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不需要地面气象观测资料的遥感蒸发模型(GRL 2013)

已有 5016 次阅读 2013-8-11 16:02 |个人分类:论著|系统分类:论文交流| 遥感, 蒸发, GPP

 
不需要地面气象观测资料的遥感蒸发模型
 
根据试验观测资料发现月尺度上陆面蒸发ET与总初级生产力GPP存在明显的相关关系,据此提出了一种利用遥感GPP估算ET的方法。其中GPP估算模型为基于MODIS  EVI、LST数据的  TG模型,该模型不需要地面气象观测资料,因此本文的模型可以只利用遥感资料进行陆面蒸发估算。 
 
 
 
Remote estimation of terrestrial evapotranspiration without using meteorological data
  1. Yuting Yang1,*,

  2. Di Long2,

  3. Songhao Shang1

Article first published online: 17 JUN 2013

DOI: 10.1002/grl.50450

Geophysical Research Letters
Geophysical Research Letters

Volume 40,  Issue 12, pages 3026–3030, 28 June 2013

How to CiteAuthor InformationPublication HistoryFunding Information

How to Cite

Yang,  Y., D.  Long, and S.  Shang (2013), Remote estimation of terrestrial evapotranspiration without using meteorological data, Geophys. Res. Lett., 40, 3026–3030, doi:10.1002/grl.50450.

Author Information
  1. State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing, China

  2. Bureau of Economic Geology, Jackson School of Geosciences, The University of Texas at Austin, Austin, Texas, USA

     

*Corresponding author: Y. Yang, State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084, China. (yyt08@mails.tsinghua.edu.cn)

Publication History
  1. Issue published online: 18 JUL 2013

  2. Article first published online: 17 JUN 2013

  3. Accepted manuscript online: 8 APR 2013 12:44PM EST

  4. Manuscript Accepted: 5 APR 2013

  5. Manuscript Revised: 4 APR 2013

  6. Manuscript Received: 28 FEB 2013

 
Keywords:
  • remote sensing;

  • evapotranspiration;

  • ecosystem water use efficiency;

  • gross primary production

[1] We developed a new method to estimate terrestrial evapotranspiration (ET) from satellite data without using meteorological inputs. By analyzing observations from 20 eddy covariance tower sites across continental North America, we found a strong relationship between monthly gross primary production (GPP) and ET (R2 = 0.72 – 0.97),  implying the potential of using the remotely  sensed GPP to invert ET. We therefore adopted the Temperature-Greenness model which calculates 16 day GPP using MODIS EVI and  LST products to estimate GPP and then to calculate ET by dividing GPP with ecosystem water use efficiency (the ratio of GPP to ET). The proposed method estimated 16 day ET very well by comparison with tower-based measurements (R2 = 0.84, p < 0.001, n = 1290) and provided better ET estimates than the MODIS ET product. This suggests that routine estimation of ET from satellite remote sensing without using fine-resolution meteorological fields is possible and can be very useful for studying water and carbon cycles.

 



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