基于HJ星CCD遥感数据的落叶阔叶林NDVI差值速率识别模型  

NDVI Difference Rate Recognition Model of Deciduous Broad-Leaved Forest Based on HJ-CCD Remote Sensing Data

作　　者：王龑[1,2] 田庆久[1,2] 黄彦[1,2] 魏宏伟[1,2] 

机构地区：[1]南京大学国际地球系统科学研究所,江苏南京210023 [2]南京大学江苏省地理信息技术重点实验室,江苏南京210023

出　　处：《光谱学与光谱分析》2013年第4期1018-1022,共5页Spectroscopy and Spectral Analysis

基　　金：国家科技重大专项(30-Y20A01-9003-12/13);高分应用综合数据库系统先期攻关项目(E0103/1112/10)资助

摘　　要：以安徽省滁州地区的落叶阔叶林为研究对象,基于2012年4月1日与5月4日HJ-CCD遥感影像数据,利用落叶阔叶林萌芽展叶期与花果期的归一化植被指数(NDVI)差值速率构建了落叶阔叶林识别模型,并有效地提取出落叶阔叶林的空间分布图,再结合野外实地考察和观测的样地位置信息对提取结果进行了验证和评价。研究表明所提出的落叶阔叶林NDVI差值速率提取方法的有效性,证实了环境星CCD数据在植被分类识别方面的可应用性。The present paper takes Chuzhou in Anhui Province as the research area,and deciduous broad-leaved forest as the research object.Then it constructs the recognition model about deciduous broad-leaved forest was constructed using NDVI difference rate between leaf expansion and flowering and fruit-bearing,and the model was applied to HJ-CCD remote sensing image on April 1,2012 and May 4,2012.At last,the spatial distribution map of deciduous broad-leaved forest was extracted effectively,and the results of extraction were verified and evaluated.The result shows the validity of NDVI difference rate extraction method proposed in this paper and also verifies the applicability of using HJ-CCD data for vegetation classification and recognition.

关 键 词：HJ星 多光谱遥感 落叶阔叶林 NDVI 

分 类 号：TP79[自动化与计算机技术—检测技术与自动化装置]