Proceedings of the National Academy of Sciences (PNAS)

Michael E. Dorcas, John D. Willson, Robert N. Reed, Ray W. Snow, Michael R. Rochford, Melissa A. Miller, Walter E. Meshaka, Jr., Paul T. Andreadis, Frank J. Mazzotti, Christina M. Romagosa, and Kristen M. Hart

“Invasive species represent a significant threat to global biodiversity and a substantial economic burden. Burmese pythons, giant constricting snakes native to Asia, now are found throughout much of southern Florida, including all of Everglades National Park (ENP). Pythons have increased dramatically in both abundance and geographic range since 2000 and consume a wide variety of mammals and birds. Here we report severe apparent declines in mammal populations that coincide temporally and spatially with the proliferation of pythons in ENP. Before 2000, mammals were encountered frequently during nocturnal road surveys within ENP. In contrast, road surveys totaling 56,971 km from 2003–2011 documented a 99.3% decrease in the frequency of raccoon observations, decreases of 98.9% and 87.5% for opossum and bobcat observations, respectively, and failed to detect rabbits.

Map of South Florida illustrating sampling locations in relation to python distribution. Road surveys for mammals were conducted in the 1990s and 2000s along the Main Park Road (MPR) in Everglades National Park (ENP). Areas recently invaded by pythons and surveyed for mammals in 2009–2011 include Big Cypress National Preserve (BCNP), Collier-Seminole State Park (CSSP), Chekika (CHK), and Key Largo. Immokalee and Corbett Wildlife Management Area (CWMA; north of the map) are two sampled sites where pythons have not yet become established. The purple region represents the area of ENP where pythons were found in the 1990s and where reproduction was first reported (16). Red triangles represent localities of pythons found during 2008–2009.

“Road surveys also revealed that these species are more common in areas where pythons have been discovered only recently and are most abundant outside the python’s current introduced range. These findings suggest that predation by pythons has resulted in dramatic declines in mammals within ENP and that introduced apex predators, such as giant constrictors, can exert significant top-down pressure on prey populations. Severe declines in easily observed and/or common mammals, such as raccoons and bobcats, bode poorly for species of conservation concern, which often are more difficult to sample and occur at lower densities.”

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Ugur Alganci, Dursun Seker, and Elif Sertel

“The rapid population growth and related urbanization in developing countries mostly affect the metropolitan cities. The urban sprawl that comes with rapid population growth changes land use / cover (LULC) dynamics that mostly results with decrease in natural resources such as forests or pastures and farmlands. In the last decade, a common population growth is observed all over Turkey with increase at 66 provinces out of 81. Antalya is one of the important cities of Turkey that exposed to unplanned urban sprawl. It was at the 29th place according to 1927 population census while it rose to 7th place according to 2000 census results. According to “9th Progress Report” issued by Ministry of Development, Antalya is the city that exposed to fastest population growth with a rate of %0, 48 during 1990-2000.
Antalya is the most popular touristic city of the Turkey, with its 650 km of coastline, appropriate climatic conditions, historical and natural beauties. Its population has increased due to employment facilities and migration related to tourism. It is also a n important agricultural center with its fertile soil and rainy climate. Development in industry and building trade also results with continuous development and rapid urbanization. Main effects of population growth and related urbanization are; change of watersheds, forests and agricultural lands into settlement in an irregular and uncontrolled way and urban sprawl.

“In terms of effective analysis of urbanization; determination of spatial distribution and trend, effects on other land cover types and relationship between topographic parameters become very important. At this point, spatial and topographic information derived from satellite imagery can be used as main data resources. Images obtained from optical satellites that are capable of observing large areas fastly and repeatedly, have been used for decomposition of land cover types and time dependent changes of them depending on spatial, spectral and temporal resolution capabilities. Spatio-temporal analysis of satellite images provides valuable information about changes in LULC dynamics.

