Improving the Evapotranspiration Estimation under Cloudy Condition by Extending the Ts-VI Triangle Model

• Main Authors: Boyang Li, Yaokui Cui, Xiaozhuang Geng, Huan Li
• Format: Article
• Language: English
• Published: MDPI AG 2021-04-01
• Series: Remote Sensing
• Subjects: evapotranspiration; spatio-temporal continuity; land surface temperature; Ts-VI ET model; robust regression
• Online Access: https://www.mdpi.com/2072-4292/13/8/1516

Evapotranspiration (ET) of soil-vegetation system is the main process of the water and energy exchange between the atmosphere and the land surface. Spatio-temporal continuous ET is vitally important to agriculture and ecological applications. Surface temperature and vegetation index (Ts-VI) triangle ET model based on remote sensing land surface temperature (LST) is widely used to monitor the land surface ET. However, a large number of missing data caused by the presence of clouds always reduces the availability of the main parameter LST, thus making the remote sensing-based ET estimation unavailable. In this paper, a method to improve the availability of ET estimates from Ts-VI model is proposed. Firstly, continuous LST product of the time series is obtained using a reconstruction algorithm, and then, the reconstructed LST is applied to the estimate ET using the Ts-VI model. The validation in the Heihe River Basin from 2009 to 2011 showed that the availability of ET estimates is improved from 25 days per year (d/yr) to 141 d/yr. Compared with the in situ data, a very good performance of the estimated ET is found with RMSE 1.23 mm/day and R² 0.6257 at point scale and RMSE 0.32 mm/day and R² 0.8556 at regional scale. This will improve the understanding of the water and energy exchange between the atmosphere and the land surface, especially under cloudy conditions.