Articles | Volume 20, issue 11
Research article
02 Nov 2016
Research article |  | 02 Nov 2016

Remote sensing algorithm for surface evapotranspiration considering landscape and statistical effects on mixed pixels

Zhi Qing Peng, Xiaozhou Xin, Jin Jun Jiao, Ti Zhou, and Qinhuo Liu

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Cited articles

Agam, N., Kustas, W. P., Anderson, M. C., Li, F., and Colaizzi, P. D.: Utility of thermal sharpening over Texas high plains irrigated agricultural fields, J. Geophys. Res.-Atmos., 112, D19110,, 2007.
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Ambast, S. K., Keshari, A. K., and Gosain, A. K.: An operational model for estimating Regional Evapotranspiration through Surface Energy Partitioning (RESEP), Int. J. Remote Sens., 23, 4917–4930,, 2002.
Bastiaanssen, W. G. M., Menenti, M., Feddes, R. A., and Holtslag, A. A. M.: A remote sensing surface energy balance algorithm for land (SEBAL). 1. Formulation, J. Hydrol., 212–213, 198–212,, 1998.
Bateni, S. M. and Liang, S.: Estimating surface energy fluxes using a dual-source data assimilation approach adjoined to the heat diffusion equation, J. Geophys. Res.-Atmos. 117, D17118,, 2012.
Short summary
A remote sensing algorithm named temperature sharpening and flux aggregation (TSFA) was applied to HJ-1B satellite data to estimate evapotranspiration over heterogeneous surface considering landscape and statistical effects on mixed pixels. Footprint validation results showed TSFA was more accurate and less uncertain than other two upscaling methods. Additional analysis and comparison showed TSFA can capture land surface heterogeneities and integrate the effect of landscapes within mixed pixels.