Mapping surface fluxes using airborne visible, near infrared, thermal infrared 
remote sensing data and a spatialized surface energy balance model

Jacob, Frédéric; Olioso, Albert; Gu, Xing Fa; Su, Zhongbo; Séguin, Bernard

doi:10.1051/agro:2002053

Cited by 95 publications

(79 citation statements)

References 51 publications

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“…The disaggregation procedure D2 requires an estimate of T s, min , T s, max , ( 2000)) to monitor evapotranspiration at decametric (Jacob et al, 2002;Gómez et al, 2005) and regional (van den Hurk et al, 1997) scale.…”

Section: Extreme Temperatures Extrapolated From Modis Data Using Ancimentioning

confidence: 99%

Disaggregation of MODIS surface temperature over an agricultural area using a time series of Formosat-2 images

Merlin

Duchemin

Hagolle

et al. 2010

Remote Sensing of Environment

156

107

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The temporal frequency of the thermal data provided by current spaceborne high-resolution imagery systems is inadequate for agricultural applications.As an alternative to the lack of high-resolution observations, kilometric thermal data can be disaggregated using a green (photosynthetically active) veg- . The approach is also tested using the MODIS data re-sampled at 2 km resolution. Aggregation reduces errors in MODIS data and consequently increases the disaggregation accuracy.

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Section: Extreme Temperatures Extrapolated From Modis Data Using Ancimentioning

confidence: 99%

Disaggregation of MODIS surface temperature over an agricultural area using a time series of Formosat-2 images

Merlin

Duchemin

Hagolle

et al. 2010

Remote Sensing of Environment

156

107

View full text Add to dashboard Cite

show abstract

“…Such information is essential for numerical modeling of atmospheric and hydrological processes and for improving the accuracy of the models used in weather forecasting [13]. Additionally, quantitative information on these parameters is highly important for monitoring of land degradation and desertification on a regional scale [14,15].…”

Section: Introductionmentioning

confidence: 99%

Evapotranspiration Estimation with Remote Sensing and Various Surface Energy Balance Algorithms—A Review

2014

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Abstract:With the advent of new satellite technology, the radiative energy exchanges between Sun, Earth, and space may now be quantified accurately. Nevertheless, much less is known about the magnitude of the energy flows within the climate system and at the Earth's surface, which cannot be directly measured by satellites. This review surveys the basic theories, observational methods, and different surface energy balance algorithms for estimating evapotranspiration (ET) from landscapes and regions with remotely sensed surface temperatures, and highlights uncertainties and limitations associated with those estimation methods. Although some of these algorithms were built up for specific land covers like irrigation areas only, methods developed for other disciplines like hydrology and meteorology, are also reviewed, where continuous estimates in space and in time are needed. Temporal and spatial scaling issues associated with the use of thermal remote sensing for estimating evapotranspiration are also discussed. A review of these different satellite based remote sensing approaches is presented. The main physical bases and assumptions of these algorithms are also discussed. Some results are shown for the estimation of evapotranspiration on a rice paddy of Chiayi Plain in Taiwan using remote sensing data.

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“…The slope and offset are estimated inverting the sensible heat flux expression over wet areas (T o = T a ) and dry areas (H = Rn -G) [23]. The use of equation 3 enables us computing the sensible heat flux in pixel basis and solving the energy balance equation.…”

Section: Estimating Of Surface Energy Fluxesmentioning

confidence: 99%

Obtaining evapotranspiration and surface energy fluxes with remotely sensed data to improve agricultural water management

Khaldi¹,

Hamimed²,

Mederbal³

et al. 2011

African Journal of Food, Agriculture, Nutrition and Development

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4559 ABSTRACTThe quantification of evapotranspiration from irrigated areas is important for agriculture water management, especially in arid and semiarid regions where water deficiency is becoming a major constraint in economic welfare and sustainable development. Conventional methods that use point measurements to estimate evapotranspiration are representative only of local areas and cannot be extended to large areas because of heterogeneity of landscape. Remote sensing based energy balance models are presently most suited for estimating evapotranspiration at both field and regional scales. In this study, SEBAL (Surface Energy Balance Algorithm for Land), a remote sensing based evapotranspiration model, has been applied with Landsat ETM+ sensor for the estimation of actual evapotranspiration in the Habra plain, a semiarid region in west Algeria with heterogeneous surface conditions. This model followed an energy balance approach, where evapotranspiration is estimated as the residual when the net radiation, sensible heat flux and soil heat flux are known. It involves in the input the remote sensing land surface parameters such as surface temperature, NDVI and albedo. Different moisture indicators derived from the evapotranspiration were then calculated: evaporative fraction, Priestley-Taylor parameter and surface resistance to evaporation. These calculated indicators facilitate the quantitative diagnosis of moisture stress status in pixel basis. The study area contains extremes in surface albedo, vegetation cover and surface temperature. The land uses in this study area consists of irrigated agriculture, rain-fed agriculture and livestock grazing. The obtained results concern the validation of the used model for spatial distribution analysis of evapotranspiration and moisture indicators. The evaluation of daily evapotranspiration and moisture indicators are accurate enough for the spatial variations of evapotranspiration rather satisfactory than sophisticated models without having to introduce an important number of parameters in input with difficult accessibility in routine. In conclusion, the results suggest that SEBAL can be considered as an operational method to predict actual evapotranspiration from irrigated areas having limited amount of ground information.

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Mapping surface fluxes using airborne visible, near infrared, thermal infrared remote sensing data and a spatialized surface energy balance model

Cited by 95 publications

References 51 publications

Disaggregation of MODIS surface temperature over an agricultural area using a time series of Formosat-2 images

Disaggregation of MODIS surface temperature over an agricultural area using a time series of Formosat-2 images

Evapotranspiration Estimation with Remote Sensing and Various Surface Energy Balance Algorithms—A Review

Obtaining evapotranspiration and surface energy fluxes with remotely sensed data to improve agricultural water management

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