Glendale Valley Municipal Authority Improves Water Quality with GIS

With maps based on Esri technology, Glendale Valley Municipal Authority is able to quickly locate problems and plan for future renovations, a move that will improve water quality and reduce groundwater infiltration to the sewage system. The company, which serves a growing population of 1,000 customers in the State of Pennsylvania, is taking advantage of Esri’s Small Utility Enterprise License Agreement (SU-ELA) program.

Using Esri’s geographic information system (GIS) technology, Glendale Valley Municipal Authority has been able to map its existing water and wastewater system. Printed map booklets are now available to field crews, engineers, and customers. The maps are also fostering good communication between the company and the county government GIS department, ensuring both entities’ abilities to keep databases current.

“The ELA program allowed us to attain the fully functional GIS software we need at a price that we could afford,” said Shawn Kauffman, GIS specialist/web designer for Glendale Valley Municipal Authority. “The program also gives us access to Esri Support Services and the Virtual Campus courses, which proved crucial for me.”

Through Esri’s Small Utility ELA program, small utilities receive unlimited deployments of Esri’s core ArcGIS platform as well as maintenance and support for products, staff training, passes to the Esri International User Conference, and Esri data models. The Small Utility ELA program is open to utilities with 100,000 or fewer meters.

[Source: Esri press release]

Geo-Visual Analytics: Requirements from a User Perspective

GeoViz: Linking Geovisualization with Spatial Analysis and Modeling, 10-11 March 2011, Hamburg, Germany

Doris Dransch and Mike Sips

“The scientific investigation of real-world phenomena in space and time has become a data-intensive science in the last decade; especially at interdisciplinary research laboratories like the German Research Centre for GeoSciences (short GFZ). Terrestrial, marine and space-based high resolution sensor systems as well as complex simulation models create massive data. For instance the TerraSAR-X and the following TanDEM-X Satellite mission launched in June 2007 have created 1.5 Petabyte data since now which would, if stored at CDs, form a stack of more than 430 m and thus, top the Eiffel Tower. New insights into phenomena in space and time are often only achieved by deriving a good understanding of relationships hidden in those vast volumes of data.”

Spatio-Temporal Analysis for Bioindicators of Climate Change

Virginia Polytechnic Institute and State University, Friday, April 1, 2011, 1:00 p.m. – 2:00 p.m., NVC 325

Ali Arab

“Climate Researchers are increasingly interested in analyzing spatio-temporal trends for environmental and ecological processes that are viewed as “bioindicators” of climate change (e.g., changes in migratory patterns of birds, changes in intensity and frequency of precipitation events, floods, tornadoes and hurricanes). In particular, there is interest in modeling uncertainty for these processes using statistical methods, as a result of the recent debates over global warming of the earth’s climate. The complexity, and often high-dimensionality, of these processes exhibited through different scales of spatial and temporal variability necessitates the implementation of statistical models applicable to very large data sets. In this work, we present a general framework for computationally efficient spatio-temporal trend analysis of environmental and ecological processes with linkage to climatological effects. The proposed approach allows climate researchers to investigate spatial and temporal patterns of environmental and ecological response to climate events. Finally, example applications of the proposed approach will be discussed.”

Application of an Adaptive and Directed Kernel Density Estimation (AD-KDE) for the Visual Analysis of Traffic Data

GeoViz: Linking Geovisualization with Spatial Analysis and Modeling, 10-11 March 2011, Hamburg, Germany

Jukka M. Krisp, Stefan Peters, and Masria Mustafa

“Remote sensing and tracking technologies (such as tracking mobile phones and in vehicle navigation systems) have enabled us to store the position of individual cars over time. A number of previous studies have investigated methods to display the density of cars on a road network. These density maps show density of vehicles moving on the street as an isopleths map within a city or region at a single instance. Often these investigations use the well known kernel density estimations (KDE) to display static densities (and traffic hot-spots) representing one point in time. This “classic” method may reveal the traffic hotspots, but it does not recognize the movement trends within dynamic point data representing the individual cars. Therefore we investigate how to display the dynamic component of point densities and the density changes. We take two points in time (set1 and set2) representing the individual vehicles positions and apply an adaptive directed kernel density estimation (AD-KDE), which recognizes the underlying dynamics of the individual points.”

