GEOG 160
Mapping Our Changing World

9.11 New York: A Raster Case Study


Like Pennsylvania, the State of New York was compelled by the LLRW Policy Act to dispose of its waste within its own borders. New York also turned to GIS in the hope of finding a systematic and objective means of determining an optimal site. Instead of the vector approach used by its neighbor, however, New York opted for a raster framework.

Overview of the raster approach, part 1.
Figure 9.12. Overview of the raster approach adopted by the New York LLRW Siting Commission, part one.
Credit:  Monmonier, 1995.

Mark Monmonier, a professor of geography at Syracuse University (and a Penn State Dept. of Geography alumnus), has written that the list of siting criteria assembled by the New York Department of Environmental Conservation (DEC) was "an astute mixture of common sense, sound environmental science, and interest-group politics" (1995, p. 226). Source data included maps and attribute data produced by the U.S. Census Bureau, the New York Department of Transportation, and the DEC itself, among others. The New York LLRW Siting Commission overlaid the digitized source maps with a grid composed of cells that corresponded to one square mile (640 acres; slightly larger than the 500 acres required for a disposal site) on the ground. As illustrated above, the Siting Commission's GIS subcontractors then assigned each of the 47,224 grid cells a "favorability" score for each criterion. The process was systematic, but hardly objective, since the scores reflected social values (to borrow the term used by McHarg).

Overview of the raster approach, part 2.
Figure 9.13. Overview of the raster approach adopted by the New York LLRW Siting Commission, part two.
Credit:  Monmonier, 1995.

To acknowledge the fact that some criteria were more important than others, the Siting Commission weighted the scores in each data layer by multiplying them all by a constant factor. Like the original integer scores, the weighting factors were a negotiated product of consensus, not of objective measurement. Finally, the commission produced a single set of composite scores by summing the scores of each raster cell through all the data layers. A composite favorability map could then be produced from the composite scores. All that remained was for the public to embrace the result.