An integrated algorithm for estimating regional latent heat flux and daily evapotranspiration

Zhang, Y; Liu, C; Lei, Y; Tang, Y; Yu, Q; Shen, Y; Sun, H

An integrated algorithm for estimating regional latent heat flux and daily evapotranspiration

Zhang, Y Liu, C Lei, Y Tang, Y Yu, Q

Shen, Y Sun, H

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Publication Type:: Journal Article
Citation:: International Journal of Remote Sensing, 2006, 27 (1), pp. 129 - 152
Issue Date:: 2006-01-10

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Field	Value	Language
dc.contributor.author	Zhang, Y	en_US
dc.contributor.author	Liu, C	en_US
dc.contributor.author	Lei, Y	en_US
dc.contributor.author	Tang, Y	en_US
dc.contributor.author	Yu, Q https://orcid.org/0000-0001-6950-1821	en_US
dc.contributor.author	Shen, Y	en_US
dc.contributor.author	Sun, H	en_US
dc.date.issued	2006-01-10	en_US
dc.identifier.citation	International Journal of Remote Sensing, 2006, 27 (1), pp. 129 - 152	en_US
dc.identifier.issn	0143-1161	en_US
dc.identifier.uri	http://hdl.handle.net/10453/14738
dc.description.abstract	Using remote-sensing data and ground-based data, we constructed an integrated algorithm for estimating regional surface latent heat flux (LE) and daily evapotranspiration (ETd). In the algorithm, we first used trapezoidal diagrams relating the surface temperature and fractional vegetation cover (fc) to calculate the surface temperature-vegetation cover index, a land surface moisture index with a range from 0.0 to 1.0. We then revised a sine function to assess ETd from LE estimated for the satellite's overpass time. The algorithm was applied to farmland in the North China Plain using Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper Plus (ETM+) data and synchronous surface-observed data as inputs. The estimated LE and ETd were tested against measured data from a Bowen Ratio Energy Balance (BREB) system and a large-scale weighing lysimeter, respectively. The algorithm estimated LE with a root mean square error (RMSE) of 50.1 W m-2 as compared to measurements with the BREB System, and ETd with an RMSE of 0.93 mm d-1 as compared with the measurement by the lysimeter. Sensitivity analysis showed that changing meteorological variables have some influence on LE, while variation of fc has little effect on LE. The test of the model in the study indicated that the improved algorithm provides an accurate and easy-to-handle approach for assessing regional surface LE and ETd. Further improvement can be achieved in the assessments if we increase the accuracy of some key parameters on a large regional scale, such as the minimum stomatal conductance and the atmospheric vapour pressure deficit. © 2006 Taylor & Francis.	en_US
dc.relation.ispartof	International Journal of Remote Sensing	en_US
dc.relation.isbasedon	10.1080/01431160500159743	en_US
dc.subject.classification	Geological & Geomatics Engineering	en_US
dc.title	An integrated algorithm for estimating regional latent heat flux and daily evapotranspiration	en_US
dc.type	Journal Article
utslib.citation.volume	1	en_US
utslib.citation.volume	27	en_US
utslib.for	0406 Physical Geography and Environmental Geoscience	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
utslib.copyright.status	closed_access
pubs.issue	1	en_US
pubs.publication-status	Published	en_US
pubs.volume	27	en_US

Abstract:

Using remote-sensing data and ground-based data, we constructed an integrated algorithm for estimating regional surface latent heat flux (LE) and daily evapotranspiration (ETd). In the algorithm, we first used trapezoidal diagrams relating the surface temperature and fractional vegetation cover (fc) to calculate the surface temperature-vegetation cover index, a land surface moisture index with a range from 0.0 to 1.0. We then revised a sine function to assess ETd from LE estimated for the satellite's overpass time. The algorithm was applied to farmland in the North China Plain using Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper Plus (ETM+) data and synchronous surface-observed data as inputs. The estimated LE and ETd were tested against measured data from a Bowen Ratio Energy Balance (BREB) system and a large-scale weighing lysimeter, respectively. The algorithm estimated LE with a root mean square error (RMSE) of 50.1 W m-2 as compared to measurements with the BREB System, and ETd with an RMSE of 0.93 mm d-1 as compared with the measurement by the lysimeter. Sensitivity analysis showed that changing meteorological variables have some influence on LE, while variation of fc has little effect on LE. The test of the model in the study indicated that the improved algorithm provides an accurate and easy-to-handle approach for assessing regional surface LE and ETd. Further improvement can be achieved in the assessments if we increase the accuracy of some key parameters on a large regional scale, such as the minimum stomatal conductance and the atmospheric vapour pressure deficit. © 2006 Taylor & Francis.

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http://hdl.handle.net/10453/14738