Remote sensing-based evapotranspiration algorithm: a case study of all sky conditions on a regional scale

Accurate estimation of the land surface evapotranspiration (ET) over a heterogeneous ecosystem is important to understand the interaction between the land surface and the atmosphere with practical applications in integrated water resources management. Although numerous studies have been carried out...

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Veröffentlicht in:GIScience and remote sensing 2015-09, Vol.52 (5), p.627-642
Hauptverfasser: Sur, Chanyang, Kang, Seokkoo, Kim, Jong-suk, Choi, Minha
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Sprache:eng
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Zusammenfassung:Accurate estimation of the land surface evapotranspiration (ET) over a heterogeneous ecosystem is important to understand the interaction between the land surface and the atmosphere with practical applications in integrated water resources management. Although numerous studies have been carried out to develop remote sensing technologies which could achieve more accurate prediction of the regional ET distributions, degrees of uncertainty remain due to the high spatiotemporal variability of the hydrometeorological parameters. A revised remote sensing-based Penman-Monteith algorithm under all sky conditions (Revised RS-PM allsky ) is proposed in this study using the MODerate resolution Imaging Spectroradiometer (MODIS) (ET MODIS ), and the model's capability was assessed over the complex topography of the Korean peninsula. The ground measurements taken at two flux sites with different land cover types in 2012 were employed. The results of ET MODIS represented temporal compatibility yielding biases of −0.18 mm day −1 at Seolmacheon (SMC) site and −0.14 mm day −1 at Cheongmicheon Farmland (CFC) site and root mean square error (RMSE) values of 1.42 mm day −1 at SMC site and 1.26 mm day −1 at CFC site. Overall, ET MODIS was verified to have similar error ranges as those of the previous studies conducted over flat and heterogeneous regions. The results suggest that the revised RS-PM algorithms can be applied on a regional scale with heterogeneous topography over long-term periods if handling of the input data is carefully conducted.
ISSN:1548-1603
1943-7226
DOI:10.1080/15481603.2015.1056288