Modeling effective directional emissivity of row crop

Land surface temperature (LST) is a key geophysical parameter that reflects the combined effects of land surface energy and-radiation balance. Remote sensing of LST, requires better a understanding of the directional patterns of thermal emission from heterogeneous land surfaces. Recently, semi-empirical, linear, kernel-driven models have been rather successfully applied to describe observed directional patterns of land surface reflectance, but none is special for directional radiometric of row crop. Row crop structure is a very important type in China. Row crop structure is a major objective for remote sensing. A geometric model of Kimes predicts the thermal infrared response of a sensor as a function of sensor view angle, component temperature and geometry structure of the canopy. The model serves as a sound mathematical basis for interpreting remotely sensed data from row crops, but it doesn\´t consider the multi-scattering between the crops and soil. We developed a geometrical optical model of effective directional emissivity for row crop. We defined an average temperature and effective or equivalent directional emissivity. Effective directional emissivity consists of three parts: emissivity due to directly radiation, multi-scattering and difference of component temperature. We calculated the emissivity by two-step approximation. The first step, we just consider the multi-scattering among crops, crops and the soil beneath the crop; the second step, we consider the multi scattering between the crops and the soil between the row crops similar to the "V" shape valley. This model can be rather simple to retrieve component temperature of remote sensing pixel