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A Novel NIR–Red Spectral Domain Evapotranspiration Model From the Chinese GF-1 Satellite: Application to the Huailai Agricultural Region of China

Yunjun Yao, Shunlin Liang, Joshua B. Fisher, Yuhu Zhang, Jie Cheng, Jiquan Chen, Kun Jia, Xiaotong Zhang, Xiangyi Bei, Ke Shang, Xiaozheng Guo, Junming Yang

2020IEEE Transactions on Geoscience and Remote Sensing17 citationsDOI

Abstract

The Chinese GF-1 satellite, the first satellite of the China High-resolution Earth Observation System launched in 2013, can be used to help estimate evapotranspiration (LE), which is important for myriad hydroclimatic and ecosystem science and applications. We propose a novel approach to use the GF-1 visible and near-infrared (VNIR) measurements at 16 m and 4-day resolutions to estimate LE. The NIR (near-infrared)–red spectral-domain (NRSD) model is coupled to a perpendicular soil moisture index (PSI) and a perpendicular vegetation index (PVI). We applied the model to the Huailai agricultural region of China with 55 scenes of GF-1 imagery during 2013–2017 and validated using ground measurements with footprint models for two eddy-covariance (EC) flux tower sites and one large aperture scintillometer (LAS) site. The results illustrate that the terrestrial daily LE can be estimated with squared correlation coefficients ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$R^{2}$ </tex-math></inline-formula> ) of 0.77–0.84 ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$p &lt; 0.01$ </tex-math></inline-formula> ) and root-mean-square error (RMSE) values of 17.9–21.5 W/m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> among all three sites. The site-calibrated statistics are improved by 0.14–0.25 for <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$R^{2}$ </tex-math></inline-formula> and decreased by 4.2–8.3 W/m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> for RMSE as compared to the commonly used universal PT-JPL model. A satisfactory performance is achieved across all experimental conditions, encouraging the application of the NRSD model to estimate LE for other broad regions.

Topics & Concepts

Mean squared errorEvapotranspirationScintillometerSatelliteVNIRRemote sensingEddy covarianceMathematicsAlgorithmMeteorologyStatisticsPhysicsGeographyHyperspectral imagingEcosystemAstronomyAtmospheric turbulenceTurbulenceEcologyBiologyPlant Water Relations and Carbon DynamicsRemote Sensing in AgricultureUrban Heat Island Mitigation