  • Monitoring of Vegetation Phenological Change and Health
    Dr R Guisa (University of Surrey), Dr R Pitman (Centre for Forestry & Climate Change (FR))

Drought Tool Expands to 48 States

In Climate Change, Environmental Science, GIScience, Imagery, Science on June 19, 2009 at 7:02 am

VegDRIA seven-year research effort achieved a milestone last month when the Vegetation Drought Response Index expanded across the 48 states of the continental United States. VegDRI maps, produced every two weeks, combine satellite-based observations of vegetation conditions with climate and biosphysical information to map drought’s effect on vegetation at a one-kilometer resolution.

“VegDRI provides a regional overview of how rangeland and crops are doing,” said Brian Wardlow, the GIScience program area leader at the National Drought Mitigation Center, which is headquartered at the University of Nebraska-Lincoln. “For anyone monitoring agricultural conditions, particularly ranching, or with interests in natural resource management, this is an invaluable addition to their tool set.”

Read more

GeoENV 2010 to be held in Gent, Belgium 13-15 September 2010

In Conferences, Environmental Science, GIS, Imagery, Modeling, Science, Statistics on June 18, 2009 at 7:18 am

geoen_2010_kleurGeoENV 2010, the 8th International Conference on Geostatistics for Environmental Applications will be held in Gent, Belgium, on the 13th – 15th September 2010. GeoENV conferences have been held biennially at venues across Europe. From the first conference in Lisbon in 1996, the event has been staged in Valencia (1998), Avignon (2000), Barcelona (2002), Neuchâtel (2004), Rhodes (2006), Southampton (2008) and has become established as a leading forum for Scientists across a broad range of disciplines to share their experiences on the application of geostatistics to environmental problems.

Topics to be covered include:

  • Geostatistical methodology, new evolutions
  • Spatial statistics
  • Multiple point geostatistics
  • Spatio-temporal statistics
  • Ecology, natural resources
  • Hydrology, ground water modelling
  • Soil inventory, mapping
  • Health, epidemiology, ecotoxicology
  • Environmental pollution and risk assessment
  • Forestry, agriculture
  • Remote & proximal sensing

An extended abstract of 2-3 pages (incl. tables, figures, references, etc.) should be submitted by 1 March 2010 via e-mail to the symposium secretary: geoenv10@ugent.be. In this email it should be indicated if you prefer an oral or poster presentation. The organizing committee will decide about the possibilities for an oral presentation. The abstracts should be sufficiently clear to facilitate selection by the Organizing Committee. The organizers will inform you before 1 May 2010 about the acceptance of the paper for the symposium. If accepted, it will be distributed at the conference in a book of abstracts with ISBN.

Indian Space Research Organisation Implements ESRI Software for Image Processing

In ESRI, Environmental Science, GIS, Imagery, Science on May 6, 2009 at 6:47 am

isroArcGIS Server and Its Image Extension Will Be Used throughout the Indian Government to Integrate Data with New-Generation Images

The Indian Space Research Organisation (ISRO) has reached an agreement with NIIT GIS Limited (ESRI India), ESRI’s distributor in India, to equip its five Regional Remote Sensing Service Centres (RRSSCs) with ArcGIS Server and the Image extension. The centers in Jodhpur, Dehradun, Kharagpur, Nagpur, and Bangalore use Indian Remote Sensing (IRS) satellite and other imagery to create thematic maps and geographic information system (GIS) databases that provide valuable societal applications to various government agencies throughout India.

With India’s success in remote-sensing technology through the IRS constellation, several new imagery-based and GIS-centric projects of national relevance are gaining visibility and importance. ISRO is presently implementing major programs related to natural resources, disaster management, environmental oversight, and groundwater and watershed management.

The remote-sensing centers are establishing a distributed architecture of server-based solutions designed to be the foundation for publishing, hosting, and serving images and data. Over time, the RRSSCs have collected large volumes of map data and integrated them with attribute data. The centers plan to combine and assimilate all the data with new-generation IRS high-resolution images and serve the data and application sets across the government sector.

