Advances in Land Remote Sensing System, Modeling, Inversion and Appl
This book collects the review papers from both technical sessions and three discussion panels of the 9th International Symposium on Physical Measurements and Signatures in Remote Sensing (ISPMSRS). It systematically summarizes the past achievements and id
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Modeling and Inversion in Thermal Infrared Remote Sensing over Vegetated Land Surfaces Fr´ed´eric Jacob, Thomas Schmugge, Albert Olioso, Andrew French, Dominique Courault, Kenta Ogawa, Francois Petitcolin, Ghani Chehbouni, Ana Pinheiro, and Jeffrey Privette
Fr´ed´eric Jacob Formerly at Remote Sensing and Land Management Laboratory Purpan Graduate School of Agriculture, Toulouse, France Now at Institute of Research for the Development Laboratory for studies on Interactions between Soils – Agrosystems – Hydrosystems UMR LISAH SupAgro/INRA/IRD, Montpellier, France [email protected] Thomas Schmugge Gerald Thomas Professor of Water Resources College of Agriculture New Mexico State University, Las Cruces, NM, USA Albert Olioso and Dominique Courault National Institute for Agronomical Research Climate – Soil – Environment Unit UMR CSE INRA/UAPV, Avignon, France Andrew French United States Department of Agriculture/Agricultural Research Service US Arid Land Agricultural Research Center, Maricopa, AZ, USA Kenta Ogawa Department of Geo-system Engineering, University of Tokyo Japan Francois Petitcolin ACRI-ST, Sophia Antipolis, France Ghani Chehbouni Institute of Research for the Development Center for Spatial Studies of the Biosphere UMR CESBio CNES/CNRS/UPS/IRD, Toulouse, France Ana Pinheiro Biospheric Sciences Branch, NASA’s GSFC, Greenbelt, MD, USA Jeffrey Privette NOAA’s National Climatic Data Center, Asheville, NC, USA S. Liang (ed.), Advances in Land Remote Sensing, 245–291. c Springer Science + Business Media B.V., 2008
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Abstract Thermal Infra Red (TIR) Remote sensing allows spatializing various land surface temperatures: ensemble brightness, radiometric and aerodynamic temperatures, soil and vegetation temperatures optionally sunlit and shaded, and canopy temperature profile. These are of interest for monitoring vegetated land surface processes: heat and mass exchanges, soil respiration and vegetation physiological activity. TIR remote sensors collect information according to spectral, directional, temporal and spatial dimensions. Inferring temperatures from measurements relies on developing and inverting modeling tools. Simple radiative transfer equations directly link measurements and variables of interest, and can be analytically inverted. Simulation models allow linking radiative regime to measurements. They require indirect inversions by minimizing differences between simulations and observations, or by calibrating simple equations and inductive learning methods. In both cases, inversion consists of solving an ill-posed problem, with several parameters to be constrained from few information. Brightness and radiometric temperatures have been inferred by inverting simulation models and simple radiative transfer equations, designed for atmosphere and land surfaces. Obtained accuracies suggest refining the use of spectral and temporal information, rather than innovative approaches. Forthcoming challenge is recovering more elaborated temperatures. Soil and vegetation compon
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