Radiative transfer models describing the interaction between matter and electromagnetic radiation serve as cornerstones for optical remote sensing. The radiative transfer theory provides the most logical linkage between observations and physical processes that generate signals in optical remote sensing. Radiative transfer modelling is therefore an integral part of remote sensing, since it provides the most efficient tool for accurate retrievals of Earth properties from satellite data. Radiative transfer models are used in a number of different applications such as sensor radiometric calibration, atmospheric correction and the modelling radiation processes in vegetation canopies.
Vegetation radiative transfer models (RTMs) study the relationship between leaf and canopy biophysical variables and reflectance, absorbance and scattering mechanisms. The infinite variability of vegetation structure complicates the modeling of RT in vegetation canopies. Numerous models of RT in vegetation canopies were developed in the second half of the last century. Models differ by the details accounted for and by the simplifications introduced in the description of canopy structure and photon–vegetation interactions. Gradual improvement in RTMs accuracy, yet in complexity too, have diversified RTMs from simple turbid medium RTMs towards advanced Monte Carlo RTMs that allow for explicit 3D representations of complex canopy architectures. This evolution has resulted in an increase in the computational requirements to run the model, which bears implications towards practical applications. When choosing an RTM, a trade-off between invertibility and realism has to be made: simpler models are easier to invert but less realistic, while advanced models more realistic but require a large amount of variables to be configured. The two most widely used models are the leaf model PROSPECT and Scattering by Arbitrary Inclined Leaves (SAIL) canopy model.
Atmosphere RTMs study the interaction of radiation with the atmosphere. The remotely-sensed signals at satellite or airborne platforms are combinations of surface and atmospheric contributions, with relative amounts varying across the two wavelength regions, depending on the condition of the atmosphere. The order of magnitude of atmosphere signals can be equal or larger than that of land or ocean surface signals that arise at the top of the atmosphere (TOA). In order to derive accurate sensor calibration and atmospheric correction, the contribution of the atmospheric constituents to the total retrieved signal must be understood and modelled. Atmospheric radiative transfer models simulate the radiative transfer interactions of light scattering, absorption and emission through the atmosphere. Some widely used atmospheric RTMs are 6SV, libRadtran, MODTRAN, and ATCOR.
Advances in radiative transfer modeling enhance our ability to detect and monitor changes in our planet through new methodologies and technical approaches to analyze and interpret measurements from air- and space-borne sensors.