Spatial Distribution and Risk Factors of Influenza in Jiangsu Province, China, based on Geographical Information System

ghGeospatial Health, Volume 8, Number 2, May 2014, Pages 429-435

By Jia-Cheng Zhang, Wen-Dong Liu, Qi Liang, Jian-Li Hu, Jessie Norris, Ying Wu, Chang-Jun Bao, Fen-Yang Tang, Peng Huang, Yang Zhao, Rong-Bin Yu, Ming-Hao Zhou, Hong-Bing Shen, Feng Chen, and Zhi-Hang Peng

“Influenza poses a constant, heavy burden on society. Recent research has focused on ecological factors associated with influenza incidence and has also studied influenza with respect to its geographic spread at different scales. This research explores the temporal and spatial parameters of influenza and identifies factors influencing its transmission.

Spatial clusters of annual incidence of influenza (hotspots) in Jiangsu province, P.R. China, for the years 2004 (a), 2 006 (b), 2009 (c) and 2011 (d).

Spatial clusters of annual incidence of influenza (hotspots) in Jiangsu province, P.R. China, for the years 2004 (a), 2006 (b), 2009 (c) and 2011 (d).

“A spatial autocorrelation analysis, a spatial-temporal cluster analysis and a spatial regression analysis of influenza rates, carried out in Jiangsu province from 2004 to 2011, found that influenza rates to be spatially dependent in 2004, 2005, 2006 and 2008. South-western districts consistently revealed hotspots of high-incidence influenza. The regression analysis indicates that railways, rivers and lakes are important predictive environmental variables for influenza risk. A better understanding of the epidemic pattern and ecological factors associated with pandemic influenza should benefit public health officials with respect to prevention and controlling measures during future epidemics. ”

Machine Learning Approaches to Coastal Water Quality Monitoring using GOCI Satellite Data

GISRSGIScience & Remote Sensing, Volume 51, Issue 2, 2014 — Special Issue: Coastal Remote Sensing

By Yong Hoon Kim, Jungho Im, Ho Kyung Ha, Jong-Kuk Choi, and Sunghyun Ha

“Since coastal waters are one of the most vulnerable marine systems to environmental pollution, it is very important to operationally monitor coastal water quality. This study attempts to estimate two major water quality indicators, chlorophyll-a (chl-a) and suspended particulate matter (SPM) concentrations, in coastal environments on the west coast of South Korea using Geostationary Ocean Color Imager (GOCI) satellite data. Three machine learning approaches including random forest, Cubist, and support vector regression (SVR) were evaluated for coastal water quality estimation. In situ measurements (63 samples) collected during four days in 2011 and 2012 were used as reference data. Due to the limited number of samples, leave-one-out cross validation (CV) was used to assess the performance of the water quality estimation models. Results show that SVR outperformed the other two machine learning approaches, yielding calibration R2 of 0.91 and CV root-mean-squared-error (RMSE) of 1.74 mg/m3 (40.7%) for chl-a, and calibration R2 of 0.98 and CV RMSE of 11.42 g/m3 (63.1%) for SPM when using GOCI-derived radiance data. Relative importance of the predictor variables was examined. When GOCI-derived radiance data were used, the ratio of band 2 to band 4 and bands 6 and 5 were the most influential input variables in predicting chl-a and SPM concentrations, respectively. Hourly available GOCI images were useful to discuss spatiotemporal distributions of the water quality parameters with tidal phases in the west coast of Korea.”

A Combined Biophysical and Economic GIS Framework to Assess Sugarcane Cropping Potential in Brazil

Transactions in GISTransactions in GIS, Volume 18, Issue 3, pages 449–463, June 2014

By Letícia de Barros Viana Hissa and Britaldo Silveira Soares Filho

“Recently, the increasing demand for biofuels triggered a new phase for the sugar-alcohol sector. In Brazil, as well as in other tropical countries, this process raised worries regarding the possible direct and indirect effects of the crop’s expansion on the conversion of native vegetation coverings. Therefore, the modeling of spatial-economic surfaces, representing the potential rent variation in its spatial component, for economic activities, may be a useful tool in the decision-making process. Hence, here we propose and present the results of a combined framework composed of two modules using the modeling platform Dinamica EGO.

