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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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Satellite‐based near‐real‐time estimation of irrigated crop water consumption

TL;DR: In this paper, a variation of the MODIS standard evapotranspiration algorithm for near-real-time method for estimation of actual evapOTranspiration based entirely on satellite data is described.
Journal ArticleDOI

Evapotranspiration estimates derived using thermal-based satellite remote sensing and data fusion for irrigation management in California vineyards

TL;DR: In this paper, the authors investigate the utility of satellite-derived maps of evapotranspiration (ET) and the ratio of actual-to-reference ET (fRET) based on remotely sensed land-surface temperature (LST) imagery for monitoring crop water use and stress in vineyards.
Journal ArticleDOI

Automated Calibration of the METRIC‐Landsat Evapotranspiration Process

TL;DR: The background and logic for the statistical approach, how the statistics were developed, area of interest requirements and assumptions, adjustment for dry conditions in desert climates, and implementation in a common image processing environment are described.
Journal ArticleDOI

Comparison of three dual‐source remote sensing evapotranspiration models during the MUSOEXE‐12 campaign: Revisit of model physics

TL;DR: In this paper, three dual-source terrestrial evapotranspiration (ET) models were compared using ASTER images during the MUSOEXE-12 campaign in the Heihe River Basin in Northwest China, aiming to better understand the differences in model physics.
Journal ArticleDOI

A phenology-based approach to map crop types in the San Joaquin Valley, California

TL;DR: In this article, a phenology-based classification approach has been employed, which has extracted phenological metrics from normalized difference vegetation index (NDVI) profiles and identified crop types based on these metrics using decision trees.
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.
Journal ArticleDOI

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.
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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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