“In this research, the effects of urban sprawl over LULC dynamics of Antalya were investigated in terms of spatial and areal changes using multitemporal satellite imagery. Landsat 5 TM images belonging to 1984, 2001 and 2010 were subjected to registration and supervised classification process. LULC information derived from these analyses was used for areal changes between years. Topographic parameters such as aspect and slope were produced from ASTER GDEM data at the same time. After applying a raster –vector conversation to whole dataset, relationship between LULC changes and spatial-topographic characteristics of the area was determined.”

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Golden Research Thoughts

Debabrata Mondal

“In modern time, Geographic Information System (GIS) has been considered as a powerful tool in mapping of ground water resources. The study area Murshidabad district has experienced a remarkable change in ground water table throughout the decades. The present paper is an attempt to evaluate the decadal trend of ground water fluctuation in several blocks of the district along with their possible causes by using the data from secondary sources and processed them through GIS software.

“Groundwater is the only reliable water resource for domestic, as well as for agriculture practice in those countries where rainfall is erratic. Since the country of India has its economic base lying on agricultural sector, a major emphasis has been given to accelerate the agricultural production without concerning the environmental issues for feeding its huge population. From the last few decades gradual depletion of groundwater supplies as a consequence of continued population growth and initiation of Boro cultivation over the Gangetic moribund delta has now been considered as an emerging problem. Now a day’s Murshidabad district is also facing this invisible hazard of groundwater depletion. In this regard monitoring, analyzing of groundwater is necessary for assessing its quantity.                                                                                                                                                                                                                                                                                                                     “Ground water fluctuation map is an important tool for analyzing the temporal as well as spatial changing pattern of groundwater resources. In this regard Geographic Information System (GIS) plays a crucial role for analyzing, model building and interpreting the groundwater data. In order to obtain long term groundwater information, GIS has been used in this study to visually and spatially analyze groundwater data.”

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Benedikt Gräler, Lydia Gerharz, and Edzer Pebesma

“This study investigates the potential of spatio-temporal kriging approaches for daily mean PM10 concentrations. The methods used include separate daily variogram estimates, temporally evolving variograms, the metric model, the separable covariance model and the product-sum model, and are combined with multiple linear regression. These methods are applied to daily mean rural background PM10 concentrations across Europe for the year 2005, and incorporate daily EMEP model data and elevation data as predictors.

Interpolated maps for daily PM10 concentration from May 1 to 9, 2005.

“The air quality indicators used in this study are the daily and yearly mean PM10 concentrations and the number of days exceeding the limit value 50 µg/m³ (NOE). The quality assessment of the different techniques relies on a cross-validation. Statistical measures are used to quantify the improvement for different indicators.

“It is shown that daily interpolations can improve the statistical performance of the interpolation of annual mean PM10 concentrations. Furthermore, some advantages of daily estimates are described. Besides the improvement in annual mean PM10 concentration maps, studying the phenomenon in a wider spatio-temporal context becomes possible with daily estimates. Especially the estimation the number of days PM10 concentrations exceed certain limits can be done in a more natural way. Likewise, the detection of outliers and data inhomogeneity benefits from a daily spatio-temporal model.

“Interpolation with the simple spatio-temporal variogram models used here exploits the temporal correlations present and out performs the purely spatial interpolation methods. Based on temporal variability of the spatial short-distance variation component, a discussion is given on the suitability of this statistic to infer measurement errors, and alternative approaches are proposed.”

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Thomas Brinkhoff and Stephan Jansen

“Recent disastrous floodings have demonstrated the demand for early flood warnings. This need will be enforced by the expected climate change that probably leads to more torrential rain. In general, flood forecasts concentrate on large rivers considering water gauges. However, there exist a large number of smaller drainage areas with a size of 100 to 1000 square kilometers. In such areas, disastrous drainages may happen after heavy rain that cannot reasonably be observed by gauges because the water level changes very fast without having enough time for warnings.

WEBBOS web client depicting the sensors of a sensor network.

