植被生化组分的遥感反演方法研究

Inversion of Vegetation Biochemicals by Remote Sensing

从反演物理模型提取植被生化组分含量的角度 ,分别在叶片和冠层水平探讨了反演生化参量的方法。在叶片水平 ,利用实验室测量光谱数据 ,较为准确地提取了水分和叶绿素含量 ,通过比较真实光谱数据与利用模型和真实参数模拟的光谱数据 ,得出如下结论 :模型能否准确描述某个参数的作用是能否真正准确反演该参数的关键。在模拟的冠层水平 ,基于多阶段反演思想 ,采用了分步反演策略 ,最终较为准确地反演了生化参数。

The knowledge of foliar biochemical concentration provides us a deep understanding of many esosystem functions, such as photosynthesis, nutrient cycling, and so on. Generally speaking, two ways of biochemical concentration estimation by remote sensing, namely statistical regression and physical model inversion, have been studied in parallel. There are many limitations in statistical regression method. So, direct inversion of physical model is desired. From the view of inverting physical models to retrieve biochemical concentration, inversion methods were analyzed at leaf and canopy level respectively. At leaf level, using laboratory measured spectra and PROSPECT model, water and chlorophyll concentration were inverted quite accurately. Through comparing true spectra with reconstructed spectra using true inputs, results were got as that accurate inversion of some parametes are based on the model which should describe the effect of this parameter accurately. At simulated canopy level, preliminary inversion of biochemical content directly from canopy spectra showed poor accuracy especially for chlorophyll. Based on the idea of multi stage inversion, following inversion was decomposed into 2 parts: first from canopy spectra to leaf spectra, then from leaf spectra to biochemical content. By this step by step inversion strategy, biochemical concentration was inverted accurately ultimately.It should be noted that in this paper the canopy spectra was simulated by model, further testifying with real spectra is needed which we will take into consideation in near future. Also other inversion algorithms than iterative optimization will be tested.