Landsat TM versus MSS data for forest type identification |
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| Authors: | David L Evans John M Hill |
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| Institution: | 1. USDA Forest Service Southern Forest Experiment Station , Forestry Sciences Laboratory , P. O. Box 906, Starkville, MS, 39759, U.S.A;2. RS/GIS Laboratory , HARC/Space Technology Research Center , 4802 Research Forest Drive, The Woodlands, TX, 77381, U.S.A |
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| Abstract: | Landsat Thematic Mapper (TM) and Multispectral Scanner (MSS) data were digitally analyzed for forest type identification in the Kisatchie Ranger District, Kisatchie National Forest, Louisiana. Ground‐verification maps were produced from field surveys and interpretation of 1.12,000 and 1: 58,000 color‐infrared (CIR) aerial photography of nine compartments. Stand boundary and soils maps were input to a digital Geographic Information System (GIS) with the Landsat and ground‐verification data. ‐ Unsupervised classifications of the Landsat data did not identify the above cover types well. Supervised classifications were tested by stand agreement to the ground verification. The highest four‐class agreement was obtained for the TM classification (76 percent). Three‐class (open, pine, and hardwoods) stand agreements (81 (MSS) and 85 (TM) percent) were not significantly different as tested by analysis of variance (alpha level 0.1). |
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