LIU Qiang, CHEN Liang-fu, LIU Qin-huo, et al. A Radiation Transfer Model to Predict Canopy Radiation in Thermal Infrared Band[J]. Journal of Remote Sensing, 2003, (3): 161-167. DOI: 10.11834/jrs.20030301.
Canopy radiance in thermal infrared (TIR) band mainly comes from emission of canopy itself. This differs very much from the situation of visible and near infrared (VNIR) band
in which reflection plays the major role. How- ever
the sophisticated canopy model in visible and near infrared band are still instructive to thermal infrared researches. Some recent works extend results of canopy BRDF model
such as Hapke’s formula
to thermal infrared band through Kirchhoff’s law that directional emissivity of a surface equals 1 minus its directional-hemispherical reflectance. However
this in-direct approach is not convenient because using Kirchhoff’s law means to assume isothermal condition
but most natural surface is not isothermal. In this paper
we extend a typical canopy model in VNIR band
the SAIL model
to TIR band by adding terms of thermal emission in the radiation transfer equations. Analytic solution of the radiation transfer equations is derived. This enables us to directly simulate the emission and radiation transfer process inside the horizontal homogeneous canopy which is a good approximation to many kinds of crops. Leaf angle distribution (LAD) can be simulated discretely
and vertical canopy structure is also easily handled. Simulation of our model indicates that these factors play important role in directional signature of the canopy radiance. The model can also be used in some flexible ways
which enable it to act as basic modular in higher level TIR model. Here
we give two examples. In the first example
we use this model to calculate multiple scattering inside canopy and derive component effective emissivity. In the second example
the result of our RT model is adjusted by a row-structured GO model to simulate the real structure of winter wheat canopy as well as the footprint of radiometer. Comparison with field measured data indicates that the horizontal homogeneous assumption is also not valid in real cases
so the better choice is to integrate RT and GO model together.