Estimation of soil and vegetation temperatures with multiangular thermal infrared observations: IMGRASS, HEIFE, and SGP 1997 experiments

Menenti, Massimo; Li, Jia; Li, Zhao-Liang; Djepa, V.; Wang, Jiemin; Stoll, M. P.; Su, Zhongbo; Rast, M.

doi:10.1029/2000jd900671

Cited by 51 publications

(26 citation statements)

References 38 publications

(24 reference statements)

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“…Land surface variables, such as surface temperature, surface hemispherical albedo, Normalized Difference Vegetation Index (NDVI) and surface thermal emissivity can be derived directly from satellite observations (e.g., Susskind et al, 1984;Che'din et al, 1985;Tucker, 1986;Wan and Dozier, 1989;Menenti et al, 1989;Li, 1990, 1995;Watson et al, 1990;Baret and Guyot, 1997;Price, 1992;Kahle and Alley, 1992;Li and Becker, 1993;Qi et al, 1994;Schmugge et al, 1995;Sobrino and Raissouni, 2000;Li et al, 2000Li et al, , 2003Jia et al, 2003b;Menenti et al, 2001). The regional heat flux can be obtained indirectly using the derived parameters and variables (Pinker, 1990).…”

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confidence: 99%

Estimating surface fluxes over middle and upper streams of the Heihe River Basin with ASTER imagery

et al. 2011

Hydrol. Earth Syst. Sci.

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Abstract. Land surface heat fluxes are essential measures of the strengths of land-atmosphere interactions involving energy, heat and water. Correct parameterization of these fluxes in climate models is critical. Despite their importance, stateof-the-art observation techniques cannot provide representative areal averages of these fluxes comparable to the model grid. Alternative methods of estimation are thus required. These alternative approaches use (satellite) observables of the land surface conditions. In this study, the Surface Energy Balance System (SEBS) algorithm was evaluated in a cold and arid environment, using land surface parameters derived from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data. Field observations and estimates from SEBS were compared in terms of net radiation flux (R n ), soil heat flux (G 0 ), sensible heat flux (H ) and latent heat flux (λE) over a heterogeneous land surface. As a case study, this methodology was applied to the experimental area of the Watershed Allied Telemetry Experimental Research (WATER) project, located on the mid-to-upstream sections of the Heihe River in northwest China. ASTER data acquired between 3 May and 4 June 2008, under clearsky conditions were used to determine the surface fluxes. Ground-based measurements of land surface heat fluxes were compared with values derived from the ASTER data. The results show that the derived surface variables and the land surface heat fluxes furnished by SEBS in different months over the study area are in good agreement with the observed Correspondence to: W. Ma (wqma@lzb.ac.cn) land surface status under the limited cases (some cases looks poor results). So SEBS can be used to estimate turbulent heat fluxes with acceptable accuracy in areas where there is partial vegetation cover in exceptive conditions. It is very important to perform calculations using ground-based observational data for parameterization in SEBS in the future. Nevertheless, the remote-sensing results can provide improved explanations of land surface fluxes over varying land coverage at greater spatial scales.

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confidence: 99%

Estimating surface fluxes over middle and upper streams of the Heihe River Basin with ASTER imagery

et al. 2011

Hydrol. Earth Syst. Sci.

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“…where T s was the surface temperature derived from SW and AATSR data; T g was the temperature above the bare soil surface; T v was the temperature above the canopy surface; δT was the typical discrepancy between soil and canopy surface temperature, which depends on the field and density of vegetation, and moisture status Menenti et al, 2001;Jia et al, 2003), a 2.3 K was observed during the experiment at the satellite overpass time.…”

Section: The Net Radiation Over the Canopy And The Bare Soil Surfacementioning

confidence: 99%

“…The split-window (SW) algorithm can minimize the contributions of water vapour in land surface retrieval and the AATSR have two thermal channels. Therefore, the surface temperatures were calculated by splitwindow algorithm, and it was portioned by the vegetation fractional coverage and the typical discrepancy between soil and canopy surface temperature Menenti et al, 2001;Jia et al, 2003), these were…”

Section: The Net Radiation Over the Canopy And The Bare Soil Surfacementioning

confidence: 99%

Actual daily evapotranspiration estimated from MERIS and AATSR data over the Chinese Loess Plateau

Liu

Wen

Wang

et al. 2010

Hydrol. Earth Syst. Sci.

