Remote Sensing of Soils in the Santa Monica Mountains: II. Hierarchical Foreground and Background Analysis

Hierarchical foreground and background analysis (HFBA) was used to discriminate soil properties from two valleys in the Santa Monica Mountains Recreation Area, California. The analysis was organized in two levels. First, spectral data from laboratory measured soil samples were used to train a vector...

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Bibliographic Details
Published in:Remote sensing of environment 1999-05, Vol.68 (2), p.138-151
Main Authors: Palacios-Orueta, Alicia, Pinzón, Jorge E., Ustin, Susan L., Roberts, Dar A.
Format: Article
Language:English
Subjects:
Applied geophysics
Earth sciences
Earth, ocean, space
Exact sciences and technology
Geographic information systems
Image analysis
Infrared spectrometers
Internal geophysics
Iron
Numerical methods
Organic compounds
Soils
Spectroscopy
Statistical methods
Surficial geology
Vegetation
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Summary:Hierarchical foreground and background analysis (HFBA) was used to discriminate soil properties from two valleys in the Santa Monica Mountains Recreation Area, California. The analysis was organized in two levels. First, spectral data from laboratory measured soil samples were used to train a vector in AVIRIS data for classifying the soils between valleys. The prediction of organic matter and iron contents is performed at a second level of resolution. Results showed that, in the laboratory, soils could be classified at a high level of accuracy. When applied to the image, the spatial predictions of organic matter and iron content were consistent for the first level of classification. The ranges of predicted organic matter and iron contents developed at the second level of classification were also consistent with the magnitude and distribution of field samples. The presence of vegetation and the steep terrain affect adversely the ability to resolve these soil properties.
ISSN:0034-4257
1879-0704
DOI:10.1016/S0034-4257(98)00106-0