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Proceedings Paper

Designing a generalized soil-adjusted vegetation index (GESAVI)
Author(s): M. A. Gilabert; Jose Gonzalez Piqueras; Joan Garcia-Haro; J. Melia
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Paper Abstract

Operational monitoring of vegetative cover by remote sensing currently involves the utilization of vegetation indices (VIs), most of them being functions of the reflectance in red (R) and near-infrared (NIR) spectral bands. A generalized soil-adjusted vegetation index (GESAVI), theoretically based on a simple vegetation canopy model, is introduced. It is defined in terms of the soil line parameters (A and B) as: GESAVI equals (NIR-BR-A)/(R + Z), where Z is related to the red reflectance at the cross point between the soil line and vegetation isolines. Z can be considered as a soil adjustment coefficient which let this new index be considered as belonging to the SAVI family. In order to analyze the GESAVI sensitivity to soil brightness and soil color, both high resolution reflectance data from two laboratory experiments and data obtained by applying a radiosity model to simulate heterogeneous vegetation canopy scenes were used. VIs (including GESAVI, NDVI, PVI and SAVI family VIs) were computed and their correlation with LAI for the different soil backgrounds was analyzed. Results confirmed the lower sensitivity of GESAVI to soil background in most of the cases, thus becoming the most efficient index. This good index performance results from the fact that the isolines in the NIR-R plane are neither parallel to the soil line (as required by the PVI) nor convergent at the origin (as required by the NDVI) but they converge somewhere between the origin and infinity in the region of negative values of both NIR and R. This convergence point is not necessarily situated on the bisectrix, as required by other SAVI family indices.

Paper Details

Date Published: 11 December 1998
PDF: 9 pages
Proc. SPIE 3499, Remote Sensing for Agriculture, Ecosystems, and Hydrology, (11 December 1998); doi: 10.1117/12.332774
Show Author Affiliations
M. A. Gilabert, Univ. de Valencia (Spain)
Jose Gonzalez Piqueras, Univ. de Valencia (Spain)
Joan Garcia-Haro, Univ. de Valencia (Spain)
J. Melia, Univ. de Valencia (Spain)


Published in SPIE Proceedings Vol. 3499:
Remote Sensing for Agriculture, Ecosystems, and Hydrology
Edwin T. Engman, Editor(s)

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