“Thus, the creation of early flood warnings for small drainage areas is still an unsolved challenge. One promising approach for solving this problem is the observation of the soil humidity because that measure decides how much of the precipitation will drain off. WEBBOS is a joint project of two universities funded by the German Federal Ministry of Education and Research. It has the objective to build a web-based sensor system for early flood warnings by measuring soil moisture profiles. Within this project, special sensors measuring the soil humidity in different depths have been developed and successfully tested. These sensors were integrated into sensor nodes that form local sensor networks. Such a sensor network should be located in an area with a high variety of soil humidity, which typically happens near to small rivers on sloping terrains.

“Like in other early-warning and disaster management systems, it is important to incorporate the sensor measurements into a geospatial information service that allows managing sensor data. This encloses the visualization of the sensor measurements and the control of the soil humidity sensors as well as the detection and processing of alarm events. Interoperability is an important issue for such systems. Therefore, the Open Geospatial Consortium (OGC) started the Sensor Web Enablement (SWE) initiative 5 years ago and specified several services and data models in the meantime. The 52° North Sensor Web framework is the most prominent implementation of SWE specifications.

“WEBBOS implemented its information system using those specifications and the 52° North SWE framework. Many standard requirements can be solved by following such an approach without additional efforts. However, often there are important demands that need more sophisticated solutions. Such cases and their solutions for the WEBBOS project will be discussed in the following:

“The support of early flood warnings based on soil moisture profiles requires temporal 3D measurements and 3D models of soil humidity for each sensor network: Only the relation and difference between the humidity in different depths and their development over the time allow detecting relevant events. The temporal aspect is sufficiently covered by the current SWE specifications. However, these specifications and their implementation are mainly 2D-oriented. The latter is also caused by the underlying spatial database systems which are restricted to simple feature geometries. For solving this challenge, a layered sensor model has been developed and applied to the SWE implementation. This enables us to cope with these restrictions.

“An important issue for such systems is the detection of potentially dangerous situations. This requires the description of spatio-temporal events and their detection. For this purpose, the OCG currently proposed (as discussion papers) the Sensor Event Service (SES) and the Event Pattern Markup Language (EML). The WEBBOS project demonstrated that these specifications can be successfully applied for the evaluation of soil moisture profile measurements.

“Standard visualization tools are often not sufficient for an adequate visualization of sensor data. However, the use of SWE services restricts and formalizes the syntax and semantics of the sensor measurements and of sensor metadata. Therefore, open toolkits are well-suited for developing flexible solutions that can be easily adapted to the requirements of special applications. In case of the WEBBOS project, we followed this approach by extending the popular JavaScript map library “OpenLayers”. We introduced subclasses for sensors and sensor data that can be flexibly used in standard vector layers of OpenLayers. The web client allows retrieving sensor data and metadata by the Sensor Observation Service (SOS) as well as controlling and evaluating the SES.

“Overall, the WEBBOS project demonstrated the strengths and deficiencies of the current SWE services and provided feasible solutions for sensor networks measuring soil moisture on the top of standard geospatial software packages. “

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GIScience & Remote Sensing, Volume 48, Number 3 / July-September 2011

Yang Liu, Xiufeng Wang, Meng Guo, Hiroshi Tani, Nobuhiro Matsuoka and Shinji Matsumura

“This study uses a multiple linear regression method to composite standard Normalized Difference Vegetation Index (NDVI) time series (1982-2009) consisting of three kinds of satellite NDVI data (AVHRR, SPOT, and MODIS). This dataset was combined with climate data and land cover maps to analyze growing season (June to September) NDVI trends in northeast Asia. In combination with climate zones, NDVI changes that are influenced by climate factors and land cover changes were also evaluated. This study revealed that the vegetation cover in the arid, western regions of northeast Asia is strongly influenced by precipitation, and with increasing precipitation, NDVI values become less influenced by precipitation. Spatial changes in the NDVI as influenced by temperature in this region are less obvious. Land cover dynamics also influence NDVI changes in different climate zones, especially for bare ground, cropland, and grassland. Future research should also incorporate higher-spatial-resolution data as well as other data types (such as greenhouse gas data) to further evaluate the mechanisms through which these factors interact.”

