ABSTRACT
The combination of remote sensing and socioeconomic data layers in geographic information system (GIS) packages and models for humanenvironment research has become commonplace in the past two decades [1, 2]. The possibilities of integrating spatial data only arose as technology made it possible to process large data les in a common spatial framework. In the predigital era, similar work was performed through acetate overlays of multiple map layers. Early GIS packages such as IDRISI and ArcINFO opened up new areas for research and applied uses of data from multiple sources.