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Abstract. The Chinese Loess Plateau is located in the north of China and has a significant impact on the climate and ecosystem evolvement over the East Asian continent. Estimates of evapotranspiration (ET) at a regional scale are in crucial need for climate studies, weather forecasts, hydrological surveys, ecological monitoring and water resource management. In this research, the ET of the Chinese Loess Plateau was estimated by using an energy balance approach and data collected during the LOess Plateau land-atmosphere interaction pilot EXperiments 2005 (LOPEX05). With the combined data of the Medium Resolution Imaging Spectrometer (MERIS), the Advanced Along-Track Scanning Radiometer (AATSR) and some other variables such as air temperature, crop height and wind speed, the instantaneous net radiation, sensible heat flux and soil heat flux were calculated; the instantaneous latent heat flux was derived as the residual term of energy balance, and then converted to daily ET value by sunshine duration. The calculated daily ET from the model showed a good match with the measurements of the eddy covariance systems deployed in LOPEX05. The minimum relative error of this approach is 9.0%, the cause of the bias was also explored and discussed.

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“…Previous efforts have been directed toward inverting component temperatures using both experimental and satellite-borne multi-angle datasets [16][17][18][19]. Many directional algorithms have been proposed based on radiative transfer models (RTMs), such as the geometric model proposed by Kimes et al [20] for row-planted crops and the analytical RTM known as FR97 proposed by Francois et al [21] for homogenous canopies.…”

Section: Introductionmentioning

confidence: 99%

“…Multi-angle remote sensing has been identified as a useful tool for the separation of leaf and soil temperatures [16,17]. Previous efforts have been directed toward inverting component temperatures using both experimental and satellite-borne multi-angle datasets [16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

A Robust Inversion Algorithm for Surface Leaf and Soil Temperatures Using the Vegetation Clumping Index

Bian

Cao

et al. 2017

Remote Sensing

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Abstract:The inversion of land surface component temperatures is an essential source of information for mapping heat fluxes and the angular normalization of thermal infrared (TIR) observations. Leaf and soil temperatures can be retrieved using multiple-view-angle TIR observations. In a satellite-scale pixel, the clumping effect of vegetation is usually present, but it is not completely considered during the inversion process. Therefore, we introduced a simple inversion procedure that uses gap frequency with a clumping index (GCI) for leaf and soil temperatures over both crop and forest canopies. Simulated datasets corresponding to turbid vegetation, regularly planted crops and randomly distributed forest were generated using a radiosity model and were used to test the proposed inversion algorithm. The results indicated that the GCI algorithm performed well for both crop and forest canopies, with root mean squared errors of less than 1.0 • C against simulated values. The proposed inversion algorithm was also validated using measured datasets over orchard, maize and wheat canopies. Similar results were achieved, demonstrating that using the clumping index can improve inversion results. In all evaluations, we recommend using the GCI algorithm as a foundation for future satellite-based applications due to its straightforward form and robust performance for both crop and forest canopies using the vegetation clumping index.

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Estimation of soil and vegetation temperatures with multiangular thermal infrared observations: IMGRASS, HEIFE, and SGP 1997 experiments

Cited by 51 publications

References 38 publications

Estimating surface fluxes over middle and upper streams of the Heihe River Basin with ASTER imagery

Estimating surface fluxes over middle and upper streams of the Heihe River Basin with ASTER imagery

Actual daily evapotranspiration estimated from MERIS and AATSR data over the Chinese Loess Plateau

A Robust Inversion Algorithm for Surface Leaf and Soil Temperatures Using the Vegetation Clumping Index

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