Sugarcane crops estimated rentability for the harvest year 2005–2006 according to real (S1) and maximum (S2) rentability scenarios.

Sugarcane crops estimated rentability for the harvest year 2005–2006 according to real (S1) and maximum (S2) rentability scenarios.

“The first module simulates sugarcane’s growth, calculating the daily response of the crop to environmental conditions during the stages of the plant’s development. The second module estimates rents for sugarcane cultivation in Brazil, identifying areas where this activity would bring higher economic return, looking at simulated productivity, production costs and selling prices in a way that is spatially explicit for Brazil. Two different scenarios for production costs were tested, and results ranged from negative values to maxima of R$/ha 929 and R$/ha 1176 for standard and efficient costs of production, respectively. The model successfully indicated non-profitable and profitable areas, and regions where high expected economic return overlaps endangered ecosystems.”

Integrating the Huff Model and Floating Catchment Area Methods to Analyze Spatial Access to Healthcare Services

Transactions in GISTransactions in GIS, Volume 18, Issue 3, pages 436–448, June 2014

By Jun Luo

“Analysis of spatial access to healthcare services is critical for effective health resource planning. Gravity-based spatial access models have been widely used to estimate spatial access to healthcare services. Among them, the floating catchment area (FCA) methods have been proved to be informative and helpful to the designation of Health Professional Shortage Areas (HPSAs). This article integrates the Huff Model with the FCA method to articulate population selection on services. Through the proposed approach, population demand on healthcare services is adjusted by a Huff Model-based selection probability that reflects the impacts of both distance impedance and service site capacity.

Spatial patterns of the census tracts' spatial access to healthcare services for each distance impedance coefficient. Note: β is the distance impedance coefficient

Spatial patterns of the census tracts’ spatial access to healthcare services for each distance impedance coefficient. Note: β is the distance impedance coefficient

“The new approach moderates the over- or under-estimating of population demand that occurred with previous methods. Furthermore, the method uses a continuous distance impedance weight function instead of the arbitrarily defined subzones of previous studies. A case study of spatial access to primary care in Springfield, MO, showed that the proposed method can effectively moderate the population demand on service sites and therefore can generate more reliable spatial access measures.”

Exploring Mobility Indoors: An Application of Sensor-based and GIS Systems

Transactions in GISTransactions in GIS, Volume 18, Issue 3, pages 351–369, June 2014

By Anastasia Petrenko, Anton Sizo, Winchel Qian, A. Dylan Knowles, Amin Tavassolian, Kevin Stanley, and Scott Bell

“The popularization of tracking devices, such as GPS, accelerometers and smartphones, have made it possible to detect, record, and analyze new patterns of human movement and behavior. However, employing GPS alone for indoor localization is not always possible due to the system’s inability to determine location inside buildings or in places of signal occlusion. In this context, the application of local wireless networks for determining position is a promising alternative solution, although they still suffer from a number of limitations due to energy and IT-resources. Our research outlines the potential for employing indoor wireless network positioning and sensor-based systems to improve the collection of tracking data indoors.

3D model of campus that represents the building floors where the participants mainly spent their time. Colors close to red correspond to the locations with a high number of daily duty cycles with data, blue to those with a low number.

3D model of campus that represents the building floors where the participants mainly spent their time. Colors close to red correspond to the locations with a high number of daily duty cycles with data, blue to those with a low number.

“By applying various methods of GIScience we developed a methodology that can be applicable for diverse human indoor mobility analysis. To show the advantage of the proposed method, we present the result of an experiment that included mobility analysis of 37 participants. We tracked their movements on a university campus over the course of 41 days and demonstrated that their movement behavior can be successfully studied with our proposed method.”

A Multi-indicator Framework for Mapping Cultural Ecosystem Services: The Case of Freshwater Recreational Fishing

Ecological IndicatorsEcological Indicators, Volume 45, October 2014, Pages 255–265

By Amy M. Villamagna, Beatriz Mogollón, and Paul L. Angermeier

“Highlights

  • We developed a framework to map freshwater fishing, a cultural ecosystem service.
  • We compared capacity and demand spatially to assess relative sustainability.
  • Fishing demand was highest in urban areas.
  • Capacity was low in the eastern region of the study area.
  • Relative capacity exceeded demand in 83% of North Carolina and 95% of Virginia.
  • High demand-low capacity areas were common in suburban areas of North Carolina.

