With a mission to create affordable home ownership and housing opportunities in communities across the United States, the Fannie Mae Foundation needs to be able to assess and understand community-level geographic data. Program officers in five regions and the District of Columbia are responsible for reviewing grant applications for organizations involved in affordable housing or community development efforts.

With territories of between nine and 11 states, regional program officers need access to tools to help them understand the communities they serve. However, manual research into community characteristics can be too time-intensive. Three years ago, the foundation began to implement GIS analysis to enhance the level of information available to program officers.

The foundation's initial GIS efforts began with the manual creation of neighborhood studies, which provide community maps and demographic information for neighborhoods or communities identified by program officers. Within a few months, it became clear that the foundation's GIS team was running the same applications again and again, just for different geographic areas. The foundation developed templates based on the most common requests, but program officers still had to request the information, and the foundation's GIS users still had to run the templates.

"Once the templates were in place, then we began to look at the next step, which was to automate the process," says Kristopher Rengert, Ph.D., director of Urban and Metropolitan Research for the Fannie Mae Foundation. "We wanted something that would allow the information to be immediately accessible and easy to use."

To help automate the process, Rengert, a long-time user of Esri software products, turned to the consulting team at Esri-Washington, D.C. The consulting team worked closely with the foundation to determine the best approach for automating the neighborhood studies. Esri consultants held several brainstorming meetings, which allowed the foundation to determine and prioritize the requirements for the application. Based on the brainstorming meetings, the foundation chose to break the project into two phases. The first phase, launched at the end of 2001, includes information for the metropolitan areas in which the foundation has offices. The second phase, scheduled for implementation this winter, will expand the application to the entire United States.

The foundation chose to implement an Intranet-based application, called Fannie Mae Foundation (FMF)-MAPS, using ArcIMS with the ArcIMS Route Server extension. Because the foundation had previously used and liked Geographic Data Technology (GDT) data, Rengert chose GDT's ArcIMS Route Server data pack to provide the data foundation for FMF-MAPS. The consulting team worked with the foundation to define the specific hardware needed and determine the best foundation location for hosting the Intranet application.

All program officers have access to FMF-MAPS from the foundation's Intranet. Program officers select one of the metropolitan areas where the foundation has offices and use the ArcIMS navigation and selection tools to choose the extent of the area they wish to examine. The ArcIMS technology also allows program officers to select an area by entering an address and choosing a buffer around it.

Once the area of interest is defined, program officers turn on the block group layer, which overlays GDT's block group boundaries with street and address information. Program officers can create a summary report, which provides an orientation map and a table of nine variables determined by the Fannie Mae Foundation to be frequently critical in analyzing and understanding neighborhoods. For each of the variables, the report provides minimum, maximum, and average values. If program officers are interested in the variations of any variable, they can create a map showing the distribution of variable values for an area.