植被生理生化垂直分布信息遥感辐射传输机理与反演研究

At present, passive optical remote sensing has high accuracy only in the inversionof horizontal direction parameters, but it is difficult to invert characteristic parameters with vertical direction distribution, such as leaf area density distribution and the vertical distribution of biochemical components. Combination of passive optical remote sensing and Lidar waveform information is an effective method to solve this problem. Though the establishment of vegetation radioactive transfer equation has more than 30 years, it mainly focused on passive optical remote sensing. Under the conditions of active optical remote sensing, the incident boundary conditions change. Thus, the appropriate correction for the model must be made to include the phase characteristics in the equation. In this project, we will comprehensively use the direction, spectral and phase information of optical remote sensing, and integrated active and passive optical remote sensing technologies, such as multi-angle, hyperspectral and Lida waveform. Through model synergy, algorithm optimization, information fusion and experimental verification, we explored intensity characteristics of laser radar echo at different vegetation height, and the response of subsegment spectral features of different observation angle to vegetation three-dimensional environment. We discussed the quantitative inversion mechanism about radioactive transfer process and the vertical distribution of physiological and biochemical parameters of vegetation under complex surface conditions. We believe that this project will provide a strong impetus to the development of radioactive transfer theory of optical remote sensing, promote more vegetation parameters from the two-dimensional oriented towards the three-dimensional quantitative inversion, andmeet the needs of the eco-environmental assessment and management.

目前，被动光学遥感只是在参数总量反演具有较高的精度，但是对于具有垂直方向分布的特征参数，例如叶面积密度分布、生化组分垂直分布等均难以进行反演，必须结合激光雷达的波形信息解决这一难题。植被辐射传输方程的建立已有30多年，主要针对被动光学遥感。但在主动光学遥感条件下，其入射边界条件发生了变化，相位特性也同时必须列入方程的考虑之中，因此模型必须做相应修正。本项研究将综合利用光学遥感的方向、光谱和相位信息，融合多角度、高光谱和波形激光雷达等主被动光学遥感技术，通过模型协同、算法优化、信息融合、实验验证，探索植被不同高度处激光雷达回波强度特征及不同观测角度的细分光谱特征对植被立体环境的响应情况，研究复杂地表覆盖下辐射传输过程和植被生理生化参数垂直分布信息定量反演机制。相信本研究将有力地推动光学遥感辐射传输理论的发展，促进更多植被参数从二维化走向三维化的定量反演，满足生态环境评价和管理。

本课题在理论模型模拟和遥感试验基础上，针对植被生理生化参数垂直异质性分布特征，开展了主被动光学遥感反演机理研究，综合高光谱、多角度和波形激光雷达等主被动光学遥感技术，通过模型协同、算法优化、信息融合、实验验证，探索了植被不同高度处激光雷达回波强度特征及不同观测角度的细分光谱特征对植被立体环境的响应情况，研究了植被生理生化参数垂直分布信息定量反演机制。基于辐射传输理论模型单次散射和激光雷达方程，针对典型植被场景，综合考虑复杂地表森林结构和森林类型的空间分布特征，优化了基于混沌介质的高光谱激光雷达模型，建立了针对准确三维场景的连续谱激光脉冲光源复杂植被辐射传输模型。基于高光谱激光雷达的实测数据集、PROSPECT合成数据集、ANGERS公用数据集，开展了结构参数和生化参数对光谱的影响分析，促进了高光谱全波形脉冲激光雷达几何和辐射定标方法研究，基于红边通道的不变性，提出了高光谱全波形激光雷达脉冲信号延迟校正方法，针对现有仪器几何定标精度小于25mm。针对辐射差异，提出了基于物理模型的激光雷达入射角效应校正算法。基于高光谱激光雷达仪器原型，开展了生理生化参数垂直分布一体化提取方法研究，成功反演了叶绿素、氮素等的三维分布。初步形成了高光谱激光雷达系统数据处理关键技术，包括几何校正、辐射校正、点云数据处理算法等，解决了兼具点云、波形与光谱信息的海量数据在数据组织中的瓶颈问题。实现了高光谱激光雷达数据高精度辐射定标方法研究；高光谱激光雷达波形分解与距离解算方法研究和联合空谱信息的高光谱激光雷达点云预处理方法研究。.课题按时完成了任务书规定的各项研究内容，完成了各项考核指标，推动了光学遥感辐射传输理论的发展，实现了三维数据的生成、存储、组织和有序管理，取得了一系列创新成果，并产生了一定的经济社会效益，促进了植被参数定量反演从二维化走向三维化。.

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