“Despite recent interest, ecosystem services are not yet fully incorporated into private and public decisions about natural resource management. Cultural ecosystem services (CES) are among the most challenging of services to include because they comprise complex ecological and social properties and processes that make them difficult to measure, map or monetize. Like others, CES are vulnerable to landscape changes and unsustainable use. To date, the sustainability of services has not been adequately addressed and few studies have considered measures of service capacity and demand simultaneously. To facilitate sustainability assessments and management of CES, our study objectives were to (1) develop a spatially explicit framework for mapping the capacity of ecosystems to provide freshwater recreational fishing, an important cultural service, (2) map societal demand for freshwater recreational fishing based on license data and identify areas of potential overuse, and (3) demonstrate how maps of relative capacity and relative demand could be interfaced to estimate sustainability of a CES.

Freshwater recreational fishing, a popular pastime, generates income, jobs, and funding for conservation. Image: Virginia Tech

Freshwater recreational fishing, a popular pastime, generates income, jobs, and funding for conservation. Image: Virginia Tech

“We mapped freshwater recreational fishing capacity at the 12-digit hydrologic unit-scale in North Carolina and Virginia using a multi-indicator service framework incorporating biophysical and social landscape metrics and mapped demand based on fishing license data. Mapping of capacity revealed a gradual decrease in capacity eastward from the mountains to the coastal plain and that fishing demand was greatest in urban areas. When comparing standardized relative measures of capacity and demand for freshwater recreational fishing, we found that ranks of capacity exceeded ranks of demand in most hydrologic units, except in 17% of North Carolina and 5% of Virginia. Our GIS-based approach to view freshwater recreational fishing through an ecosystem service lens will enable scientists and managers to examine (1) biophysical and social factors that foster or diminish cultural ecosystem services delivery, (2) demand for cultural ecosystem services relative to their capacity, and (3) ecological pressures like potential overuse that affect service sustainability. Ultimately, we expect such analyses to inform decision-making for freshwater recreational fisheries and other cultural ecosystem services.”

OGC and Joint Research Centre to Collaborate on Standards for Geospatial Interoperability

OGC_Logo_Border_Blue_3DThe Open Geospatial Consortium (OGC®) and the European Commission’s Joint Research Centre (JRC) have signed a collaboration agreement to enhance the development and use of geospatial standards. It is anticipated that this collaboration will enable the JRC to more effectively contribute to the OGC standards process, and facilitate the consideration of European objectives and requirements during the development of international open geospatial standards.

The agreement formalises the partners’ planned collaboration in the field of development, application, maintenance and promotion of international open geospatial standards and best practices in support of European objectives and requirements, in particular in relation to the implementation of the INSPIRE Directive.

“This is an important step forward for both of our organisations,” explained Mark Reichardt, President and CEO of the OGC. “OGC benefits from the JRC’s leadership in advancing geospatial information sharing across Europe, enabled by open standards, including those of the OGC. The European Union benefits greatly from open standards that improve discovery, sharing and application of diverse collections of information to address a range of important issues.”

According to Mrs. Maria Betti, Director of the JRC’s Institute for Environment and Sustainability, “During the development and implementation of INSPIRE, the JRC has gathered a lot of experience on the implementation of infrastructures for geospatial and environmental data based on interoperability standards – on an unprecedented scale. The joint activities of the OGC and the JRC will be instrumental in feeding this experience into the international standardisation process.”

About the JRC

As the Commission’s in-house science service, the Joint Research Centre’s mission is to provide EU policies with independent, evidence-based scientific and technical support throughout the whole policy cycle. Working in close cooperation with policy Directorates-General, the JRC addresses key societal challenges while stimulating innovation by developing new methods, tools and standards, and sharing its know-how with the Member States, the scientific community and international partners. Visit the JRC Science Hub at https://ec.europa.eu/jrc/ .

The JRC is the technical coordinator of the Directive establishing an Infrastructure for Spatial Information in the European Community (INSPIRE – 2007/2/EC).

About the Open Geospatial Consortium (OGC®)

The OGC® is an international consortium of more than 475 companies, government agencies, research organisations, and universities participating in a consensus process to develop publicly available geospatial standards. OGC standards support interoperable solutions that “geo-enable” the Web, wireless and location-based services, and mainstream IT. Visit the OGC website at http://www.opengeospatial.org/.

