An operational method for the disaggregation of land surface temperature to estimate actual evapotranspiration in the arid region of Chile
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Monitoring evapotranspiration in arid and semi-arid environments plays a key role in water irrigation scheduling for water use efficiency. This work presents an operational method for evapotranspiration retrievals based on disaggregated Land Surface Temperature (LST). The retrieved LSTs from Landsat-8 and MODIS data were merged in order to provide an 8-day composite LST product at 100 x 100 m resolution. The method was tested in the arid region of Copiapo, Chile using data from years 2013-2014 and validated using data from years 2015-2016. In-situ measurements from agrometeorological stations such as air temperature and potential evapotranspiration (ETU) estimated at the location were used in the ET estimation method. The disaggregation method was developed by taking into account (1) the spatial relationship between Landsat-8 and MODIS LST, (2) the spatial relationship between LST and the Normalized Difference Vegetation Index (NDVI) at high spatial resolution (Landsat-8), and (3) the temporal variations along the year of both relationships aforementioned. The comparison between disaggregated LST at 100 m resolution and in situ LST measurements presents a coefficient of determination (r(2)), in average, equal to 0.70 and a RMSE equal to 3.6 K. The disaggregated LST was used in an operational model to estimate the actual evapotranspiration (ETa). The ETa shows good results in terms of seasonal variations and in comparison to the evapotranspiration estimated by using crop coefficients (kc). The comparison between remotely sensed and in situ ETa presents an overall r(2) close to 0.67 and a RMSE equal to 0.6 mm day(-1) for both crops. These results are important for further improvements in water use sustain ability in the Copiapo valley, which is currently affected by high water demand. (C) 2017 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.
Artículo de publicación ISI
Quote ItemISPRS Journal of Photogrammetry and Remote Sensing 128 (2017) 170–181
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