In general, the procedure for developing the land developability index involves the use of weighted spatial modeling and zoning statistics to identify developable lands at the 90-meter resolution and aggregation of the pixels to a geographic scale at which the developability index is produced. Weighted spatial modeling is used to sum up logical variables based on spatial ranking. Zonal statistics averages the values of pixels within each polygon’s boundary.
The land developability index is generated in six steps.
First, each of the four input datasets is converted to a single logical raster layer in the 90-meter resolution—the NLCD and SRTM DEM are reclassified to logical raster layers; and the USGS Federal and Indian Lands and the UCSB MAD are converted to layers in the 90-meter resolution.
Second, based on the converted input datasets, we derive six data layers including surface water, wetland, federal/state-owned land, Indian reservation, built-up land, and steep slope.
Third, for each of the six layers, land pixels that are developable are coded as “1” and that are undevelopable as “0.”
Fourth, we sum up the attributes across the six data layers into a single data layer in the 90-meter resolution.
Fifth, each land pixel is re-classified: any land pixel that had a value of “6” is recoded to “1” representing “developable”; the other land pixels are re-recoded to “0” representing “undevelopable.”
Sixth, zonal statistics is used to develop a land developability index for a geographic scale of interest. In this project, we generated developability at the state level and county level by using the 2010 Cartography Boundary Files (CBF) of the U.S. Census Bureau.
It should be noted that this methodology can be used for generating a land developability index for any unit of geography that is equal to or larger than the pixel sizes of the available data layers. These scales include metro/nonmetro areas, census tracts, congressional districts, block groups, zip codes, etc. For social science research, this methodology can be very useful for analysis involving sub-county units of geography, where the components of land conversion and development can be measured more meaningfully. The sub-county units of geography can include units within political boundaries, census-delineated boundaries, and boundaries defined for other purposes.