[Source: OGC press release]

Scientists Use LiDAR, 3-D Modeling Software to Intricately Map Active Chinese Fault Zone

Chinese and American scientists collaborating in the study of an active seismic fault that produced one of China’s most deadly earthquakes say their deployment of an airborne LiDAR system, which uses pulses of laser light to calculate distances and chart terrain features, has helped them produce the most precise topographical measurements ever of the fault zone.

“Light detection and ranging (LiDAR) presents a new approach to build detailed topographic maps effectively,” they report. They add that these high-precision three-dimensional models can be used to illustrate not only land surface changes following past quakes, but also features of past ruptures that could point to the possibility of future temblors.

Experts at the State Key Laboratory of Earthquake Dynamics and at the National Earthquake Infrastructure Service in Beijing, working with a colleague at the United States Geological Survey (USGS) in Pasadena, California, mounted a Leica ALS-60 LiDAR system aboard a Chinese Yun Five aircraft and then began scanning the Haiyuan fault zone in a series of flights over the course of a week. The fault zone is similar to the San Andreas fault in California, which has similarly been scanned and studied as a comparison.

“During the past century,” they explain in a new study, “the Haiyuan fault zone produced two great earthquakes: the M 8.5 Haiyuan earthquake in 1920, along the eastern Haiyuan fault, and the M 8𔃆.3 Gulang earthquake in 1927.”

“The Haiyuan earthquake of 16 December 1920 is one of the largest intra- continental earthquakes ever documented in history,” they add, “and ruptured about a 237-kilometer-long ground surface, with a maximum left-lateral slip of 10.2 m, and claimed over 220,000 lives.”

In the new study, “Quantitative study of tectonic geomorphology along the Haiyuan fault based on airborne LiDAR,” lead scientist Jing Liu and her colleagues at the Earthquake Dynamics Lab, part of the China Earthquake Administration in Beijing, state their experiments with the LiDAR scanning system and related building of a high-resolution topographical model provide “an example of how LiDAR data may be used to improve the study of active faults and the risk assessment of related hazards.”

Sections of the 3D digital model generated with the LiDAR data are “intensively analyzed to demonstrate tectonic geomorphic feature identification and displacement measurement,” they state. The LiDAR data are also used, for example, to calculate horizontal and vertical coseismic offsets in one section of the fault zone.

LiDAR data can be used to verify measurements made during fieldwork on offsets of tectonic landform features, state co-authors Tao Chen, Pei Zhen Zhang, Jing Liu, Chuan You Li, and Zhi Kun Ren, along with Ken Hudnut at the USGS, who visited the China Earthquake Administration to participate in this study. “The offset landforms are visualized on an office computer workstation easily, and specialized software may be used to obtain fault displacement measurements quantitatively,” they explain.

With LiDAR-generated digital models of the topography across fault zones, the “link between fault activity and large earthquakes is better recognized, as well as the potential risk for future earthquake hazards,” says the team of scientists.

More precise measurements of the active fault zone made possible by the LiDAR system, and their depiction in sophisticated three-dimensional maps, are helping scientists not only in basic research, but also in terms of calculating the probability of a seismic shock recurring, say the co-authors of the new study, which was published online in the journal Chinese Science Bulletin by Science China Press and Springer-Verlag.

Airborne laser swath mapping helps scientists to virtually remove the vegetation covering from topographical models; this “bare earth” representation provides for more accurate identification of tectonic features and changes following a quake.

A LiDAR airborne scanning system of the Earth’s terrain was deployed over the section of the southwestern Chinese province of Sichuan that was the epicenter of a Mw7.9 earthquake that struck in May of 2008; LiDAR data were used to map the scale of landslides and ultimately to develop rescue schemes.

In the new study, the Chinese and American scientists say that digital models created using LiDAR data from the Haiyuan fault zone “have a much higher resolution than existing topographic data and most aerial photographs, allowing us to map the locations of fault traces more accurately than ever.”

The high level of precision of the digital models constructed with information from the LiDAR laser scans of the topography in this fault zone will encourage future “site-specific fault activity studies,” state the scientists.

