Identification of the factors involved in deforestation could lead to a comprehensive understanding of deforestation on a broad scale, as well as a prediction capability. Tanaka and Nishii [7, 8] explored regression models with two explanatory variables - human population density (N) and relief energy (R), i.e., the difference between the maximum and minimum altitudes in a sampled area- as to whether they could elucidate aspects of deforestation. As relative appropriateness of the models, Akaike's Information Criterion was used to evaluate the models on real data. Although they suceeded in identifying the fuctional form of g(N) in Asian four test areas, the topographic term h(R) remained intact in terms of alternative possible variable forms. In this research, detailed verifications of the topographic feature were employed, and it was revealed that addition of mean altitude on the same cell will give great improvement to the model.