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Journal ArticleDOI

A remote sensing surface energy balance algorithm for land (SEBAL)-1. Formulation

TLDR
The Surface Energy Balance Algorithm for Land (SEBAL) as mentioned in this paper estimates the spatial variation of most essential hydro-meteorological parameters empirically, and requires only field information on short wave atmospheric transmittance, surface temperature and vegetation height.
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This article is published in Journal of Hydrology.The article was published on 1998-12-01. It has received 2628 citations till now. The article focuses on the topics: SEBAL & Land cover.

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Citations
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Journal ArticleDOI

Analysis of variations and controls of evapotranspiration over major Indian River Basins (1982-2014).

TL;DR: This study analyses long-term estimates of evapotranspiration (ET) over four major river basins of India with the primary objective of understanding the factors controlling its space-time variability and reveals that ET variance is largely controlled by the availability of water.
Journal ArticleDOI

Managing Irrigation Water by Yield and Water Productivity Assessment of a Rice-Wheat System Using Remote Sensing

TL;DR: In this paper, an effort is made to estimate actual evapotranspiration (ETa) by using the soil and energy balance algorithm (SEBAL), which used the moderate-resolution imaging spectroradiometer (MODIS) satellite with a spatial resolution of 1,000m.
Journal ArticleDOI

Estimation of air temperature and reference evapotranspiration using MODIS land surface temperature over Greece

TL;DR: In this article, land surface temperature data, during daytime (LSTday) or night-time(LSTnight), were employed for predicting maximum (Tmax) or minimum (Tmin) for predicting Tmax and Tmin.
Journal ArticleDOI

Assessment of Spatiotemporal Variability of Evapotranspiration and Its Governing Factors in a Mountainous Watershed

TL;DR: In this paper, the authors investigated the spatio-temporal variations of ET at the East River watershed in Colorado and analyzed the factors that control these variations using community land model simulations.
Journal ArticleDOI

UAV Multispectral Imagery Combined with the FAO-56 Dual Approach for Maize Evapotranspiration Mapping in the North China Plain

TL;DR: The potential of multispectral images taken from unmanned aerial vehicles (UAVs) for estimating the temporal and spatial variability of Ks under the water stress condition and mapping the variability of field maize ET combined with the FAO-56 Kc model is explored.
References
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Journal ArticleDOI

The Interpretation of the Variations in Leaf Water Potential and Stomatal Conductance Found in Canopies in the Field

TL;DR: In this paper, the stomatal conductance of illuminated leaves is a function of current levels of temperature, vapour pressure deficit, leaf water potential (really turgor pressure) and ambient CO $_2$ concentration and when plotted against any one of these variables a scatter diagram results.
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A Revised Land Surface Parameterization (SiB2) for Atmospheric GCMS. Part I: Model Formulation

TL;DR: In this paper, a revised version of the Simple Biosphere model (SiB2) is presented, incorporating a realistic canopy photosynthesis-conductance model to describe the simultaneous transfer of CO2 and water vapor into and out of the vegetation, respectively.
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Flux Parameterization over Land Surfaces for Atmospheric Models

TL;DR: In this article, a summary of observations and modeling efforts on surface fluxes, carried out at Cabauw in The Netherlands and during MESOGERS-84 in the south of France, is given.
Journal ArticleDOI

Footprint prediction of scalar fluxes from analytical solutions of the diffusion equation

TL;DR: The use of analytical solutions of the diffusion equation for "footprint prediction" is explored in this paper, where the upwind area most likely to affect a downwind flux measurement at a given height is compared.
Journal ArticleDOI

Wheat canopy temperature: A practical tool for evaluating water requirements

TL;DR: In this paper, the authors used a sliding cubic smoothing technique to calculate daily water contents and thus water depletion rates for the entire growing season and used this to predict water use by wheat in six differentially irrigated plots.
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