Artificial neural networks for land-cover classification and mapping
DL Civco - International journal of geographical information …, 1993 - Taylor & Francis
International journal of geographical information science, 1993•Taylor & Francis
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 …
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 …
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.