基于高分一号与Radarsat-2的鄱阳湖湿地植被叶面积指数反演  

Estimation of wetland vegetation LAI in the Poyang Lake area using GF-1 and Radarsat-2 Data

作　　者：许涛[1,2] 廖静娟[1] 沈国状[1] 王娟 杨晓慧[3] 王蒙[1,2] 

机构地区：[1]中国科学院遥感与数字地球研究所数字地球重点实验室,北京100094 [2]中国科学院大学,北京100049 [3]中国农业科学院农田灌溉研究所,河南新乡453002

出　　处：《红外与毫米波学报》2016年第3期332-340,共9页Journal of Infrared and Millimeter Waves

基　　金：国家自然科学基金项目(41401483)~~

摘　　要：叶面积指数(LAI)是衡量湿地生态系统健康状况的重要指标.根据鄱阳湖湿地植被生长密集、LAI动态范围大的特点,针对雷达数据的复杂散射机制,利用Freeman-Durden极化分解技术,定义了一种雷达植被指数,并考虑光学植被指数的饱和性,尝试将光学植被指数和雷达植被指数相结合,构建融合植被指数来估算植被LAI.通过实测数据和理论模型模拟数据与LAI的相关性分析,表明融合植被指数能有效地提高与LAI的相关性.利用融合植被指数、光学植被指数、雷达植被指数与LAI构建最佳拟合模型得出:光学微波融合植被指数能更准确地估算鄱阳湖湿地植被LAI.Leaf area index( LAI) is an important indicator of wetland ecosystem health. Poyang Lake wetland vegetations grow densely,with LAI of large dynamic range. Considering the complex scattering mechanisms of radar data,a radar vegetation index was defined. To overcome the saturation of the optical vegetation indices,a new integrated vegetation index using GF-1 and Radarsat-2 data was established for estimation of wetland vegetation LAI. The validation of measured data and theoretical model simulation showed that this integrated vegetation index is a good alternative to that using only the optical or radar observation. The best fitting models were built with optical vegetation indices,radar vegetation index,and the integrated vegetation index,respectively. The result indicates that the integrated vegetation index can improve predication accuracy for wetland vegetation LAI.

关 键 词：融合植被指数 叶面积指数 高分一号 RADARSAT-2 Freeman-Durden极化分解 鄱阳湖湿地 

分 类 号：TP79[自动化与计算机技术—检测技术与自动化装置]