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Nikolaus Umlauf, Georg Mayr, Jakob Messner, and Achim Zeileis

“It is popular belief that the weather is “bad” more frequently on weekends than on other days of the week and this is often perceived to be associated with an increased chance of rain. In fact, the meteorological literature does report some evidence for such human-induced weekly cycles although these findings are not undisputed. To contribute to this discussion, a modern data-driven approach using structured additive regression models is applied to a newly available high-quality data set for Austria.

Spatial eect ^ fkr(longi; lati). The range of the color scale is 1.0 on the scale of the linear predictor.

“The analysis investigates how an ordered response of rain intensities is influenced by a (potential) weekend effect while adjusting for spatio-temporal structure using spatially varying effects of overall level and seasonality patterns. The underlying data are taken from the HOMSTART project which provides daily precipitation quantities over a period of more than 60 years and a dense net of more than 50 meteorological stations all across Austria.”

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GIScience & Remote Sensing

George Ch. Miliaresis and Andreas Tsatsaris

“The regional temporal and spatial multi-temporal land surface temperature (LST) MODIS dataset and elevation data are used to compute the day and night temperature variation in Greece in 2008. Clustering was applied and eight cluster centroids captured the temporal pattern of near-diurnal temperature (01:30 a.m. and 01:30 p.m.) variability while elevation statistics were computed per cluster. The spatial distribution of the clusters indicate that mean elevation, elevation variability, proximity to the sea, and the major inland water bodies were the key factors controlling the near-diurnal LST variability in Greece.”

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Sébastien Lord, Philippe Gerber, Christophe Sohn, Thierry Eggerickx, Jean-Pierre Hermia, Chris Kesteloot, Tim Cassiers, and Filip De Maesschalck

“This paper puts forward a methodology to rank the population along a hierarchical continuum, from a lower level to a higher level of social precariousness. Going beyond the complex layered issues related to the concept of poverty, it rather explores the notion of deprivation with the idea of social inequalities which are observable according to specific socio-economic key dimensions. Part of a broader research – Destiny1 – focusing on both the spatial and the temporal evolutions of social inequalities in Belgium and Luxembourg, this method represents a first phase of the project.

Territorial inequalities in housing for Luxembourg and Belgium in 2001

“The social inequalities are addressed in an individual perspective with disaggregated data. This standpoint allowed the analysis of the whole population for Belgium and Luxembourg in a ten-year period (1991 and 2001). The method is based, on the one hand, on the national censuses from both countries – the only comprehensive data available on an individual basis –, and on the second hand, on the European Union – Study on Income and Living Conditions Panel (EUSILC). These two data sources have been combined for accessing economic information from EU-SILC and transposed into the national censuses in both countries. The EU-SILC detailed data on household income were used as an indicator of social inequalities for three dimensions: education, socio-professional status and housing. This enabled to rank each individual on a “social continuum”. After a presentation of the methodological framework, individual ranking results are exposed and discussed on the basis of spatial analysis.”

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Indian Journal of Geo-Marine Sciences

Oza, S R; Singh, R K K; Vyas, N K; and Sarkar, Abhijit

“Present study aims at the investigation of long-term satellite derived images of Earliest Melting Onset Date (EMOD) and Latest Melting Onset Date (LMOD) to study the sea ice variability in the Arctic. By applying cluster classification technique on the images of EMOD and LMOD, clusters having similar tendency were retrieved. The locations of centroids of the clusters revealed a distinct pattern showing tendency of clusters towards the early/delayed onset of melting.

Clusters showing similar tendency of earliest and latest melt onset dates.

“It was observed that the clusters having larger differences between EMOD and LMOD fell within the ocean area that became ice-free in September 2007. This study indicates that similar analysis using information on the onset of melting over the recent past (1998-2009) may help to predict the ice-free vulnerable zones in the coming 6-8 years.”

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