The RRSSCs needed a GIS solution that met their needs and was scalable to meet growing demands for services from a large number of users for a variety of advanced applications. The centers selected ESRI’s proven technology and superior solutions after several rounds of technical presentations, demonstrations, and discussions. The RRSSCs and ESRI India have concluded a comprehensive training session, and RRSSC users have started developing the solution.

Dr. Yvn Krishnamurthy, director of the RRSSCs, says, “ISRO users have been using ESRI products for a variety of applications, and many national programs have been based on GIS solutions. IRS imagery has been the source of thematic mapping inputs and provides end-to-end solutions under the umbrella of the National Natural Resources Management System. ArcGIS Server with the ArcGIS Server Image extension is a robust and integrated product and has capabilities that can meet our application needs of serving images and thematic maps to a variety of users. Our technical team is geared up to use these capabilities and develop solutions that will be unique and beneficial. We look forward to close support from ESRI in this endeavour.”

Dr. Mukund Rao, president and chief operating officer at ESRI India, notes, “ISRO has been pioneering the use of IRS imagery and advancing GIS solutions for a long time. We are proud to be associated with [the organization] on this prestigious, first-of-its kind national project to serve image and map-based solutions in a GIS portal architecture. We value our relationship with ISRO and are committed in our support.”

ArcGIS Server helps users connect people with the information they need via Web mapping applications and GIS services. It is built on a modern, service-oriented architecture. The ArcGIS Server Image extension makes it possible to take raw or pre-processed imagery and immediately deliver it as a Web service. It enables organizations to exploit the rich information content available in imagery and quickly access large volumes of imagery. This is far superior to traditional options that required significant effort by users to locate and make file-based imagery available.

Organizations are moving to newer technology platforms because of their need to leverage imagery throughout their entire enterprise and the new capabilities available for working with imagery. “We provide some really remarkable and powerful new tools that enable things to happen in near-real time–things like delivering and displaying imagery, roaming around the imagery, zooming in to the imagery, and doing on-the-fly mosaicking and orthorectification of the imagery,” says Lawrie Jordan, ESRI’s director of imagery enterprise solutions. “Customers like this because they are seeing immediate benefits in terms of performance and the quality of their results.”

ESRI India envisions that this new software deployment and implementation will serve as a key reference within all Indian government agencies, especially those that disseminate and/or consume imagery and imagery-related data.

Lidar Solutions in ArcGIS

In ESRI, GIS, Imagery, Science on May 1, 2009 at 10:27 am

pointfileinfomapcolorrampspacingClayton Crawford, Product Engineer in ESRI’s Software Products Group’s 3D Team.   He has been writing a series of posts on the Geoprocessing blog called “Lidar solutions in ArcGIS”.  These posts cover Lidar processing tasks and workflows, and will show how to manage these vast point collections and outline approaches for mining information from them.

Here is a list of topics Clayton plans to cover, with links to the four posts already completed:

Planet Action Panel Discussions Scheduled for 2009 ESRI International User Conference

In Climate Change, Conferences, ESRI, Environmental Science, GIS, Imagery, Science on May 1, 2009 at 8:06 am

planetactionlogoPlanet Action is a non-for-profit collaborative initiative launched in June 2007 to encourage the Earth observation and geographic information professionals to help address climate change-related issues. Planet Action was launched by Spot Image, and partners include ESRI, UNESCO, CNES, CRISP, DEFINIENS, DigitalGlobe, ITT, and NSPO.

Planet Action will be holding two panel discussions at the ESRI International User Conference in San Diego, California on Thursday, 16 July 2009.

Session I: 1:30 p.m. to 2:45 p.m.
Session II: 3:15 p.m. to 4:30 p.m.

Location: Room 32 A

With more than 30 ground station partners, Planet Action is truly an international effort. Come hear from a selection of our 85 grantees from around the world about their on-the-ground projects and how they have made use of their spatial technology grants from Planet Action.

