Deforestation due to population and relief energy through spatially-correlated logit models

Deforestation is a result of complex causality chains in most cases. But identification of limited number of factors shall provide comprehensive general understanding of the vital phenomenon at broad scale, as well as projection for the future. Only two factors - human population and relief energy (difference of minimum altitude from the maximum in a sampled area) - were found to give sufficient elucidation of deforestation by a regression model, whose functional forms were verified by linear combinations of dummy variables firstly explored with use of Japanese data. Likelihood with spatial dependency was derived and applied then to East-Asian data, with which our models showed the eminently good relative appropriateness to the real data.