Modeling of TIR radiative transfer in the soil-vegetation-atmosphere system: sensitivity to soil water content and LAI and simulation of complex scenes
The exploration of the full potential of multi-angular thermal infrared measurements is hampered by the scarcity of accurate and representative data sets. Acquisition of field data has several constraints, including lack of a suitable airborne sensor system. Development and evaluation of algorithms requires detailed and accurate radiometric data, which have to be collected in a very short time to limit noise due to the temporal variability of surface temperature controlled by the local heat balance within the canopy. Several canopy properties have to be determined, e.g. leaf area index (LAI), leaf inclination distribution, in addition to soil and foliage temperature. A data set for validation studies should comprise a range of canopies and canopy conditions. We have coped with these difficulties by using a detailed radiative transfer model (CUPID) of the soil-plant--atmosphere system to produce synthetic data sets over a wide range of canopies and hydro-meteorological conditions. These data have been first used to assess the sensitivity of the anisotropy in TIR radiance to LAI and to the soil water content. It was shown that a dry top soil and a wet root zone imply that the brightness temperature is highest at nadir viewing, opposite to the condition with a wet top soil and a drier root zone. The relative magnitude of the directional change in surface temperature compared with the difference between soil and foliage temperature was evaluated in detail over a range of LAI values. Next, the radiance data base created by RT modeling was used to produce realistic complex scenes. Land cover of a complex, irrigated agriculture scene was mapped beforehand using a TM image.