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Remote Sens. 2009, 1(4), 842-857;

Derivation of Soil Line Influence on Two-Band Vegetation Indices and Vegetation Isolines

Department of Information Science and Technology, Aichi Prefectural University, 1522-3 Kumabari, Nagakute, Aichi 480-1198, Japan
Department of Natural Resources and Environmental Management, College of Tropical Agriculture and Human Resources, University of Hawaii at Manoa, 1910 East-West Road, Honolulu, HI 96822, USA
Department of Soil Science, University of São Paulo, Av. Pádua Dias, 11, Piracicaba, São Paulo, Brazil
Natural Resources Conservation Service, USDA, 355 East Hancock Avenue, Athens, GA 30601, USA
Department of Soil, Water and Environmental Science, University of Arizona, 1177 East Fourth Street, Tucson, AZ 85721, USA
Author to whom correspondence should be addressed.
Received: 3 September 2009 / Revised: 16 October 2009 / Accepted: 27 October 2009 / Published: 3 November 2009
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This paper introduces derivations of soil line influences on two-band vegetation indices (VIs) and vegetation isolines in the red and near infra-red reflectance space. Soil line variations are described as changes in the soil line parameters (slope and offset) and the red reflectance of the soil surface. A general form of a VI model equation written as a ratio of two linear functions (e.g., NDVI and SAVI) was assumed. It was found that relative VI variations can be approximated by a linear combination of the three soil parameters. The derived expressions imply the possibility of estimating and correcting for soil-induced bias errors in VIs and their derived biophysical parameters, caused by the assumption of a general soil line, through the use of external data sources such as regional soil maps. View Full-Text
Keywords: spectral vegetation index; soil noise; soil line; vegetation isoline spectral vegetation index; soil noise; soil line; vegetation isoline

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Yoshioka, H.; Miura, T.; Demattê, J.A.M.; Batchily, K.; Huete, A.R. Derivation of Soil Line Influence on Two-Band Vegetation Indices and Vegetation Isolines. Remote Sens. 2009, 1, 842-857.

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