基于植被指数的绿地信息提取的比较  

Comparative study in deriving green land based on vegetation indices

作　　者：胡晓雯[1] 曹爽[1] 赵显富[1] 

机构地区：[1]南京信息工程大学遥感学院,南京210044

出　　处：《南京信息工程大学学报（自然科学版）》2012年第5期420-425,共6页Journal of Nanjing University of Information Science & Technology（Natural Science Edition）

基　　金：南京信息工程大学科研基金(20070067)

摘　　要：运用遥感图像处理系统(ENVI)对快鸟(Quickbird)高分辨率遥感影像进行预处理,利用归一化差值植被指数(ND-VI)、归一化差异绿度指数(NDGI)、土壤调节植被指数(SAVI)和修正土壤调节植被指数(MSAVI)对南京市鼓楼区进行了绿地信息提取,通过Matlab软件比较了其灰度图像、直方图和二值图像,并分析其方差,在C语言的平台上进行了精度评定.实验结果表明:在该研究区中,SAVI、NDVI的绿地提取能力较好;ND-GI、MSAVI出现了明显的漏分、错分情况,但MSAVI在建筑物、植被边缘提取上表现出相对的优越性.The paper preprocesses Quickbird high-resolution sensing images based on ENVI and uses 4 kinds of vegetation indices, Normalized Difference Vegetation Index （ NDVI）, Normalized Differential Green Index （ NDGI ）, Soil Adjusted Vegetation Index（ SAVI）, and Modified Soil Adjusted Vegetation Index （MSAVI）to derive green land from Gulou district in Nanjing. Tacking the images with the programs of Matlab software, the paper analyses their gray image, histogram, binary image and variance and gives the result through C language. The experiments show that in this study area, SAVI and NDVI could derive green land well;mistakes and omissions appeared in NDGI and MSAVI deriving;MSAVI shows superiority in edge extraction of buildings and vegetation.

关 键 词：植被指数 Quickbird遥感影像 绿地信息提取 高分辨率 

分 类 号：TH71[机械工程—测试计量技术及仪器] TG803[机械工程—仪器科学与技术]