植被冠层热辐射方向性解析模型与组分温度反演

As the direct driving force in the exchange of long-wave radiation and hydrological cycle, land surface temperature (LST) is one of the most important parameters in the physical processes of surface energy and water balance at local through global and regional scales. The retrieval accuracy of land surface temperature (1K) depends on the accurate directional thermal radiation model. In this study, the vegetation-soil mixed pixel was chosen as study object, the physical mechanism of multi-scattering among different components in thermal band is studied firstly, and multi-scattering model based on the Law of energy conservation will be introduced to thermal band, then the analytical multi-scattering model of directional emissivity for the canopy should be derived. Combined with the matrix model of thermal radiation, the analytical model of directional thermal radiation for vegetation-soil mixed pixel can be established; the model can apply to not only continuous vegetation but also discrete vegetation. Based on the model, the retrieval method of vegetation and soil component temperature should be studied using multi-angel thermal radiance. At last, the row crop would be chosen as an example; the component temperature should be retrieved using airborne sensor (WiDAS) and satellite borne sensor (AATSR). To validate the model, field measurements of the thermal radiation must also be conducted simultaneously.

陆面温度是驱动全球及区域长波辐射、水分循环等过程的关键参数，准确遥感陆面温度是全球及区域能量平衡、水分循环等研究的迫切需求。热辐射方向性模型是决定陆面温度反演的关键，高精度的方向性发射率才能满足陆面温度反演精度1K的要求。本研究选择植被冠层为主要研究对象，从研究热红外波段植被-土壤体系内部多次散射机理出发，将基于能量守恒理论的冠层多次散射模型引入热红外波段，给出植被-土壤体系发射率多次散射项的解析表达。并将在此基础上结合热辐射矩阵模型构建全新的热辐射方向性解析模型，以适用于离散和连续等多种类型植被冠层。进而深入研究利用多角度热红外数据反演植被和土壤组分温度的方法。最终将以行播作物为例，应用机载WiDAS数据和星载AATSR数据，并结合可见光数据，实现基于多源数据的植被土壤组分温度反演,并用地面同步观测进行验证。

陆面温度是驱动全球及区域长波辐射、水分循环等过程的关键参数，准确遥感陆面温度是全球及区域能量平衡、水分循环等研究的迫切需求。热辐射方向性模型是决定陆面温度反演的关键，高精度的方向性发射率才能满足陆面温度反演精度要求。本研究选择植被土壤体系为主要研究对象，为了定量描述热红外波段植被-土壤体系内部多次散射机理，将再碰撞概率引入热红外波段，给出了基于能量守恒理论的热红外植被-土壤体系发射率多次散射项的解析表达，建立了热辐射方向性解析模型（CE-P）。并将在此基础上结合热辐射矩阵表达式构建全新的热辐射方向亮温解析模型（CBT-P）。并引入聚集指数，使模型适用于离散和连续等多种类型植被冠层。进而针对Sentinel-3传感器，建立了利用多角度热红外数据反演植被和土壤组分温度的方法。最终以行播冬小麦为例，应用Sentinel-SLSTR可见光多波段数据和热红外多角度数据，实现了植被土壤组分温度反演，并用地面同步观测进行验证。研究结果为蒸散发计算、病虫害防治等相关领域提供更高精度的植被和土壤温度产品。