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A Temporally Integrated Inversion Method for Estimating Leaf Area Index From MODIS Data

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5 Author(s)
Zhiqiang Xiao ; State Key Lab. of Remote Sensing Sci., Beijing Normal Univ., Beijing, China ; Shunlin Liang ; Jindi Wang ; Jinling Song
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Multiple leaf area index (LAI) products have been generated from remote-sensing data. Among them, the Moderate-Resolution Imaging Spectroradiometer (MODIS) LAI product (MOD15A2) is now routinely derived from data acquired by MODIS sensors onboard Terra and Aqua satellite platforms. However, the MODIS LAI product is not spatially and temporally continuous and is inaccurate in many areas for some vegetation types. In this paper, a new algorithm is developed to estimate LAI from time-series MODIS reflectance data (MOD09A1). A radiative-transfer model is coupled with a double-logistic LAI temporal-profile model, and the shuffled complex evolution optimization method, developed at the University of Arizona, is used to estimate the parameters of the coupled model from the temporal signature in a given time window. Preliminary analysis using MODIS surface-reflectance data at flux sites was performed to validate this method. The results show that the new algorithm is able to construct a temporally continuous LAI product efficiently, and the accuracy has been significantly improved over the MODIS LAI product as compared to field-measured LAI data.

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Geoscience and Remote Sensing, IEEE Transactions on  (Volume:47 ,  Issue: 8 )