Using Remotely Sensed Data in Urban Sprawl and Green Space Analyses

Abstract

Using two cities in southeast Idaho we developed a simple and widely applicable methodology for incorporating remotely sensed data into urban sprawl and green space analyses. We used land cover change data and Normalized Difference Vegetation Index (NDVI) data to assess: 1) location, amount, and direction of urban growth, 2) concentration and distribution of green space, and 3) fragmentation of green space areas. Our results document distinct patterns of growth for Pocatello, Idaho, compared to Idaho Falls, Idaho, over the past 15 years. Pocatello grew primarily to the north, while Idaho Falls grew more quickly and in a radial pattern from its urban center. These different growth patterns were influenced by topographic and landownership patterns of the region, as well as different zoning regulations. The simplicity of our methods and the minimal investment of time and money make incorporation ofremotely sensed data into urban growth and green space analyses a potentially powerful tool for the urban planner/manager.