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• W2901225187 abstract "Global leaf area index (LAI) generally produced based on the satellite sensors with 1 km spatial resolution, such as the advanced very high resolution radiometer (AVHRR), moderate resolution imaging spectroradiometer (MODIS) and VEGETATION. At present, there isn't a LAI product estimated from the Chinese Feng Yun No.3 (FY-3) images. This study aims to generate a 10-day composite LAI product from FY-3A with a medium resolution spectral imaging (MERSI) at global scale in 2011. Making use of the land cover type as priori knowledge, the LAI for pure vegetation types was inversed from a lookup-table (LUT) based on an stochastic three-dimensional radiative transfer model (3D RTM). For the mixed water and vegetation types, LAI was inversed based on an improved linear decomposition method. The accuracy of LAI inversion from FY-3A MERSI was assessed by LAI field measurements from the Chinese ecosystem research network (CERN) in 2011." @default.
• W2901225187 created "2018-11-29" @default.
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• W2901225187 date "2018-07-01" @default.
• W2901225187 modified "2023-09-27" @default.
• W2901225187 title "A Integrated Inversion Method for Estimating Global Leaf Area Index from Chinese FY-3A Mersi Data" @default.
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• W2901225187 doi "https://doi.org/10.1109/igarss.2018.8519343" @default.
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