期刊文献+

高分辨率遥感影像土地利用变化检测方法研究 被引量:34

A Study of Land Use Change Detection Based on High Resolution Remote Sensing Images
在线阅读 下载PDF
导出
摘要 提出一种利用高分辨率遥感影像进行土地利用变化检测的方法。以土地利用图为辅助数据,通过土地利用图和遥感影像的配准套合,获取影像像斑;同时,对遥感影像进行基于像素的监督分类,获取概略的类别图;再根据像斑内像素的类别编码完成子像斑的划分。以子像斑为影像分析的基本单位提取特征,以相关系数为相似性测度衡量不同时期子像斑的特征相似性,用ROC曲线(接受者操作特性曲线)代替经验选取的方法自动获取变化阈值,确定像斑是否发生变化。以武汉市区局部QuickBird 2002年和2005年多光谱影像、相同地区2002年1∶10 000土地利用图为实验数据进行了算法的实验,结果显示绝大部分的变化区域都可以被提取出来,实验方法可行。 An approach to land use change detection by using high resolution remote sensing images is put forward in this paper.With the help of GIS land use map,image objects can be obtained by the matching of land use map and remote sensing images in the same region.Meanwhile pixel-based supervised classification is conducted for each image so that each pixel has its own class code.Then image subsegments can be obtained based on the image segment and the class code of each pixel within it.Image subsegments can be regarded as the basic units for feature extraction.Correlation coefficient is used for detecting changes between the images gotten from different time periods,and instead of the empirical selection,the change threshold is founded automatically by using ROC curve(receiver operating characteristic curve).Two multispectral Quickbird images obtained in 2002 and 2005 respectively and a 1∶ 10 000 land use map of 2002 in the same region were used in the experiment.This study area is located in Wuhan City and the result shows that most land use changes can be detected,and hence this approach is effective.
出处 《国土资源遥感》 CSCD 北大核心 2012年第1期43-47,共5页 Remote Sensing for Land & Resources
基金 湖北省自然科学基金重大项目(编号:2006ABD003) 中央高校基本科研业务费专项资金(编号:3101009)共同资助
关键词 变化检测 土地利用 面向对象 高分辨率 遥感 多源数据 change detection land use object based high resolution remote sensing multisource data
  • 相关文献

参考文献5

  • 1Blaschke T.Object Based Image Analysis for Remote Sensing[J].ISPRS Journal of Photogrammetry and Remote Sensing,2010,65(1):2-16.
  • 2舒宁.关于遥感影像处理分析的理论与方法之若干问题[J].武汉大学学报(信息科学版),2007,32(11):1007-1010. 被引量:20
  • 3Yitzhaky Y,Peli E.A Method for Objective Edge Detection Evalua-tion and Detector Parameter Selection[J].IEEE Transactions onPattern Analysis and Machine Intelligence,2003,25(8):1027-1033.
  • 4杨朝辉,陈鹰.基于ROC融合准则的SAR边缘检测算法[J].光电子.激光,2010,21(7):1053-1057. 被引量:7
  • 5Chen Z Q,Hutchinson T C.Urban Damage Estimation Using Statis-tical Processing of Satellite Images[J].Journal of Computing inCivil Engineering,2007,21(3):187-199.

二级参考文献20

  • 1舒宁.通用型遥感图像理解专家系统的研究[J].武汉测绘科技大学学报,1996,21(2):145-149. 被引量:6
  • 2李晖晖 郭雷 刘坤.基于Curvelet变换的SAR与可见光图像融合研究.光电子.激光,2008,19(4):542-545.
  • 3Touzi R, Lopes A, Bousquet P. A statistical and geometrical edge detector for SAR Images[J]. IEEE Transactions on Geoscience and Remote Sensing,1988,26(6) :764-773.
  • 4Tupin F, Maitre H, Mangin J,et al. Detection of linear features in SAR images: application to road network extraction [J]. IEEE Transactions on Geoscience and Remote Sensing, 1998, 36(2) :434-453.
  • 5Oliver C J, Blacknell D,White R G. Optimum edge detection in SAR [J]. IEE ProccRadar, Sonar Navig., 1996,143 ( l ) : 31- 40.
  • 6Webb G I, Ting K M. On the application of ROC analysis to predict classification performance under varying class distribution[J]. Machine Learning, 2005,58 ( 1 ) : 25-32.
  • 7Ganugapati S S,Moloney C R. A ratio edge detector for speckled images based on maximum strength edge pruning[A]. Proceedings of the International Conference on Image Processing [C]. Washington :IEEE Computer Society, 1995,165-168.
  • 8Yitzhaky Y, Peli E. A method for objective edge detection evaluation and detector parameter selection[J]. IEEE Trans. Image Processing, 2003,25(8) : 1027-1033.
  • 9Kraemer H C. Evaluating medical tests:objective and quantitative guidelines[M]. Newbury Park,Calif. :Sage Publications, 1992.
  • 10Zhu Q. Efficient evaluations of edge connectivity and width uniformity[J]. Image and Vision Computing, 1996,14(1) : 21-34.

共引文献25

同被引文献347

引证文献34

二级引证文献323

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部