A modified soil adjusted vegetation index

Qi, J; Chehbouni, A; Huete, AR; Kerr, YH; Sorooshian, S

A modified soil adjusted vegetation index

Qi, J Chehbouni, A Huete, AR

Kerr, YH Sorooshian, S

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Publication Type:: Journal Article
Citation:: Remote Sensing of Environment, 1994, 48 (2), pp. 119 - 126
Issue Date:: 1994-01-01

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Field	Value	Language
dc.contributor.author	Qi, J	en_US
dc.contributor.author	Chehbouni, A	en_US
dc.contributor.author	Huete, AR https://orcid.org/0000-0003-2809-2376	en_US
dc.contributor.author	Kerr, YH	en_US
dc.contributor.author	Sorooshian, S	en_US
dc.date.issued	1994-01-01	en_US
dc.identifier.citation	Remote Sensing of Environment, 1994, 48 (2), pp. 119 - 126	en_US
dc.identifier.issn	0034-4257	en_US
dc.identifier.uri	http://hdl.handle.net/10453/13568
dc.description.abstract	There is currently a great deal of interest in the quantitative characterization of temporal and spatial vegetation patterns with remotely sensed data for the study of earth system science and global change. Spectral models and indices are being developed to improve vegetation sensitivity by accounting for atmosphere and soil effects. The soil-adjusted vegetation index (SAVI) was developed to minimize soil influences on canopy spectra by incorporating a soil adjustment factor L into the denominator of the normalized difference vegetation index (NDVI) equation. For optimal adjustment of the soil effect, however, the L factor should vary inversely with the amount of vegetation present. A modified SAVI (MSAVI) that replaces the constant L in the SAVI equation with a variable L function is presented in this article. The L function may be derived by induction or by using the product of the NDVI and weighted difference vegetation index (WDVI). Results based on ground and aircraft-measured cotton canopies are presented. The MSAVI is shown to increase the dynamic range of the vegetation signal while further minimizing the soil background influences, resulting in greater vegetation sensitivity as defined by a "vegetation signal" to "soil noise" ratio. © 1994.	en_US
dc.relation.ispartof	Remote Sensing of Environment	en_US
dc.relation.isbasedon	10.1016/0034-4257(94)90134-1	en_US
dc.subject.classification	Geological & Geomatics Engineering	en_US
dc.title	A modified soil adjusted vegetation index	en_US
dc.type	Journal Article
utslib.citation.volume	2	en_US
utslib.citation.volume	48	en_US
utslib.for	0909 Geomatic Engineering	en_US
utslib.for	0406 Physical Geography and Environmental Geoscience	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Life Sciences
pubs.organisational-group	/University of Technology Sydney/Strength - CAMGIS - Centre for Advanced Modelling and Geospatial lnformation Systems
utslib.copyright.status	closed_access
pubs.issue	2	en_US
pubs.publication-status	Published	en_US
pubs.volume	48	en_US

Abstract:

There is currently a great deal of interest in the quantitative characterization of temporal and spatial vegetation patterns with remotely sensed data for the study of earth system science and global change. Spectral models and indices are being developed to improve vegetation sensitivity by accounting for atmosphere and soil effects. The soil-adjusted vegetation index (SAVI) was developed to minimize soil influences on canopy spectra by incorporating a soil adjustment factor L into the denominator of the normalized difference vegetation index (NDVI) equation. For optimal adjustment of the soil effect, however, the L factor should vary inversely with the amount of vegetation present. A modified SAVI (MSAVI) that replaces the constant L in the SAVI equation with a variable L function is presented in this article. The L function may be derived by induction or by using the product of the NDVI and weighted difference vegetation index (WDVI). Results based on ground and aircraft-measured cotton canopies are presented. The MSAVI is shown to increase the dynamic range of the vegetation signal while further minimizing the soil background influences, resulting in greater vegetation sensitivity as defined by a "vegetation signal" to "soil noise" ratio. © 1994.

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http://hdl.handle.net/10453/13568