Vegetation Index Methods for Estimating Evapotranspiration by Remote Sensing

Glenn, EP; Nagler, PL; Huete, AR

Vegetation Index Methods for Estimating Evapotranspiration by Remote Sensing

Glenn, EP Nagler, PL Huete, AR

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Publication Type:: Journal Article
Citation:: Surveys in Geophysics, 2010, 31 (6), pp. 531 - 555
Issue Date:: 2010-12-01

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Field	Value	Language
dc.contributor.author	Glenn, EP	en_US
dc.contributor.author	Nagler, PL	en_US
dc.contributor.author	Huete, AR https://orcid.org/0000-0003-2809-2376	en_US
dc.date.issued	2010-12-01	en_US
dc.identifier.citation	Surveys in Geophysics, 2010, 31 (6), pp. 531 - 555	en_US
dc.identifier.issn	0169-3298	en_US
dc.identifier.uri	http://hdl.handle.net/10453/14742
dc.description.abstract	Evapotranspiration (ET) is the largest term after precipitation in terrestrial water budgets. Accurate estimates of ET are needed for numerous agricultural and natural resource management tasks and to project changes in hydrological cycles due to potential climate change. We explore recent methods that combine vegetation indices (VI) from satellites with ground measurements of actual ET (ETa) and meteorological data to project ETa over a wide range of biome types and scales of measurement, from local to global estimates. The majority of these use time-series imagery from the Moderate Resolution Imaging Spectrometer on the Terra satellite to project ET over seasons and years. The review explores the theoretical basis for the methods, the types of ancillary data needed, and their accuracy and limitations. Coefficients of determination between modeled ETa and measured ETa are in the range of 0.45-0.95, and root mean square errors are in the range of 10-30% of mean ETa values across biomes, similar to methods that use thermal infrared bands to estimate ETa and within the range of accuracy of the ground measurements by which they are calibrated or validated. The advent of frequent-return satellites such as Terra and planed replacement platforms, and the increasing number of moisture and carbon flux tower sites over the globe, have made these methods feasible. Examples of operational algorithms for ET in agricultural and natural ecosystems are presented. The goal of the review is to enable potential end-users from different disciplines to adapt these methods to new applications that require spatially-distributed ET estimates. © 2010 Springer Science+Business Media B.V.	en_US
dc.relation.ispartof	Surveys in Geophysics	en_US
dc.relation.isbasedon	10.1007/s10712-010-9102-2	en_US
dc.subject.classification	Meteorology & Atmospheric Sciences	en_US
dc.title	Vegetation Index Methods for Estimating Evapotranspiration by Remote Sensing	en_US
dc.type	Journal Article
utslib.citation.volume	6	en_US
utslib.citation.volume	31	en_US
utslib.for	0705 Forestry Sciences	en_US
utslib.for	0201 Astronomical and Space Sciences	en_US
utslib.for	0404 Geophysics	en_US
dc.location.activity	Hanoi, Vietnam
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	6	en_US
pubs.publication-status	Published	en_US
pubs.volume	31	en_US

Abstract:

Evapotranspiration (ET) is the largest term after precipitation in terrestrial water budgets. Accurate estimates of ET are needed for numerous agricultural and natural resource management tasks and to project changes in hydrological cycles due to potential climate change. We explore recent methods that combine vegetation indices (VI) from satellites with ground measurements of actual ET (ETa) and meteorological data to project ETa over a wide range of biome types and scales of measurement, from local to global estimates. The majority of these use time-series imagery from the Moderate Resolution Imaging Spectrometer on the Terra satellite to project ET over seasons and years. The review explores the theoretical basis for the methods, the types of ancillary data needed, and their accuracy and limitations. Coefficients of determination between modeled ETa and measured ETa are in the range of 0.45-0.95, and root mean square errors are in the range of 10-30% of mean ETa values across biomes, similar to methods that use thermal infrared bands to estimate ETa and within the range of accuracy of the ground measurements by which they are calibrated or validated. The advent of frequent-return satellites such as Terra and planed replacement platforms, and the increasing number of moisture and carbon flux tower sites over the globe, have made these methods feasible. Examples of operational algorithms for ET in agricultural and natural ecosystems are presented. The goal of the review is to enable potential end-users from different disciplines to adapt these methods to new applications that require spatially-distributed ET estimates. © 2010 Springer Science+Business Media B.V.

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http://hdl.handle.net/10453/14742