This is a map displaying the dispersion of gases from a single source point over a 24-hour period. The data for the dispersion was created using the Open Burn/Open Detonation Model (OBODM) developed by the US Army. The data were calculated over a 6 km² area in a 100 m² grid using site specific material and historical meteorological data. The surface displayed is a triangulated irregular network created from the grid of interpolated gaseous concentrations. This map could be used to assess the environmental impact, if any, on the area surrounding the site.
This map shows various vector data symbolization methods using fictitious voter registration data for the city of Fitchburg, Massachusetts. Organized by census group, the data are symbolized using 3D pie charts representing the number of registered voters in each party as fractions of the total number of registered voters. The base symbolization represents the percentage of the total population that is registered to vote.
This map was created using a combination of on-site GPS data collection, photograph interpretation, and aerial photography digitization. The map displays a gas station with a network of monitoring wells from which groundwater was monitored and sampled. The groundwater contours were interpolated using a kriging algorithm. Well elevations were calculated based on an assumed vertical datum using an automatic sight level. The analytical groundwater data is displayed at each well using dynamic labels, pulling information directly from the attribute table. Using a Trimble Pro XRS GPS collection system, locations of the wells, utilities, and key structure corners were collected with sub-meter accuracy.
3D analysis and visualization can easily add new perspectives to spatial and temporal data. This database design incorporated building height in addition to x and y data. The buildings and street centerlines were digitized from georeferenced TIFFs of scanned maps of Charlottesville, VA circa 1920. The underlying aerial photography is from a more recent source.
This is a map combining aerial photography downloaded via a GIS data clearinghouse and a potable well database obtained from a state environmental department. There is a 20% transparency applied to the aerial photograph in order to reduce the output file size. The half-mile radius represents a buffer of the site location.
Creation of this map involved analyzing vector datasets before converting them to raster. Further analysis was performed on the derived raster data combined with additional data in native raster format. Species richness, road density, land ownership, percent slope, land cover type, and habitat potential were all factors in determining these Candidate Wildlife Refuge areas in Centre County, PA.
This map was created combining GPS collection, aerial photography digitization, and integrated CAD data. The map displays a gas station with a network of monitoring wells from which groundwater was pumped. The groundwater contours were interpolated using a kriging algorithm.
This is another example of a basemap created using a combination of field collected, mined, and digitized data. The proper research and integration of existing data is essential for minimizing budget impact.
This map displays an analysis of data representing tornados which occurred in Oklahoma on May 3, 1999. Areas are prioritized based on population density and the destructive force of each tornado path. Locations of churches, hospitals, and schools are displayed as candidate shelters for injured or displaced populations. Maps like this could be used to help concentrate disaster relief efforts in areas with greater need.
Geocoding is used in this example to compare a set of addresses with radon potential, roads, and topography. An address locator was created based on the road centerlines. The radon potential was determined by analyzing the soil types and geology of the area, as they can help determine certain potential for radon presence. Geocoding is an extremely useful tool for determining approximate locations of addresses, such as 203 Saw Mill Rd on this map.

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