Spatial Analysis

A geographic point coverage was generated to represent the approximate location of the population-weighted centers of each community aggregation. The point coverage was developed to provide a population-based depiction of the aggregations and to facilitate analysis of the relationships between socioeconomic factors, community capacity, and aggregation location and proximity to other geographic features. Polygon representations of the block group aggregations inadequately reflect the location and distribution of populations within each aggregation. Many aggregations include large tracts of public land and other unpopulated areas, and the physical extent of the aggregation polygons often distorts the extent of the actual populations within them.

Point representations of each aggregation were created by averaging the coordinates of the internal points of the individual blocks that fall within the aggregation, weighted by the population of the block relative to the population of the entire aggregation. Block center points were used rather than block group center points in order to provide greater spatial accuracy of population centers. Block internal point coordinates (latitude and longitude), calculated by the Bureau of the Census, represent the approximate geographic center of the block. A total of 15,433 block center coordinates were used in this analysis. If, due to the shape of the block, the geographic center falls outside of the block, the internal point is relocated within the boundaries. Likewise, if the center falls within a body of water the internal point is relocated to a land area within the block (Census of Population and Housing, 1990b). Figure 2 shows the point representation of the 130 social assessment block group aggregations.

To further characterize each aggregation by geographic location relative to infrastructure, services, public land, and other factors, the aggregation point coverage was enhanced with some basic spatial data including:

Aerial distance to the nearest federal highway or interstate;
Aerial distance to the nearest state highway or major road;
Aerial distance to the closest major city with a population of 25,000 or greater;
Aerial distance to the nearest county seat;
Percentage of public land within an 8 kilometer radius.

FIGURE 2: Point Locations of Aggregations

While actual road miles or travel time may provide more explicit measures than aerial distances, time and resource limitations prohibited this type of detailed analysis. Moreover, since the aggregation center points are only representations of dispersed populations, the less precise aerial distances should suffice for this analysis. Creation of these variables permits the evaluation of spatial characterizations in developing typologies of aggregations as well as the examination of spatial relationships associated with socioeconomic factors and community capacity. These variables were selected, in part, due to a previous assessment of communities in the Pacific Northwest (FEMAT, 1993) where rudimentary analysis of spatial factors indicated that access to transportation corridors, density of federal land ownership, and general isolation may be related to community capacity. They were also used in the assessment of community well-being in the Sierra Nevada (Doak and Kusel, 1996).