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Volumn 15, Issue 6, 1991, Pages 823-831

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

Author keywords

Artificial intelligence; Decision tree classifiers; Geographic information systems; Vegetation mapping

Indexed keywords

DECISION TREE; GIS; HILLY AREA; RULE INDUCTION; VEGETATION;

EID: 0026359465     PISSN: 0364152X     EISSN: 14321009     Source Type: Journal    
DOI: 10.1007/BF02394820     Document Type: Article
Times cited : (139)

References (17)
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    • 84935303138 scopus 로고    scopus 로고
    • Moore, D. M., B. G. Lees, and S. M. Davey. 1991. A new method for predicting vegetation distributions using decision tree analysis in a geographic information system. Environmental Management (in press).
  • 12
    • 84935303133 scopus 로고    scopus 로고
    • Spanner, M. A., A. H. Strahler, and J. E. Estes. 1983. Soil loss prediction in a geographic information system format. Proceedings, 17th international symposium on remote sensing of environment. Ann Arbor, Michigan, pp. 89–102.
  • 14
    • 84935303130 scopus 로고    scopus 로고
    • Strahler, A. H., T. L. Logan, and N. A. Bryant. 1978. Improving forest cover classification accuracy from Landsat by incorporating topographic information. Proceedings, 12th international symposium on remote sensing of environment. pp. 927–942, Ann Arbor, Michigan.
  • 15
    • 84935303131 scopus 로고    scopus 로고
    • Tunstall, B., B. A. Harrison, and D. L. B. Jupp. 1987. Incorporation of geographical data in the analysis of Landsat imagery for land-use mapping—a case example. Proceedings, 4th Australasian remote sensing conference. Adelaide, Australia, pp. 279–286.


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.