An analysis of angle-based with ratio-based vegetation indices

Jiang, Z; Huete, AR; Li, J; Chen, Y

An analysis of angle-based with ratio-based vegetation indices

Jiang, Z Huete, AR

Li, J Chen, Y

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Publication Type:: Journal Article
Citation:: IEEE Transactions on Geoscience and Remote Sensing, 2006, 44 (9), pp. 2506 - 2513
Issue Date:: 2006-09-01

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Field	Value	Language
dc.contributor.author	Jiang, Z	en_US
dc.contributor.author	Huete, AR https://orcid.org/0000-0003-2809-2376	en_US
dc.contributor.author	Li, J	en_US
dc.contributor.author	Chen, Y	en_US
dc.date.issued	2006-09-01	en_US
dc.identifier.citation	IEEE Transactions on Geoscience and Remote Sensing, 2006, 44 (9), pp. 2506 - 2513	en_US
dc.identifier.issn	0196-2892	en_US
dc.identifier.uri	http://hdl.handle.net/10453/9288
dc.description.abstract	Remotely sensed, angle-based vegetation indices that measure vegetation amounts by the angle between an approximated soil line and a simulated vegetation isoline in the rednear-infrared reflectance space were developed and evaluated in this paper. Ünsalan and Boyer previously proposed an angle-based vegetation index, 0 (denoted as 0NDVI in this paper), based on the normalized difference vegetation index (NDVI) with the objective of overcoming the saturation problem in the NDVI. However, θNDVI did not consider strong soil background influences present in the NDVI. To reduce soil background noise, an angle-based vegetation index, θSAVI, based on the soil-adjusted vegetation index (SAVI), was derived using trigonometric analysis. The performance of θNDVI and θSAVI was evaluated and compared with their corresponding vegetation indices, NDVI and SAVI. The soil background influence on θNDVI was found to be as significant as that on the NDVI. θNDVI was found to be more sensitive to vegetation amount than the NDVI at low vegetation density levels, but less sensitive to vegetation fraction at high vegetation density levels. Thus, the saturation effect at high vegetation density levels encountered in the NDVI was not mitigated by θNDVI. By contrast, θSAVI exhibited insignificant soil background effects and weaker saturation, as in SAVI, but also improved upon the dynamic range of SAVI. Analyses and evaluation suggest that θSAVI is an optimal vegetation index to assess and monitor vegetation cover across the entire range of vegetation fraction density levels and over a wide variety of soil backgrounds. © 2006 IEEE.	en_US
dc.relation.ispartof	IEEE Transactions on Geoscience and Remote Sensing	en_US
dc.relation.isbasedon	10.1109/TGRS.2006.873205	en_US
dc.subject.classification	Geological & Geomatics Engineering	en_US
dc.title	An analysis of angle-based with ratio-based vegetation indices	en_US
dc.type	Journal Article
utslib.citation.volume	9	en_US
utslib.citation.volume	44	en_US
utslib.for	0404 Geophysics	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
utslib.for	0909 Geomatic Engineering	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	9	en_US
pubs.publication-status	Published	en_US
pubs.volume	44	en_US

Abstract:

Remotely sensed, angle-based vegetation indices that measure vegetation amounts by the angle between an approximated soil line and a simulated vegetation isoline in the rednear-infrared reflectance space were developed and evaluated in this paper. Ünsalan and Boyer previously proposed an angle-based vegetation index, 0 (denoted as 0NDVI in this paper), based on the normalized difference vegetation index (NDVI) with the objective of overcoming the saturation problem in the NDVI. However, θNDVI did not consider strong soil background influences present in the NDVI. To reduce soil background noise, an angle-based vegetation index, θSAVI, based on the soil-adjusted vegetation index (SAVI), was derived using trigonometric analysis. The performance of θNDVI and θSAVI was evaluated and compared with their corresponding vegetation indices, NDVI and SAVI. The soil background influence on θNDVI was found to be as significant as that on the NDVI. θNDVI was found to be more sensitive to vegetation amount than the NDVI at low vegetation density levels, but less sensitive to vegetation fraction at high vegetation density levels. Thus, the saturation effect at high vegetation density levels encountered in the NDVI was not mitigated by θNDVI. By contrast, θSAVI exhibited insignificant soil background effects and weaker saturation, as in SAVI, but also improved upon the dynamic range of SAVI. Analyses and evaluation suggest that θSAVI is an optimal vegetation index to assess and monitor vegetation cover across the entire range of vegetation fraction density levels and over a wide variety of soil backgrounds. © 2006 IEEE.

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http://hdl.handle.net/10453/9288