“In the future,” they predict, “we can expect that more and more concepts or models of fault activity would benefit from this unprecedented survey technique.”

Along the Haiyuan fault zone in the western Chinese province of Gansu, LiDAR scans and related digital models have already been used to identify 600 channels and other linear geomorphic features slated for more comprehensive analysis.

“The next step is to measure the displacements along the whole Haiyuan fault and analyze the principle of the slip distribution,” states the team of scientists, “which would help people better understand the fundamental link between fault activity and large earthquakes and assess potential risk for future earthquake hazards.”

In places where slip during past earthquakes was less pronounced, it is possible that future earthquakes could have greater slip in order to accommodate and equalize motions along the fault system. Alternatively, slip may be large repeatedly in some places and small elsewhere. Such variations in slip may help to assess future hazards, so observations of this kind are very important to answer unresolved questions that are central to research on hazards of earthquake fault zones around the world.

[Source: Science China Press]

geneGIS: Geoanalytical Tools and Arc Marine Customization for Individual-Based Genetic Records

Transactions in GISTransactions in GIS, Volume 18, Issue 3, pages 324–350, June 2014

By Dorothy M. Dick, Shaun Walbridge, Dawn J. Wright, John Calambokidis, Erin A. Falcone, Debbie Steel, Tomas Follett, Jason Holmberg, and C. Scott Baker

“To improve understanding of population structure, ecosystem relationships and predictive models of human impact in cetaceans and other marine megafauna, we developed geneGIS, a suite of GIS tools and a customized Arc Marine data model to facilitate visual exploration and spatial analyses of individual-based records from DNA profiles and photo-identification records. We used the open source programming language Python 2.7 and ArcGIS 10.1 software to create a user-friendly, menu-driven toolbar linked to a Python Toolbox containing customized geoprocessing scripts. For ease of sharing and installation, we compiled the geneGIS program into an ArcGIS Python Add-In, freely available for download from the website http://genegis.org. We used the Lord-Castillo et al. (2009) Arc Marine data model customization as the starting point for our work and retained nine key base Arc Marine classes. We demonstrate the utility of geneGIS using an integrated database of more than 18,000 records of humpback whales (Megaptera novaeangliae) in the North Pacific collected during the Structure of Populations, Levels of Abundance and Status of Humpback Whales in the North Pacific (SPLASH) program. These records represent more than 8,000 naturally marked individuals and 2,700 associated DNA profiles, including 10 biparentally inherited microsatellite loci, maternally inherited mitochondrial DNA, and genetic sex.”

OGC Seeks Comment on Charter for New netCDF Standards Working Group

ogcA new netCDF Standards Working Group (SWG) is being chartered to further extend the existing netCDF standard with extension modules for additional data models, encodings, and conventions. Initiators of the new SWG seek comments from the public on the draft new charter. The comment period closes on 2014-07-11.

NetCDF has already been established as an adopted OGC standard, encompassing a core standard along with extensions for specific data models and encodings and for the Climate and Forecast (CF) metadata conventions. The additional extensions to be addressed by the new netCDF SWG include, but are not limited to, those currently under consideration by the currently existing CF-netCDF 1.0 SWG, which will be disbanded and replaced by this NetCDF SWG.

NetCDF (network Common Data Form) is a data model for multidimensional array-oriented scientific data, a freely distributed collection of access libraries implementing support for that data model, and a machine-independent storage format. Together, the interfaces, libraries, and format support the creation, access, and sharing of scientific data.

Having already established netCDF as an OGC standard for binary encoding has made it possible to incorporate standard delivery of data in binary form via several OGC protocols, including the OGC Web Coverage Service (WCS), Web Feature Service (WFS), and Sensor Observation Service (SOS) Interface Standards. Work is already underway on an extension to GML and OWS for delivery of data encoded in netCDF. Additional netCDF conventions extensions will improve the effectiveness and usability of netCDF datasets by a wider community. One example is the recently released OGC NetCDF Uncertainty Conventions Discussion Paper.

The OGC® is an international consortium of more than 475 companies, government agencies, research organizations, and universities participating in a consensus process to develop publicly available geospatial standards. OGC standards support interoperable solutions that “geo-enable” the Web, wireless and location-based services, and mainstream IT. Visit the OGC website at http://www.opengeospatial.org/.

[Source: OGC press release]