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遥感技术与应用  2016, Vol. 31 Issue (6): 1107-1113    DOI: 10.11873/j.issn.1004-0323.2016.6.1107
数据与图像处理     
基于环境卫星数据的沿海滩涂地物类型分类的随机森林方法
王艳楠1,王健健1,龚健新1,袁帅1,刘辉1,罗文2,3





(1.南京师范大学虚拟地理环境教育部重点实验室,江苏 南京 210023;
2.江苏省地理环境演化国家重点实验室培育建设点,江苏 南京 210023;
3.江苏省地理信息资源开发与利用协同创新中心,江苏 南京 210023)
Detection of Coastal Tidal Flat Using the Rrandom Forests Method and HJ Satellite Images
Wang Yannan1,Wang Jianjian1,Gong Jianxin1,Yuan Shuai1,Liu Hui1,Luo Wen2,3
(1.Key Laboratory of Virtual Geographic Environment (Nanjing Normal University),
Ministry of Education,Nanjing 210023,China; 2.State Key Laboratory Cultivation Base
of Geographical Environment Evolution (Jiangsu Province),Nanjing 210023,China;
3.Jiangsu Center for Collaborative Innovation in Geographical Information Resource
Development and Application,Nanjing 210023,China)
 全文: PDF(4700 KB)  
摘要:

基于环境卫星遥感影像,利用随机森林数据自适应探测特性,构建了面向沿海滩涂区域的地物类型分类方法,并以大丰为例进行了实证分析,探讨了基于随机森林方法的滩涂分类的参数选择与精度分析。结果显示:基于随机森林的沿海滩涂地物分类方法分类精度较传统监督分类(平行管道法\,最小距离法和最大似然法)精度提高明显,且具有很好的分类稳定性。

关键词: 随机森林遥感影像沿海滩涂地物分类    
Abstract:

Taking advantage of the adaptive detection feature of the random forests method,a classification method for coastal tidal flat area has been developed on basis of the HJ satellite images.Two typical areas covering coastal tidal flats,namely the ecological demonstration area of coastal tidal flats and the elk reserve,in the city of Dafeng,Jiangsu Province were selected in this study to showcase the classification effectiveness.The parameter settings and its accuracy were discussed.The results show that the random forests method performs obviously better than other traditional supervised classification methods such as parallelepiped,minimum distance,and maximum likelihood methods,and presents high stability in classification performance.

Key words:      Random forests    Remote sensing image    Coastal tidal flat    Classification
收稿日期: 2015-11-24 出版日期: 2016-12-30
:  TP 75  
基金资助:

国家科技支撑项目(2012BAC07B01),国家自然科学基金项目(41571380),江苏省测绘地理信息科研项目资助(JSCHKY201509)。

通讯作者: 罗文(1986-),男,湖北荆州人,博士后,主要从事GIS方面的研究。Email:luow1987@163.com。   
作者简介: 王艳楠(1992-),女,北京人,硕士研究生,主要从事环境遥感方面的研究。Email:wangyn_1992@163.com。
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引用本文:

王艳楠,王健健,龚健新,袁帅,刘辉,罗文. 基于环境卫星数据的沿海滩涂地物类型分类的随机森林方法[J]. 遥感技术与应用, 2016, 31(6): 1107-1113.

Wang Yannan,Wang Jianjian,Gong Jianxin,Yuan Shuai,Liu Hui,Luo Wen. Detection of Coastal Tidal Flat Using the Rrandom Forests Method and HJ Satellite Images. Remote Sensing Technology and Application, 2016, 31(6): 1107-1113.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2016.6.1107        http://www.rsta.ac.cn/CN/Y2016/V31/I6/1107

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