Hepinstall, J.A. and S.A. Sader. 1997. Using bayesian statistics, thematic mapper satellite imagery and breeding bird survey data to model bird species probability of occurrence in Maine. Photogrammetric Engineering and Remote Sensing 63(10):1321-37.

A Bayesian modeling technique was used to predict probability of occurrence for 14 species of Maine land birds. The relationships between bird species survey data and the spectral values of Landsat-Thematic Mapper bands 4 and 5 as well as a derived texture measure were used to build conditional probabilities for input into Bayes' Theorem. The conditional probabilities form decision rules for reclassifying the input spectral data into probability of occurrence estimates with associated estimates of error inherent in the model prediction. This methodology removed the costly and time-consuming step of creating a habitat map before modeling species occurrence. The output resolution of the species predictions is not degraded from the original 30-m TM pixel size to the coarse resolution of the wildlife survey data. Model results can be compared to results from other habitat modeling techniques and used by natural resource managers to predict the effects of land use changes on available habitat.

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