Optimized algorithm for evapotranspiration retrieval via remote sensing

Many algorithms for surface energy balance (SEB) based on remote sensing (RS) have been advanced to determine evapotranspiration (ET). These algorithms were developed for specific conditions (e.g., sensors, land use, and crop management) in which functions and empirical parameters within its algorit...

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Vydáno v:Agricultural water management Ročník 262; s. 107390
Hlavní autoři: Wagner Wolff, Francisco, João Paulo, Flumignan, Danilton Luiz, Marin, Fábio Ricardo, Folegatti, Marcos Vinícius
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier B.V 31.03.2022
Témata:
algorithms
Brazil
corn
crop management
Data-driven
energy balance
evapotranspiration
Geoprocessing
Irrigation
Jatropha curcas
land use
Landsat
Precision agriculture
soybeans
sugarcane
unmanned aerial vehicles
water management
Brazil
Precision agriculture
Irrigation
Data-driven
Geoprocessing
ISSN:0378-3774, 1873-2283
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Shrnutí:Many algorithms for surface energy balance (SEB) based on remote sensing (RS) have been advanced to determine evapotranspiration (ET). These algorithms were developed for specific conditions (e.g., sensors, land use, and crop management) in which functions and empirical parameters within its algorithms concur with those conditions. Therefore, this study aims to develop a SEB-RS algorithm for retrieving ET adjusted to in situ observations. The study was conducted in two experimental fields in Brazil with the crops Jatropha curcas, maize, soybean, and sugarcane. We used multispectral images from the orbital sensors, Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) coupled in Landsat 8 satellite and from the terrestrial sensor, Altum, on board of an unmanned aerial vehicle. The proposed algorithm termed as Ground-truthed Surface Energy Balance (GT-SEB) is based on physical formulation of SEB-RS algorithms, where two extra computational processes using in situ ET observations were proposed for originating the new algorithm. The first additional process for optimizing the automatic “anchor” pixels selection and another for algorithm parameters optimization. Thus, both processes aim to reduce the difference between the observed ET and estimated by GT-SEB. Being assessed for both orbital (OLI/TIRS) and suborbital (Altum) sensors, the GT-SEB yielded excellent results (root-mean-square-error, RMSE, ≤ 0.48 mm and modified Kling-Gupta efficiency, KGE, ≥ 0.92). In addition to GT-SEB being an optimized algorithm, it uses a classic parameterization of SEB-RS algorithms, providing efficiency and scalability for other remote sensors, climates, and surfaces. •A new algorithm for mapping evapotranspiration (ET) from remote sensing (RS) is proposed.•ET in situ observed is employed to drive an optimal ET mapping.•The uncertainties in the ET mapping via RS are reduced.•The algorithm is scalable for different kind of sensors, climates and surfaces.
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ISSN:0378-3774
1873-2283
DOI:10.1016/j.agwat.2021.107390