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Forestry information content of Thematic Mapper data
284
Citations
14
References
1986
Year
Environmental MonitoringEngineeringForest BiometricsForestryLand CoverLeaf Moisture ContentSocial SciencesData ScienceBiogeographyCartographyGeographyForest Health MonitoringHyperspectral ImagingLand Cover MapDeforestationClimatologyThematic MapperRemote SensingForestry Information ContentForest InventoryPrincipal Components
Abstract This paper provides an initial investigation of the spectroradiometric data structure and information content of Thematic Mapper (TM) data for some Canadian forest-cover types. The Dryden-Lac Seul region in western Ontario is an important commercial and tourist area containing mainly boreal forest. A LANDSAT-4 TM scene of this region was analysed in conjunction with a considerable amount of ancillary data. The data were reduced to a manageable volume by selectingsubscenes;a preliminary attempt at atmospheric correction and radiometric calibration was then carried out; polygons representing a wide variety of cover classes were defined and, finally, the spectroradiometric information available for class discrimination was analysed using several techniques. Principal component analysis and feature selection reveal that the spectral data can be reduced to three eigenvectors with a loss of less than 10 per cent of the scene variance, and that the best three TM bands perform almost as wellas the first three principal components; for general cover-type discrimination, these bands areTM 3,4 and 5.TM bands 1,4 and 5 are marginally better for separating a set of softwood classes, although TM I has a very small dynamic range. The shortwave infrared (SWIR) spectral region, represented byTM bands 5and 7, seems to be particularly sensitive to forest vegetation density, especially in the early stages of clearcut regeneration. Shadowing is suggested as a factor at least as important as leaf moisture content in influencingthe spectral reflectanceof forests in this region. The first three principal components are related to the scene brightness (PC I), greenness (PC 2) and the contrast between the SWIR and the visible and near-infrared regions. We propose the name 'swirness' for the third component until a more complete understanding of its properties is achieved.
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