  • Mario Hernandez, UNESCO
  • Peter Ndunda, Green Belt Movement
  • Aurelie Shapiro, WWF
  • Andrew Scanlon, Eco-Institute
  • Rosanna Rivero, Everglades Foundation
  • Pierre Duquesne, Brazil Spot Image
  • Dr. James Sheppard, Center for Reproduction of Endangered Species (CRES)
  • Nancy Briggs, Orangutan Foundation International
  • Birute Galdikas, Orangutan Foundation International
  • Leslie Bolick, Orangutan Foundation International

ESRI UC web site

Planet Action Day: 09 June 2009

In Climate Change, Conferences, ESRI, Environmental Science, GIS, Imagery on May 1, 2009 at 7:51 am

r1956_3_logo_paday_170This year Planet Action is celebrating its second anniversary and will be holding the first Planet Action Day conference in Toulouse, France.  We look forward to welcoming all our partners, experts, project leaders, and more.  An exhibition space will showcase projects supported by Planet Action (posters and demos), as well as partners having contributed to the projects.  The evening session will be open to a broader public.

Environmental Modelling with GIS and Remote Sensing (Geographic Information Systems Workshop)

In Books, Environmental Science, GIS, Imagery, Modeling, Science on April 23, 2009 at 7:09 am

env_mod_wkshp“This book derives from a training course run by ITC for professionals and managers in the environmental sciences, detailing the applications of remote sensing and GIS for environmental monitoring, modelling and assessment. It sets out current research results and provides operational methods for environmental mapping and monitoring.”

Nicole Wayant Announced as 2009 Winner of the ASPRS Abraham Anson Memorial Scholarship

In Education, GIS, Imagery, Science on April 7, 2009 at 10:11 am

Nicole Wayant is the first winner of the Abraham Anson Memorial Scholarship. This scholarship was established in 2008. The purpose of the award is to encourage undergraduate students currently enrolled or intending to enroll in a U.S. college or university who have an exceptional interest in pursuing scientific research or education in geospatial science or technology related to photogrammetry, remote sensing, surveying and mapping to enter a professional field where they can use the knowledge of this discipline to excel in their profession. This annual scholarship will consist of a certificate and a check in the amount of $1,000 and a one-year student membership (new or renewal) in the American Society for Photogrammetry and Remote Sensing (ASPRS).

Wayant is a senior at Kansas State University (KSU), studying for her BS in Geography and her BS in Mathematics. She has received several academic honors and awards for her scholastic achievements. She has also worked on several research projects at the university, notably, on a project entitled “Spatial-temporal Analysis of Malaria in Paraguay: Correlating Malaria and Normalized Difference Vegetation Index.” She expects to graduate in May 2009 and intend to pursue further studies in a graduate program in remote sensing.

For over six decades, Lt. Col. Abraham Anson, affectionately known as Abe, devoted a considerable period of his life to the cause of the Society in various forums and forms, as an author of many articles, Associate Editor of the Manual of Color Aerial Photography and the first edition of the Manual of Remote Sensing, and the editor of the Proceedings of the Aerial Photography Workshop for the Plant Sciences. He served on the Society and the Potomac Region Boards and numerous committees. After his retirement, Anson assumed the task of compiling the history of the ASPRS and the Potomac Region from its founding days, working countless hours with great dedication for several years.

ASPRS Announces Sergio Bernardes as 2009 Colwell Fellowship Winner

In Climate Change, Environmental Science, GIS, Imagery, Modeling, Science on April 7, 2009 at 10:07 am

The Robert N. Colwell Memorial Fellowship for 2009 was awarded to Sergio Bernardes.  He is a doctoral candidate at the University of Georgia (UGA) where he expects to earn a PhD in Geography in 2010.

This award was presented by the American Society for Photogrammetry and Remote Sensing (ASPRS) through the ASPRS Foundation from funds donated by students, associates, colleagues and friends of Robert N. Colwell. The award consists of a grant in the amount of $5,000, a certificate, and a one-year student or associate membership (new or renewal) in ASPRS. The presentation of the award took place at the ASPRS 2009 Annual Conference held in Baltimore, Maryland in March.

The Colwell award was established in 2006 to encourage and commend college/university graduate students or post-doctoral researchers who display exceptional interest, desire, ability and aptitude in the field of remote sensing or other related geospatial information technologies, and who have a special interest in developing practical uses of these technologies.

