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Proceedings Paper

Retrieval of water and heat flux based on fusion of LANDSAT TM/ETM+ and MODIS data
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Paper Abstract

The Moderate Resolution Imaging Spectroradiometer (MODIS) data has a high temporal resolution, which, at present, is an ideal data source in simulative monitoring of regional-scale changes in surface energy and water. However, the spatial resolution of its thermal infrared band is relatively low (1 km). The Landsat TM/ETM+ data have a high spatial resolution, but their single thermal infrared bands can lead to the fact that the inversion accuracy for the surface temperature is not high, and that the time resolution is low. This limits its application in the surface evapotranspiration (ET) monitoring. Combining TM/ETM + visible wave band with MODIS thermal infrared wave band, this paper discusses a multi-scale remote sensing method to estimate regional surface ET. On the basis of space enhancement method, the vegetation index estimated by TM/ETM + enhances the surface temperature scale with the inversion of MODIS to a 30 m resolution, which aims to improve the estimation accuracy of ET in the non-uniform surface mixed-pixel. The results show that this method has a higher accuracy of ET estimation compared with the method of only using MODIS or ETM+ data. Moreover, it can obtain a more obvious effect on scale correction in the uneven land surface or various surface covering types, and the corrected ET is close to the observation result.

Paper Details

Date Published: 4 September 2015
PDF: 6 pages
Proc. SPIE 9610, Remote Sensing and Modeling of Ecosystems for Sustainability XII, 96101D (4 September 2015); doi: 10.1117/12.2184667
Show Author Affiliations
Jicai Ning, East China Normal Univ. (China)
Yantai Institute of Coastal Zone Research (China)
Zhiqiang Gao, Yantai Institute of Coastal Zone Research (China)
Colorado State Univ. (United States)
Chaoshun Liu, East China Normal Univ. (China)
Wei Gao, Colorado State Univ. (United States)


Published in SPIE Proceedings Vol. 9610:
Remote Sensing and Modeling of Ecosystems for Sustainability XII
Wei Gao; Ni-Bin Chang; Jinnian Wang, Editor(s)

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