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

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

doi:https://doi.org/10.5194/hess-20-4409-2016

Articles | Volume 20, issue 11

https://doi.org/10.5194/hess-20-4409-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/hess-20-4409-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

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

Data sets

HiWATER: Land cover map of Heihe River Basin B. Zhong http://card.westgis.ac.cn/hiwater/view/uuid/6bbf9a3f-e7d8-4255-9ecb-131e1543316d

NCEP FNL Operational Model Global Tropospheric Analyses, continuing from July 1999. Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory National Centers for Environmental Prediction/National Weather Service/NOAA/U.S. Department of Commerce http://rda.ucar.edu/datasets/ds083.2/

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.