Environmental Management

, Volume 15, Issue 6, pp 823–831

Decision-tree and rule-induction approach to integration of remotely sensed and GIS data in mapping vegetation in disturbed or hilly environments

Authors

  • Brian G. Lees
    • Department of Geography School of Resource & Environmental Management Faculty of ScienceAustralian National University
  • Kim Ritman
    • Department of Geography School of Resource & Environmental Management Faculty of ScienceAustralian National University
Research

DOI: 10.1007/BF02394820

Cite this article as:
Lees, B.G. & Ritman, K. Environmental Management (1991) 15: 823. doi:10.1007/BF02394820

Abstract

The integration of Landsat TM and environmental GIS data sets using artificial intelligence rule-induction and decision-tree analysis is shown to facilitate the production of vegetation maps with both floristic and structural information. This technique is particularly suited to vegetation mapping in disturbed or hilly environments that are unsuited to either conventional remote sensing methods or GIS modeling using environmental data bases.

Key words

Vegetation mappingGeographic information systemsDecision-tree classifiersArtificial intelligence

Copyright information

© Springer-Verlag New York Inc. 1991