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A comparison of false color composites in mapping and discriminating between salt-affected soils in Kings County, California

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https://ir.library.oregonstate.edu/concern/graduate_projects/r207tq08j

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  • Spectral profiles, transformed divergence values, and feature space derived from Landsat Thematic Mapper (TM) data were used to analyze the ability of four false color composites to discriminate between different classes of salt-affected soils. To compare the spatial distribution of salt-affected soil classes, maps were generated for each false color composite using the maximum likelihood classification algorithm applied to training data from the Landsat TM image. Soil samples were collected and analyzed to correlate brightness values from Landsat data with surface soil characteristics. Few differences occurred in the number of pixels assigned to each class among the four false color composites. Based on signature separability data, no false color composite provided an overall improvement in discriminating between salt-affected soil classes. Poor separability occurred in the western portion of the study area between several classes: saline and salinesodic; sandy soils and saline soils; sandy soils and saline-sodic soils; and between nonsaline and sodic soils. Greater separability between classes occurred in the eastern portion of the study area. The low discrimination between several soil types and salt-affected soils using remote sensing data illustrates the challenges in mapping salt-affected soils.
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