Human activities, such as military off-road vehicular traffic, disturb ground and vegetation cover of landscapes and increase potential rainfall related runoff and soil erosion. On military lands, soil erosion is of major concern in order to sustain training lands and thus there is a need for land condition maps for planning training activities and land management. In this study, we presented a conditional co-simulation algorithm to generate annual time series maps of soil erosion status from 1989 to 2001 for an army installation. The spatial variability and temporal dynamics of land condition were analyzed. This algorithm modeled soil erosion as realizations of a random function by combining a set of permanent plot data and Landsat Thematic Mapper (TM) images. In addition to estimation maps of soil erosion status, we obtained the maps of uncertainties including the variance of each pixel estimate and the probability of poor land condition. The results and maps are useful tools for land managers and decision-makers to guide military training programs and to generate management plans for sustaining training lands.
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