首页 | 本学科首页   官方微博 | 高级检索  
     

基于最优波段组合的TM影像土地覆盖信息分类
引用本文:刘德儿,于海霞,兰小机,陈元增.基于最优波段组合的TM影像土地覆盖信息分类[J].金属矿山,2013,42(10):80-83.
作者姓名:刘德儿  于海霞  兰小机  陈元增
作者单位:1.江西理工大学建筑与测绘工程学院;2.赣州市城市规划设计院
基金项目:* 国家自然科学基金项目(编号:40971234),江西省教育厅科学研究项目(编号:GJJ13431),江西理工大学基金项目(编号:jxxj11012)。
摘    要:针对TM遥感影像光谱特征利用率不高,影响土地覆盖信息分类精度的问题,提出一种基于最优波段组合的分类方法。以赣州市章贡区2006年的TM遥感影像为研究对象,首先根据遥感影像的光谱特征和波段间的相关性计算最佳指数;其次根据研究区域特征,引入修正植被指数,并对原影像进行主成分分析,综合分析最佳指数、修正植被指数和前3个主成分量,认为PC3、RNDVI、Band1为最优波段组合。最后结合监督分类与非监督分类法对最优波段组合成的遥感影像进行分类,得到的整体分类精度为86.237 5%,kappa系数为0.825 3。

关 键 词:最优波段组合  最佳指数  修正植被指数  主成分分析  

Land Cover Information Classification Based on the Optimal Band Combination of TM Image
Liu De'er,Yu Haixia,Lan Xiaoji,Chen Yuanzeng.Land Cover Information Classification Based on the Optimal Band Combination of TM Image[J].Metal Mine,2013,42(10):80-83.
Authors:Liu De'er  Yu Haixia  Lan Xiaoji  Chen Yuanzeng
Affiliation:1.School of Architectural and Surveying Engineering,Jiangxi University of Science and Technology;2.Urban Planning and Design Institute of Ganzhou
Abstract:The accuracy of land cover classification is affected by the low utilization efficiency of the TM image spectral characteristics.Aimed at this issue,a classification method is proposed based on the optimal band combination.Taking the TM image in 2006 in Zhanggong district of Ganzhou as a study goal,the optimum index factor(OIF)is firstly calculated by the spectral characteristics of remote sensing image and the relation of bands.Then,the revised normalized difference vegetation index(RNDVI)is introduced according to the topographic feature in study region,and the original image is analyzed by principal component analysis(PCA).Through comprehensive analysis on the optimum index factor,the revised normalized difference vegetation index and three former principal components,it is concluded that the optimal band combinations are PC3,RNDVI and Band1.Finally,with combination of supervised classification and unsupervised classification,the composite remote sensing image is classified,obtaining that the overall classification accuracy is 86.2375% and the kappa factor is 0.8253.
Keywords:The optimal band combination  Optimum index factor(OIF)  Revise normalized difference vegetation index(RNDVI)  Principal component analysis(PCA)
点击此处可从《金属矿山》浏览原始摘要信息
点击此处可从《金属矿山》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号