Linearization of NDVI based on its relationship with vegetation fraction

Jiang, Z; Huete, A

Linearization of NDVI based on its relationship with vegetation fraction

Jiang, Z Huete, A

Permalink

Publisher:: ASPRS
Publication Type:: Journal Article
Citation:: Photogrammetry Engineering & Remote Sensing, 2010, 76 (8), pp. 545 - 561
Issue Date:: 2010-01

Closed Access

	Filename	Description	Size
	2010000712OK.pdf		2.52 MB	Adobe PDF	View/Open

Copyright Clearance Process

Recently Added
In Progress
Closed Access

This item is closed access and not available.

Full metadata record

Field	Value	Language
dc.contributor.author	Jiang, Z	en_US
dc.contributor.author	Huete, A https://orcid.org/0000-0003-2809-2376	en_US
dc.date.issued	2010-01	en_US
dc.identifier.citation	Photogrammetry Engineering & Remote Sensing, 2010, 76 (8), pp. 545 - 561	en_US
dc.identifier.issn	0099-1112	en_US
dc.identifier.uri	http://hdl.handle.net/10453/14713
dc.description.abstract	The Normalized Difference Vegetation Index (NDVI) is widely used for global monitoring of land surface vegetation dynamics from space. However, it is well documented that the NDVI approaches saturation asymptotically over highly vegetated areas. In this study, a linearized NDVI (LNDVI) is derived by introducing a linearity-adjustment factor, beta, into the NDVI equation to improve the linearity of the relationship with vegetation fraction and mitigate the saturation problem encountered by NDVI. The linearity of the LNDVI is demonstrated using a ground-observed data set and a model-simulated data set. A functional relationship and consistence of LNDVI with other NDVI adaptations are found, providing independent justification of the value of the NDVI adaptations. Due to its improved linearity with vegetation fraction, this index would provide more accurate monitoring of vegetation dynamics and estimation of biophysical parameters. The LNDVI can be derived from historical NDVI datasets directly without knowledge of input reflectances.	en_US
dc.publisher	ASPRS	en_US
dc.relation.ispartof	Photogrammetry Engineering & Remote Sensing	en_US
dc.subject.classification	Geological & Geomatics Engineering	en_US
dc.title	Linearization of NDVI based on its relationship with vegetation fraction	en_US
dc.type	Journal Article
utslib.citation.volume	8	en_US
utslib.citation.volume	76	en_US
utslib.for	0909 Geomatic Engineering	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	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.consider-herdc	false	en_US
pubs.issue	8	en_US
pubs.volume	76	en_US

Abstract:

The Normalized Difference Vegetation Index (NDVI) is widely used for global monitoring of land surface vegetation dynamics from space. However, it is well documented that the NDVI approaches saturation asymptotically over highly vegetated areas. In this study, a linearized NDVI (LNDVI) is derived by introducing a linearity-adjustment factor, beta, into the NDVI equation to improve the linearity of the relationship with vegetation fraction and mitigate the saturation problem encountered by NDVI. The linearity of the LNDVI is demonstrated using a ground-observed data set and a model-simulated data set. A functional relationship and consistence of LNDVI with other NDVI adaptations are found, providing independent justification of the value of the NDVI adaptations. Due to its improved linearity with vegetation fraction, this index would provide more accurate monitoring of vegetation dynamics and estimation of biophysical parameters. The LNDVI can be derived from historical NDVI datasets directly without knowledge of input reflectances.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/14713