IMAGE PROCESSING FOR SURVEYING NATURAL VEGETATION: POSSIBLE EFFECTS ON CLASSIFICATION ACCURACY.

Stephen R. Yool, David W. Eckhardt, Jeffrey L. Star, Tasha L. Becking, John E. Estes

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Tests of data processing approaches using Landsat data from a complex forested scene in California show the relative performance of ratioing, filtering and principal components approaches. Untransformed channels appear to perform best overall. Performances for untransformed, ratioed and the principal components of Landsat data channels are comparable for forest classes having complete cover. Filtered Landsat dta channels performed poorest overall, but perform best on select forest classes. Performance variability appears to be related to variations in background reflectance, surface illumination and spatial pattern by class.

Original languageEnglish (US)
Title of host publicationTechnical Papers of the American Society of Photogrammetry, Annual Meeting
PublisherAmerican Soc of Photogrammetry
Pages595-603
Number of pages9
ISBN (Print)0937294640
StatePublished - Jan 1 1985

Publication series

NameTechnical Papers of the American Society of Photogrammetry, Annual Meeting
Volume2

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Yool, S. R., Eckhardt, D. W., Star, J. L., Becking, T. L., & Estes, J. E. (1985). IMAGE PROCESSING FOR SURVEYING NATURAL VEGETATION: POSSIBLE EFFECTS ON CLASSIFICATION ACCURACY. In Technical Papers of the American Society of Photogrammetry, Annual Meeting (pp. 595-603). (Technical Papers of the American Society of Photogrammetry, Annual Meeting; Vol. 2). American Soc of Photogrammetry.