Paper
26 March 1993 Evaluation of remote-sensing methods used to differentiate forested wetlands
Tommy L. Coleman, William H. Clerke, Wubishet Tadesse, Reginald S. Fletcher
Author Affiliations +
Abstract
Accurate assessment of forested wetlands is essential for forest managers in the development of management plans because these areas are considered unsuitable for timber production and therefore affect the allowable sale quantity of the forest. Three methods of quantifying wetland habitats using Thematic Mapper (TM) imagery were evaluated to determine the most effective method of assessing this forest resource. The methods of evaluating the TM imagery were the Kauth-Thomas transformation, principal component analysis (PCA), and a maximum likelihood supervised classification algorithm using TM bands 2, 3, 4, and 5. A summer and winter TM scene was used to allow for those areas that are seasonal and may be dry for periods of the year. The results of this study revealed that the maximum likelihood supervised classification using TM bands 2, 3, 4, and 5 was the most effective method of quantifying wetland habitats. However, this method was the most time consuming and required the user to have good ancillary data and skills in site selection and assessment of those signatures used as input into the algorithm.
© (1993) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Tommy L. Coleman, William H. Clerke, Wubishet Tadesse, and Reginald S. Fletcher "Evaluation of remote-sensing methods used to differentiate forested wetlands", Proc. SPIE 1819, Digital Image Processing and Visual Communications Technologies in the Earth and Atmospheric Sciences II, (26 March 1993); https://doi.org/10.1117/12.142190
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Cited by 1 scholarly publication.
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KEYWORDS
Principal component analysis

Vegetation

Agriculture

Error analysis

Image classification

Infrared photography

Remote sensing

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