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Calibration of the CLAIR Model by Using Landsat 8 Surface Reflectance Higher-Level Data and MODIS Leaf Area Index Products

机译:使用Landsat 8表面反射高级数据和MODIS叶面积指数产品校准CLAIR模型

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This study proposes a method for the calibration of the semi-empirical CLAIR model, a simplified reflectance model used to estimate Leaf Area Index (LAI) from optical data. The procedure can be applied in case of lacking of both LAI field measurements and surface reflectance data by exploiting free of charge data as the novel high level Landsat 8 Operational Land Imager Surface Reflectance (OLISR) product and the MODIS LAI (MCD15A3H level 4 product). This last dataset was used as LAI reference within an iterative procedure based on the resampling, at the MODIS pixel size, of LAI estimated from OLISR data. The procedure generated LAI information consistent with the MCD15A3H LAI estimation. Lastly, the method was tested and statistically assessed in a territory characterized by an extremely heterogeneous and fragmented landscape (irrigation district "Sinistra Ofanto") located in the Apulia Region (Italy).
机译:这项研究提出了一种用于校准半经验CLAIR模型的方法,该模型是一种简化的反射率模型,用于根据光学数据估算叶面积指数(LAI)。如果缺乏LAI现场测量和表面反射率数据,则可以应用该程序,方法是利用免费数据作为新型高水平Landsat 8操作性陆地成像仪表面反射率(OLISR)产品和MODIS LAI(MCD15A3H 4级产品) 。在基于OLISR数据估算的MOI像素大小的LAI重采样的迭代过程中,该最后一个数据集用作LAI参考。该过程生成了与MCD15A3H LAI估计值一致的LAI信息。最后,对该方法进行了测试,并在位于意大利普利亚大区(Apulia Region)的一个极为异质且破碎的景观(灌溉区“ Sinistra Ofanto”)地区进行了统计评估。

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