Retrieving LAI of Winter Wheat Based on Sensitive Vegetation Index by the Segmentation Method
[ Objective ] The method of inversion leaf area index (LAI) using a single vegetation index (VI) is influenced by different degrees of saturability and soil background. This paper proposed a method choosing sensitive vegetation index by the segmentation method to form optimal VI combination, and to improve the accuracy of LAI inversion. [Method] In this study the ACRM radiation transmission model was used to simulate data, and the ground measured spectrum data were obtained. The study analyzed soil sensitivity and saturability about the common vegetation index to determine the segment point of LAI, and chose the best vegetation index based on segment point of LAI to form a combination VI for achieving the final inversion of the LAI. This method was also used in the regional winter wheat LAI inversion application with the Landsat5 TM data. [Result] The analysis showed that, LAI = 3 was the more appropriate segment point, and the use of vegetation index segment combination OSAVI (LAI ≤3) + TGDVI (LAI>3) partly overcame soil factors and the saturation problems. The joint inversion results were significantly superior to the single vegetation index retrieval accuracy. [Conclusion] LAI was effectively inversed with the higher accuracy bychoosing the best vegetation index through the segmentation method.
winter wheatleaf area index (LAI)vegetation indexsegmentation inversionremote sensing
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万方数据
维普
