Hydrology and Earth System Sciences www.hydrol-earth-syst-sci.net 1027-5606 1607-7938 14 8 2010 10.5194/hess-14-1499-2010 http://www.hydrol-earth-syst-sci.net/14/1499/2010/ http://www.hydrol-earth-syst-sci.net/14/1499/2010/hess-14-1499-2010.html http://www.hydrol-earth-syst-sci.net/14/1499/2010/hess-14-1499-2010.pdf 1499 1507 2010-08-10 Accurate LAI retrieval method based on PROBA/CHRIS data W. J. Fan fanwj@pku.edu.cn X. R. Xu X. C. Liu B. Y. Yan Y. K. Cui Institute of Remote Sensing and GIS, Peking University, Beijing, China International Institute for Earth System Science, Nanjing University, Nanjing, China Leaf area index (LAI) is one of the key structural variables in terrestrial vegetation ecosystems. Remote sensing offers an opportunity to accurately derive LAI at regional scales. The anisotropy of canopy reflectance, variations in background characteristics, and variability in atmospheric conditions constitute three factors that can strongly constrain the accuracy of retrieved LAI. Based on a hybrid canopy reflectance model, a new hyperspectral directional second derivative method (DSD) is proposed in this paper. This method can estimate LAI accurately through analyzing the canopy anisotropy. The effect of the background can also be effectively removed. With the aid of a widely-accepted atmospheric model, the influence of atmospheric conditions can be minimized as well. Thus the inversion precision and the dynamic range can be markedly improved, which has been proved by numerical simulations. As the derivative method is very sensitive to random noise, we put forward an innovative filtering approach, by which the data can be de-noised in spectral and spatial dimensions synchronously. 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