James D. Wickham

A note on contagion indices for landscape analysis

The landscape contagion index measures the degree of clumping of attributes on raster maps. The index is computed from the frequencies by which different pairs of attributes occur as adjacent pixels on a map. Because there are subtle differences in the way the attribute adjacencies may be tabulated, the standard index formula may not always apply, and published index values may not be comparable. This paper derives formulas for the contagion index that apply for different ways of tabulating attribute adjacencies — with and without preserving the order of pixels in pairs, and by using two different ways of determining pixel adjacency. When the order of pixels in pairs is preserved, the standard formula is obtained. When the order is not preserved, a new formula is obtained because the number of possible attribute adjacency states is smaller. Estimated contagion is also smaller when each pixel pair is counted twice (instead of once) because double-counting pixel adjacencies makes the attribute adjacency matrix symmetric across the main diagonal.

DESERTIFICATION EVALUATED USING AN INTEGRATED ENVIRONMENTAL ASSESSMENT MODEL

Desertification has been defined as land degradation in arid, semi-arid and dry sub-humid areas resulting from various factors, including climatic variations and human activities (United Nations, 1992). A technique for identifying and assessing areas at risk fordesertification in the arid, semi-arid, and subhumid regionsof the United States was developed by the Desert Research Institute and the U.S. Environmental Protection Agency (EPA), using selected environmental indicators integrated into a Geographic Information System (GIS). Five indicators were selected: potential erosion, grazing pressure, climatic stress (expressed as a function of changesin the Palmer Drought Severity Index [PDSI]), change invegetation greenness (derived from the Normalized DifferenceVegetation Index [NDVI]), and weedy invasives as a percentof total plant cover. The data were integrated over aregional geographic setting using a GIS, which facilitateddata display, development and exploration of data relationships, including manipulation and simulation testing. By combining all five data layers, landscapes having a varying risk for land degradation were identified, providing a tool which could be used to improve landmanagement efficiency.