Effective usable area is a key parameter in land acquisition and afforestation planning. The purpose of this research was to generate predictive maps of areas suitable for planting eucalyptus trees using binary logistic regressions and geomorphometric variables. The relationships between the predicting variables and suitable areas for planting eucalyptus trees were modeled and the variable that best explained occurrence of suitable lands was distance from rivers. The generated map showing areas suitable for planting had a high ability to reproduce the original planting map. Logistic regressions demonstrated the feasibility of use this approach to map suitability for eucalyptus forestation.
afforestation; GIS; data mining
