16 July 2019 Estimation of surface latent heat fluxes in an oasis utilizing a two-source energy balance model based on land surface temperature decomposition
Runke Wang, Jian Wang, Gaofeng Zhu, Hongyi Li, Donghang Shao, Xiaohua Hao
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Abstract

Latent heat flux is the main indicator of regional water-heat balance and plays an important role in drought monitoring and water resource management. Here, we attempt to estimate latent heat flux using a two-source energy balance model (TSEB). The decomposition algorithm of soil surface temperature and vegetation canopy temperature is discussed, and it is a key factor for calculating the latent heat flux in the TSEB model. Temperature decomposition was conducted using two methods: one is based on a simple linear relationship between the canopy temperature and directional radiation temperature and the other is based on soil latent heat flux expressed by the Priestley–Taylor formula. Then, the soil temperature was estimated using the soil latent heat flux. The estimation of the surface heat flux was based on the soil and vegetation canopy temperatures. The results show that the Priestley–Taylor formula method provided more accurate estimates of the latent heat flux than the linear relation method, and the reliability and precision were improved. The root-mean-squares error of the former method decreased by 38.8% compared with the latter method. The TSEB model was used to estimate the surface heat flux, and it was feasible for monitoring drought in typical drought-prone regions.

© 2019 Society of Photo-Optical Instrumentation Engineers (SPIE) 1931-3195/2019/$28.00 © 2019 SPIE
Runke Wang, Jian Wang, Gaofeng Zhu, Hongyi Li, Donghang Shao, and Xiaohua Hao "Estimation of surface latent heat fluxes in an oasis utilizing a two-source energy balance model based on land surface temperature decomposition," Journal of Applied Remote Sensing 13(3), 034504 (16 July 2019). https://doi.org/10.1117/1.JRS.13.034504
Received: 30 October 2018; Accepted: 25 June 2019; Published: 16 July 2019
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KEYWORDS
Vegetation

Heat flux

Error analysis

Remote sensing

Data modeling

Wind energy

Agriculture

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