Artificial neural networks for land-cover classification and mapping

Abstract Abstract. Artificial intelligence approaches toward image processing and pattern recognition are perceived as an alternative to, and an improvement over, traditional statistically-based procedures. Of particular interest to the satellite remote sensing community are artificial neural networks. This article describes the application of such an approach to the problem of deriving land-cover information from Landsat satellite Thematic Mapper (TM) digital imagery. The techniques being developed are ones that will provide more accurate and useful data for use with geographical information systems.