1. State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing 100101, China 2. Center for Spaceborne Remote Sensing Demonstration, China National Space Administration, Beijing 100101, China 3. Graduate University of Chinese Academy of Sciences, Beijing 100039, China 4. Institute of Mechanics, Chinese Academy of Sciences, Beijing 100190, China 5. Beihang University, Beijing 100191, China
Abstract：The present study used the PROSAIL forward model to simulate vegetation canopy spectrum, introducing blue and green bands to amend the effects of atmosphere and soil background, and constructing HuanJing vegetation Index (HJVI) to avoid premature saturation. Based on ground observation data of different typical winter wheat, we established HJVI-LAI long time series inversion models and implemented different varieties cross-validation to the models. The results show that the LAI inversion model of HJVI has higher precision than similar vegetation index model, has good universality, and can be applied to remote sensing multi-temporal winter wheat growth monitoring and LAI inversion.
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