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.”