Bernardes’ research involves multi-temporal and multi-sensor analyses of biophysical parameters of vegetation in the Brazilian Amazon forest and savanna transition areas. His research on modeling of carbon sources and sinks, understanding human impacts on Brazilian Amazon forests and savanna, and advancing remote sensing image processing techniques will provide an important contribution to global change monitoring and modeling. Bernardes’ research program is consistent with the emphasis on practical applications of remote sensing to natural resources that characterized the career of Dr. Colwell, in whose memory this Fellowship is awarded.

Bernardes earned a BS degree in Agricultural Engineering from Vicossa Federal University, Brazil in 1991 and an MS degree in Remote Sensing from the Brazilian National Institute for Space Research in 1996.  He held a highly competitive university-wide Graduate School Award for two years at the UGA and received the ASPRS GeoEye Award and other UGA graduate awards in 2008.

Complete Interview with Lawrie Jordan Now Available

In ESRI, GIS, Imagery, Interviews on March 24, 2009 at 7:01 am

Back in January, I posted a preview of an interview with Lawrie Jordan, ESRI’s new director of imagery.  The complete interview was recently printed in the Spring 2009 issue of ArcNews, and you can also read it online:

Free Time Series Satellite Images for Busy People

In Climate Change, Earth Systems Engineering, Earth Systems Management, Earth Systems Science, Environmental Science, Geography, Imagery, Science on March 2, 2009 at 12:38 pm

TerraLook, a joint project between NASA and the US Geological Survey, provides free georeferenced images for multiple dates in a common JPEG format, and bundles them with free, open source desktop software.

Preview: Interview with Lawrie Jordan, ESRI’s New Director of Imagery

In ESRI, GIS, Imagery, Interviews on January 30, 2009 at 7:19 am

Renee Brandt, ESRI’s product marketing specialist for imagery, recently interviewed Lawrie Jordan, ESRI’s new director of imagery enterprise solutions. The interview will be published in the Spring 2009 issue of ArcNews, which will be mailed and posted online in a month or two. In the meantime, I wanted to share some excerpts from the interview.gi_ljordan1_jpg

Lawrie Jordan has more than three decades of experience working in imagery and has served on several defense science advisory panels to the U.S. Secretary of Defense, provided numerous testimonies to the U.S. Senate and House of Representatives, and served as an adviser to the National Aeronautics and Space Administration (NASA).

What strengths do you bring to ESRI’s imagery team?

First of all, I bring a passion for imagery with me. I never met an image I didn’t like and I’ll admit it, I’m just thrilled that I have the opportunity to be here at ESRI. Jack Dangermond has personally asked me to be an imagery evangelist in the company, which I am really excited about. I’ll be working on a comprehensive strategic plan for ESRI and imagery, the path going forward, and focusing on how imagery can help shape the future and most importantly create success stories for our customers. Some of the strengths I bring to the ESRI imagery team are the knowledge and experience gained from more than 30 years working as a leader in the field of image processing and remote sensing, including a long-standing strategic partnership with ESRI.

Is this focus on imagery taking ESRI in a new direction?

I would not call it a new direction. Imagery is essential to what we do, and it has been, actually, for a long time. We believe that imagery is core to GIS, and customers tell us that they want more integration of their imagery with the GIS, and we agree wholeheartedly. The whole focus of our offerings has imagery as a central component of what we do. We’ve had many great imagery capabilities in our products over the past years, which people have appreciated. Historically, it’s been through partners but now, it’s moving to the core of what we do.

The thing to remember is that imagery is a core source of information to create a GIS. Many times, particularly in natural disasters and things of this nature, things happen suddenly. Traditional GIS databases are instantly out of date, but the most appropriate, the most accurate, and most timely information to update that is near real-time or live imagery, which we can now collect and support. The exciting thing is commercial imagery providers, all of them are our strategic partners, are providing tremendously high-quality imagery now that we didn’t have even a few years ago. So we’re having much higher volumes of imagery, much higher quality of imagery, and much better tools now, so I think you’ll see less of a separation between “imagery” customers and “GIS” customers. In fact, what we see is that a GIS is incomplete without imagery. It is core to what we do. It’s no longer a separate industry; it’s actually an integral part of a GIS. Imagery gains its full benefit by being in a GIS. Imagery and GIS inform each other, and having imagery integrated into the geodatabase and populated throughout the architecture of the enterprise is the direction that we’re going.