Surface energy fluxes with the Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER) at the Iowa 2002 SMACEX site (USA)

French, Andrew N.; Jacob, Frédéric; Anderson, Martha C.; Kustas, William P.; Timmermans, W.; Gieske, A.S.M.; Su, Zhongbo; Su, Haijun; McCabe, Matthew F.; Li, F..; Prueger, John H.; Brunsell, Nathaniel A.

doi:10.1016/j.rse.2005.05.015

Cited by 164 publications

(129 citation statements)

References 46 publications

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“…But in most cases, those studies lack the temporal representativeness of a surface evolution during a full growing season (Choi et al, 2009;French et al, 2005;Gonzalez-Dugo et al, 2009;van der Kwast et al, 2009;Li et al, 2005Li et al, , 2008Long and Singh, 2012;Ma et al, 2011;McCabe and Wood, 2006;Minacapilli et al, 2009;Su et al, 2005Su et al, , 2007. A nonexhaustive list of validation and intercomparison studies of surface energy budget (SEB) models is shown in Table 1.…”

Section: Context and Objectivesmentioning

confidence: 99%

Intercomparison of four remote-sensing-based energy balance methods to retrieve surface evapotranspiration and water stress of irrigated fields in semi-arid climate

Chirouze

Boulet

Jarlan

et al. 2014

Hydrol. Earth Syst. Sci.

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Abstract. Instantaneous evapotranspiration rates and surface water stress levels can be deduced from remotely sensed surface temperature data through the surface energy budget. Two families of methods can be defined: the contextual methods, where stress levels are scaled on a given image between hot/dry and cool/wet pixels for a particular vegetation cover, and single-pixel methods, which evaluate latent heat as the residual of the surface energy balance for one pixel independently from the others. Four models, two contextual (S-SEBI and a modified triangle method, named VIT) and two single-pixel (TSEB, SEBS) are applied over one growing season (December-May) for a 4 km × 4 km irrigated agricultural area in the semi-arid northern Mexico. Their performance, both at local and spatial standpoints, are compared relatively to energy balance data acquired at seven locations within the area, as well as an uncalibrated soilvegetation-atmosphere transfer (SVAT) model forced with local in situ data including observed irrigation and rainfall amounts. Stress levels are not always well retrieved by most models, but S-SEBI as well as TSEB, although slightly biased, show good performance. The drop in model performance is observed for all models when vegetation is senescent, mostly due to a poor partitioning both between turbulent fluxes and between the soil/plant components of the latent heat flux and the available energy. As expected, contextual methods perform well when contrasted soil moisture and vegetation conditions are encountered in the same image (therefore, especially in spring and early summer) while they tend to exaggerate the spread in water status in more homogeneous conditions (especially in winter). Surface energy balance models run with available remotely sensed products prove to be nearly as accurate as the uncalibrated SVAT model forced with in situ data.

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Section: Context and Objectivesmentioning

confidence: 99%

Intercomparison of four remote-sensing-based energy balance methods to retrieve surface evapotranspiration and water stress of irrigated fields in semi-arid climate

Chirouze

Boulet

Jarlan

et al. 2014

Hydrol. Earth Syst. Sci.

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show abstract

“…ASTERs excellent capabilities for surface energy flux mapping (French et al, 2005) -15 m resolution in 3 visible, 30 m resolution in 6 near-infrared and 90 m resolution in 5 thermal infrared bands -are used from an overpass on 18 July at 11:00:29 UTC (Fig. 1).…”

Section: Remote Sensing Datamentioning

confidence: 99%

Evaluation of the Surface Energy Balance System (SEBS) applied to ASTER imagery with flux-measurements at the SPARC 2004 site (Barrax, Spain)

Kwast

Timmermans

Gieske

et al. 2009

Hydrol. Earth Syst. Sci.

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Abstract. Accurate quantification of the amount and spatial variation of evapotranspiration is important in a wide range of disciplines. Remote sensing based surface energy balance models have been developed to estimate turbulent surface energy fluxes at different scales. The objective of this study is to evaluate the Surface Energy Balance System (SEBS) model on a landscape scale, using tower-based flux measurements at different land cover units during an overpass of the ASTER sensor over the SPARC 2004 experimental site in Barrax (Spain). A sensitivity analysis has been performed in order to investigate to which variable the sensible heat flux is most sensitive. Taking into account their estimation errors, the aerodynamic parameters (h c , z 0M and d 0 ) can cause large deviations in the modelling of sensible heat flux. The effect of replacement of empirical derivation of these aerodynamic parameters in the model by field estimates or literature values is investigated by testing two scenarios: the Empirical Scenario in which empirical equations are used to derive aerodynamic parameters and the Field Scenario in which values from field measurements or literature are used to replace the empirical calculations of the Empirical Scenario. In the case of a homogeneous land cover in the footprints of the measurements, the Field Scenario only resulted in a small improvement, compared to the Empirical Scenario. The Field Scenario can even worsen the result in the case of heterogeneous footprints, by creating sharp borders related to the land cover map. In both scenarios modelled fluxes correspond Correspondence to: J. van der Kwast (hans.vanderkwast@vito.be) better with flux measurements over uniform land cover compared to cases where different land covers are mixed in the measurement footprint. Furthermore SEBS underestimates sensible heat flux especially over dry and sparsely vegetated areas, which is common in single-source models.

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“…ASTER is used to estimate evapotranspiration over highly heterogeneous landscapes (e.g. Schmugge et al, 1998b;French et al, 2005;Courault et al, 2009), but its relatively long revisit cycle is not convenient for seasonal monitoring (e.g. Norman et al, 1995;Sellers et al, 1995;Norman et al, 2003).…”

Section: Introductionmentioning

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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Surface energy fluxes with the Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER) at the Iowa 2002 SMACEX site (USA)

Cited by 164 publications

References 46 publications

Intercomparison of four remote-sensing-based energy balance methods to retrieve surface evapotranspiration and water stress of irrigated fields in semi-arid climate

Intercomparison of four remote-sensing-based energy balance methods to retrieve surface evapotranspiration and water stress of irrigated fields in semi-arid climate

Evaluation of the Surface Energy Balance System (SEBS) applied to ASTER imagery with flux-measurements at the SPARC 2004 site (Barrax, Spain)

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

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