基于SAIL模型的多角度多光谱遥感叶面积指数反演

随着多角度传感器的陆续出现及植被遥感传输机理研究的深入,多角度遥感逐渐成为地表信息反演的热点问题.以SAIL冠层反射率模型为基础,通过联合多角度和多光谱数据,可以从物理机理角度进行植被叶面积指数(LAI)反演的应用研究.首先通过计算得到多角度多光谱遥感影像的角度信息,并经6S模型纠正后得到多光谱多角度植被冠层反射率数据.然后将PROSPECT模型模拟出的植被叶片反射率和透过率,以及多角度观测数据、LAI和其它实测数据输入SAIL模型,模拟得到了多角度多光谱冠层反射率,进而建立多角度多光谱冠层反射率与LAI的查找表.最后,将影像的多角度多光谱冠层反射率与查找表进行匹配,实现植被LAI的反演.最后对反演结果进行了验证和分析,结果表明反演精度较高,误差均在合理范围之内.

Inversion of LAI based on SAIL model with multi-angle and multi-spectral remote sensing data

Leaf area index (LAI) is one of the key ecological parameters and can be widely used in crop monitoring and yield estimations. Although researchers have already worked out some retrieval algorithms of LAI, there is still a long way to go, for instance, retrieval accuracy and adaptability by single remote sensing sensor data. As a hotpot remote sensing technology, multi-angle remote sensing has been proved great potential on LAI inversion. Using multi-angle and muhi-spectral remote sensing data, and based on SAIL bidirectional model, this paper explores a series of researches on inversion of LAI. The multi-angle and muhi-spectral remote sensing data, and other ground data were get from "Remote Sensing and Ground-based Experiment in the Heihe River Basin". The LOPEX93 da-tabase is employed to identify the input value of PROSPECT model. Firstly, the paper computes observation angle for remote sensing data and use 6S (Second Simulation of the Satellite Signal in the Solar Spectrum) to ensure the accuracy of atmospheric correction, and obtain multi-angle and multi-spectral Canopy Reflectance (CR) from re-mote sensing images. The values of leaf parameters (leaf mesophyll structure N, chlorophyll a + b, concentration Cab, water depth Cw) are used to simulate the PROSPECT model, and leaf reflectance and transmittance are re-trieved from the PROSPECT model. The canopy parameters (average leaf inclination angle, LAD, LAI and so on) and the output of the PROSPECT model (leaf reflectance and transmittance) are used as the input of the SAIL model. Then, based on simulations using the SAIL bidirectional canopy reflectance model coupled with the PROS-PECT leaf optical properties model, the paper constructs a look-up table (LUT) which describes the relationship of multi-angle and multi-spectral CR with LAI. Finally, LAI can be retrieved from LUT by matching CR with LAI. The inversion results are validated with field data, and some error sources are found out.