归一化植被指数的土壤背景影响去除

摘要

Owing to the fact that canopy NDVI is disturbed by different types of soil background,the validity in using NDVI to monitor the crop condition has been deeply reduced.Therefore,this paper proposes two removal methods of soil background to NDVh It uses the wheat farmland in Lai'an county,Anhui province as the research area,uses the winter wheat in jointing stage under the background of different soil types (like paddy soil and Yellow-cinnamon soil) as the object,combines with measured wheat canopy spectrum and leaf area index,and uses the traditional overhead photograph to calculate the vegetation coverage.Then,it proposes two removal models of soil background to NDVI based on the theory of mixing spectral and verifies the proposed models.The study shows:both of the models can remove certain effects of soil;NDVI1T owns the better ability of extracting vegetation information and resisting soil noise;it shows a good fitting relationship between soil background removal models and NDVI andR2 are over 0.9.%植被冠层归一化植被指数(normalized difference vegetation index,NDVI)由于不同土壤背景的混入干扰,导致利用NDVI信息对作物长势监测等应用的有效性降低.以安徽省来安县小麦农田为研究区,以2种土壤类型(水稻土和黄褐土)背景下拔节期冬小麦为研究对象,采用实测小麦冠层光谱及叶面积指数(leaf area index, LAI)数据,利用传统的照相法求算植被覆盖度,基于混合光谱理论,提出2种NDVI土壤背景影响去除模型(NDVIT),对模型进行对比验证.研究结果表明:2种模型均可去除一定的土壤背景影响;采用信噪比的分析方法定量研究2种模型抵抗土壤噪声影响的能力,分析发现NDVI1T提取植被信息抗土壤噪声能力更佳;2种土壤背景影响去除模型和NDVI的拟合关系良好,相关关系R2均达到0.9以上.