复杂地形下植被遥感辐射传输建模及叶面积指数反演研究

Mountainous regions take up about two thirds of the land area of China, and the rugged terrain is one of the main characteristics of the land surface of China. Rugged terrains can change the sun-target-sensor geometry and the multiple scattering effects between different slopes, which significantly influences the remote sensing signals and further influences the accuracy of the leaf area index (LAI) inversions. The whole radiation transfer process over mountainous vegetated regions include three parts: the direct solar radiation within the slope, the diffuse sky scattering and the multiple scattering radiation among the slopes. The innovation of this research includes: (1) the current canopy reflectance models cannot characterize the whole radiation transfer process of the three parts, or can only be applied to single vegetation type, e.g., cropland or forest, which is not beneficial for the retrievals of LAI over rugged terrains with high accuracy. This project will develop an analytical full radiative transfer model for vegetation canopies over rugged terrains, which is especially suitable for the LAI inversion of multiple vegetation types, including the mixed forest. (2) The current several global LAI products did not account for the applicability of the forward model and the retrieval algorithm over rugged terrains. This project will introduce the digital elevation model (DEM) into the current LAI inversion algorithm, and develop the new LAI inversion algorithm which has the physical meaning and is effective for the mountainous vegetated areas. This shows the theoretically novel and promising in the future applications.

山地约占我国陆地面积的三分之二，地形复杂是我国国土的基本特征之一。地形起伏通过改变太阳-坡面-传感器成像几何、坡面间多次散射等辐射传输过程，显著影响遥感信号强弱，并直接影响遥感反演叶面积指数(Leaf area index, LAI)的精度。完整的山地植被辐射传输过程包括坡面冠层内太阳直射辐射、漫散射天空光、坡面间交叉辐射三部分。本研究的创新之处体现在：1) 到目前为止，并没有一个同时适合于山地连续/离散植被(含混交林)等多种植被类型LAI反演的具有普适性的模型。本项目以随机辐射传输理论为基础，发展复杂地形下辐射传输过程考虑完整、适合多种植被类型LAI反演的普适性的山地冠层反射率模型，具有一定的理论创新性；2) 现有的十余套全球LAI产品，暂未对正向模型与反演算法在复杂地形下的适用性单独考虑。本项目将通过建立的山地植被模型，引入DEM地形信息，为山地LAI反演提供具有明确物理机理的新方法。

复杂的地形与结构是制约叶面积指数(Leaf area index, LAI)遥感反演精度的瓶颈之一，建立精准的正向辐射传输模型是提高后续反演结果的理论基石。本项目以认识厘清复杂地形对辐射传输过程与叶面积指数反演的影响为总体目标，（1）发展了适合于复杂植被结构、易于参数反演的SIP植被二向性反射统一模型：基于光谱不变理论，构建了同时适合于连续、离散多种植被类型，适合于LAI反演的解析稳健的植被辐射传输统一模型；（2）发展了适合于我国北方生态交错区的RTEC植被二向性反射模型：由于相邻森林和农田斑块之间的相互遮蔽和遮挡作用，研究了破碎的生态交错区的光谱非线性混合；（3）定量分析了复杂地形对叶面积指数反演的影响：以DART三维辐射传输模型生成的多角度观测数据集为基础，分析了坡度、坡向等复杂地形对LAI反演与地表二向性反射率的影响。依托于本项目，共发表SCI论文5篇，其中RSE、IEEE TGRS两大遥感主流期刊3篇。项目的研究成果为山地的结构参数反演提供了参考价值与理论方法。