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Proceedings Paper

Regional evapotranspiration estimation using SEBAL model with remotely sensed data in Guanzhong Plain and Weibei Tablelands
Author(s): Wen-ning Xu; Peng-xin Wang; Shu-yu Zhang
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Paper Abstract

To some extent, the estimations of regional evapotranspiration using remotely sensed data could help researchers and decision makers to analyze regional crop water stress information, to estimate drought extent and water supply situation, and to make decisions on crop water management, especially for irrigation farming systems. In this paper, the Surface Energy Balance Algorithm for Land (SEBAL) is applied to retrieve land surface evapotranspiration in Guanzhong Plain and Weibei Tablelands by using Landsat TM data. After the preprocessing of the remotely sensed data and weather observation data, some algorithms of inversing the parameters under the SEBAL are developed locally. By using energy balance equation, latent heat flux during satellite overpass and the integrated daily fluxes in Guanzhong Plain and Weibei Tablelands are estimated. On the basis of the study area, some locally retrieved land surface parameters are used as inputs for the SEBAL. Spatial distributions of surface albedo, land surface temperature, as well as various energy fluxes are drawn. After parameter improvement, statistical analysis indicates that the operating results in Guanzhong Plain and Weibei Tablelands are simple and reasonable, also shows good application prospect of SEBAL.

Paper Details

Date Published: 3 November 2008
PDF: 9 pages
Proc. SPIE 7145, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Monitoring and Assessment of Natural Resources and Environments, 71452F (3 November 2008); doi: 10.1117/12.813071
Show Author Affiliations
Wen-ning Xu, China Agricultural Univ. (China)
Peng-xin Wang, China Agricultural Univ. (China)
Shu-yu Zhang, Remote Sensing Information Ctr. for Agriculture (China)


Published in SPIE Proceedings Vol. 7145:
Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Monitoring and Assessment of Natural Resources and Environments
Lin Liu; Xia Li; Kai Liu; Xinchang Zhang; Yong Lao, Editor(s)

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