Modeling and Inversion in Thermal Infrared Remote Sensing over ...

246 F. Jacob et al.ird-00392669, version 1 - 9 Jun 2009– Surface brightness temperature is equivalent to the radiance outgoing from thetarget, by assuming a unity emissivity [50], and corresponds to the basic TIRremote sensing measurement. It is recovered from at sensor measurements performingatmospheric corrections. It can be assimilated, using modeling tools forland surface, into process models such as SVAT and crop models [18, 38, 39, 43].– Ensemble waveband emissivity is needed to derive radiometric temperature frombrightness temperature [50, 51]. It is also useful for retrieving ensemble broadbandemissivity, a key parameter for land surface radiative budget [52–54].– Ensemble radiometric temperature is emissivity normalized [50, 51]; and correspondsto kinetic temperature for an homogeneous and isothermal surface [55].It is used to estimate surface energy fluxes and water status from spatial variabilityindicators: the vegetation index / temperature triangle [41, 56–58]; or thealbedo / temperature diagram [23, 37, 59, 60]. It is also used for retrieving soiland vegetation temperatures from two source energy balance modeling [19, 24].– Aerodynamic temperature is air temperature at the thermal roughness length [50].It is the physical temperature to be used with one source models of surface energyfluxes based on excess resistance [61–63]. These can be SVAT models [39, 64];or energy balance models [22, 23, 37, 59, 60, 65, 66].– Soil and vegetation temperatures correspond to kinetic [67] or radiometric [68]temperatures. They are often used for two-source modeling. The latter can beSVAT models [43, 67, 69]; or energy balance models [70, 20, 71]. Retrievingthese temperatures requires an adequate estimation of directional ensemble emissivity.– Sunlit and shaded components are refinements of soil and vegetation temperatures.They can significantly differ, according to various factors which drive thethermal regime: the water status, the solar exposure resulting from the canopygeometry and the illumination direction. These components are of interest forunderstanding canopy directional brightness and radiometric temperatures [58,72–74].– Canopy temperature profile, from the soil surface to the top of canopy, is thefinest temperature one can consider. Similarly to sunlit and shaded componentsfor soil and vegetation temperatures, this thermal regime is considered for understandingcanopy directional brightness and radiometric temperatures, in relationwith local energy balance within the canopy [75–78].The seek accuracies vary from one application to another,according to the sensitivitiesof process models. For temperature, the goal is accuracy better than 1 K [79].For emissivity, the goal is absolute accuracy better than 0.01 [80]. Recovering bothrelies on exploiting the dimensions of the TIR remotely sensed information.10.3 Available Information from TIR Remote SensingUncorrected ProofThe four dimensions of the remotely sensed information are temporal and spatial(Section 10.3.1), and spectral and directional (Section 10.3.2). Due to orbital rules