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Systematic analysis of the LUT-based inversion of PROSAIL using full range hyperspectral data for the retrieval of leaf area index in view of the future EnMAP mission

机译:鉴于将来的EnMAP任务,使用全范围高光谱数据对基于LUT的PROSAIL反演进行系统分析,以检索叶面积指数

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The upcoming satellite mission EnMAP offers the highly relevant opportunity of retrieving information on the seasonal development of vegetation parameters on a regional scale based on hyperspectral data. This study aims to investigate the potential of retrieving leaf area index (LAI) information from hyperspectral images. The widely used PROSAIL model is applied to generate look-up-table (LUT) libraries, by which the model is inverted to derive LAI information. Different techniques for the LUT based inversion are tested, such as several cost functions, type and amount of artificial noise, number of considered solutions and type of averaging method. The optimal inversion procedure (laplace, median, 4% inverse multiplicative noise, 350 averages) is identified by validating the results against corresponding in-situ measurements (N = 330) of LAI, leading to robust results (R = 0.65, RMSE = 0.64).
机译:即将到来的卫星任务EnMAP为基于高光谱数据的区域尺度上的植被参数季节变化信息检索提供了高度相关的机会。这项研究旨在调查从高光谱图像中检索叶面积指数(LAI)信息的潜力。广泛使用的PROSAIL模型应用于生成查找表(LUT)库,通过该库,该模型可以反转以得出LAI信息。测试了基于LUT的反演的不同技术,例如几种成本函数,人工噪声的类型和数量,考虑的解决方案的数量以及平均方法的类型。最佳反演程序(拉普拉斯,中位数,4%逆乘性噪声,350个平均值)可通过对LAI的相应原位测量值(N = 330)进行验证来确定,从而得出可靠的结果(R = 0.65,RMSE = 0.64) )。

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