Spatial Analysis of Land Cover Determinants of Malaria Incidence in the Ashanti Region, Ghana

PLoS ONE 6(3): e17905. 2011.

Anne Caroline Krefis, Norbert Georg Schwarz, Bernard Nkrumah, Samuel Acquah, Wibke Loag, Jens Oldeland, Nimako Sarpong, Yaw Adu-Sarkodie, Ulrich Ranft, and Jürgen May

“Malaria belongs to the infectious diseases with the highest morbidity and mortality worldwide. As a vector-borne disease malaria distribution is strongly influenced by environmental factors. The aim of this study was to investigate the association between malaria risk and different land cover classes by using high-resolution multispectral Ikonos images and Poisson regression analyses. The association of malaria incidence with land cover around 12 villages in the Ashanti Region, Ghana, was assessed in 1,988 children <15 years of age. The median malaria incidence was 85.7 per 1,000 inhabitants and year (range 28.4–272.7). Swampy areas and banana/plantain production in the proximity of villages were strong predictors of a high malaria incidence. An increase of 10% of swampy area coverage in the 2 km radius around a village led to a 43% higher incidence (relative risk [RR] = 1.43, p<0.001). Each 10% increase of area with banana/plantain production around a village tripled the risk for malaria (RR = 3.25, p<0.001). An increase in forested area of 10% was associated with a 47% decrease of malaria incidence (RR = 0.53, p = 0.029).

“Distinct cultivation in the proximity of homesteads was associated with childhood malaria in a rural area in Ghana. The analyses demonstrate the usefulness of satellite images for the prediction of malaria endemicity. Thus, planning and monitoring of malaria control measures should be assisted by models based on geographic information systems.”

Development of Open Source Functionality for the Analysis and Visualization of Remotely Sensed Time Series

GeoViz: Linking Geovisualization with Spatial Analysis and Modeling, 10-11 March 2011, Hamburg, Germany

Connie A. Blok, Ulanbek D. Turdukulov, Raul Zurita-Milla, Bas Retsios, and Martin Schouwenburg

“The GEONETCast data dissemination system delivers low cost environmental data to users worldwide. Long time series of images from various satellites can be obtained to study dynamic phenomena. To explore the dynamics, displaying the images as animation with few controls is a common practice. However, some problems need to be addressed. We present how the current approach to animate time series of satellite images can be improved by pre-processing (pixel co-registration and resampling data from satellites with different spatio-temporal resolution), by analytical functionality (detecting features of interests and feature tracking) and by enriching the visualization environment with more interactive functions. But even then, animations still lead to information overload. We discuss our attempts to reduce this problem, and describe the resulting software component that is fully dedicated to visual exploration and analysis of dynamic phenomena and will be added to the open source ILWIS software.”

Quantitative Analysis of Transmission Parameters for Bluetongue Virus Serotype 8 in Western Europe in 2006

Veterinary Research 2011, 42:53

Aline A de Koeijer, Gert Jan Boender, Gonnie Nodelijk, Christoph Staubach, Estelle Meroc, and Armin RW Elbers

“The recent bluetongue virus serotype 8 (BTV-8) epidemic in Western Europe struck hard. Controlling the infection was difficult and a good and safe vaccine was not available until the spring of 2008. Little was known regarding BTV transmission in Western Europe or the efficacy of control measures. Quantitative details on transmission are essential to assess the potential and efficacy of such measures. To quantify virus transmission between herds, a temporal and a spatio-temporal analysis were applied to data on reported infected herds in 2006. We calculated the basic reproduction number between herds (Rh: expected number of new infections, generated by one initial infected herd in a susceptible environment). It was found to be of the same order of magnitude as that of an infection with Foot and Mouth Disease (FMD) in The Netherlands, e.g. around 4. We concluded that an average day temperature of at least 15 ºC is required for BTV-8 transmission between herds in Western Europe. A few degrees increase in temperature is found to lead to a major increase in BTV-8 transmission.

“We also found that the applied disease control (spatial zones based on 20 km radius restricting animal transport to outside regions) led to a spatial transmission pattern of BTV-8, with 85% of transmission restricted to a 20 km range. This 20 km equals the scale of the protection zones. We concluded that free animal movement led to substantial faster spread of the BTV-8 epidemic over space as compared to a situation with animal movement restrictions.”