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Predicting Common Crupina Habitat With Geographic And Remote Sensing Data, Timothy S. Prather, Bahman Shafii, Robert H. Callihan

Conference on Applied Statistics in Agriculture

Field surveys for common crupina, as part of an eradication program, are time intensive and could be made more efficient if common crupina habitat could be predicted. Slope, aspect, and vegetation data were used as generalized plant community variables to predict common crupina habitat using a transformed logistic regression. Models were constructed using either aspect or slope as an explanatory variable such that one model predicted the overall effect of either slope or aspect and a set of models predicted the effect of slope or aspect at each of three vegetation classes. A second data set was used to validate …