A Four-Component Parameterized Directional Thermal Radiance Model for Row Canopies
Kun Li, Yonggang Qian, Ning Wang, Wan Li, Shi Qiu, Lingling Ma, Chuanrong Li, Dexin Sun, Yinnian Liu, Ni Li
Abstract
Directional brightness temperature (DBT) acquired by remote sensing instruments plays a significant role in characterizing the directional anisotropy of land surface, especially for row canopies. The difference between shaded vegetation and sunlit vegetation is ignored in the existing models. In this article, a four-component parameterized directional thermal radiance model (FCPMod) has been proposed to describe the DBT of the row canopy by considering the four components including the sunlit/shaded soil and sunlit/shaded leaf, the improved multiple scattering within the canopy, and the sensor’s field of view (FOV). First, the sensor’s FOV is divided into many tiny rectangles along the row direction and the probabilities of four components in each tiny rectangle are estimated based on the radiative transfer (RT) theory and the bidirectional gap probability. Second, the DBTs are weighted by the four components’ probabilities and brightness temperatures of tiny rectangles. Third, a modified multiple scattering model is proposed to improve the modeling accuracy by considering the contribution of the multiple scattering radiance between soil and canopy. The sensitivity analysis results show that the proposed method performed well compared to the FRA97 model proposed by François <i>et al.</i> (1997) over continuous canopy and the RT model (FovMod) proposed by Ren <i>et al.</i> (2013) over row canopy. Finally, the field validations on a maize row canopy show that the proposed FCPMod performed better than about 0.4 K compared with the FovMod.