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Use of topographic and climatological models in a geographical data base to improve Landsat MSS classification for Olympic National ParkAn unsupervised computer classification of vegetation/landcover of Olympic National Park and surrounding environs was initially carried out using four bands of Landsat MSS data. The primary objective of the project was to derive a level of landcover classifications useful for park management applications while maintaining an acceptably high level of classification accuracy. Initially, nine generalized vegetation/landcover classes were derived. Overall classification accuracy was 91.7 percent. In an attempt to refine the level of classification, a geographic information system (GIS) approach was employed. Topographic data and watershed boundaries (inferred precipitation/temperature) data were registered with the Landsat MSS data. The resultant boolean operations yielded 21 vegetation/landcover classes while maintaining the same level of classification accuracy. The final classification provided much better identification and location of the major forest types within the park at the same high level of accuracy, and these met the project objective. This classification could now become inputs into a GIS system to help provide answers to park management coupled with other ancillary data programs such as fire management.
Document ID
Document Type
Reprint (Version printed in journal)
Cibula, William G. (NASA National Space Technology Laboratories Bay St. Louis, MS, United States)
Nyquist, Maurice O. (National Park Service, Geographic Information Systems Field Unit, Denver CO, United States)
Date Acquired
August 13, 2013
Publication Date
January 1, 1987
Publication Information
Publication: Photogrammetric Engineering and Remote Sensing
Volume: 53
ISSN: 0099-1112
Subject Category
Distribution Limits