Abstract
A method for using coarse resolution data from wildlife survey to classify a Landsat Thematic Mapper image and digital elevation model (DEM) is described. Classification is based on an analytical Bayesian probability method implemented within a GIS and is illustrated using a case study of Curlew in part of the Grampian Region, northeast Scotland, United Kingdom. Conditional probabilities for Curlew presence and absence are calculated for spectral values in the image bands and DEM. The conditional probabilities are then used to classify the image in conjunction with the DEM. The product of this analysis is a detailed map («information surface») at the spatial resolution of the satellite image that describes the distribution of the specified species as probability of occurence
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