期刊文献+

土地利用/覆被变化遥感检测方法与应用分析 被引量:23

RS-Detection Methods for LUCC and Related Application Analysis
在线阅读 下载PDF
导出
摘要 随着我国经济建设的飞速发展,土地利用/覆被变化(LUCC)日新月异,如何快速、高效地获取变化信息已经成为LUCC研究的核心技术之一。本文以SPOT(Pan波段)影像和TM影像为例,对LUCC自动检测方法进行了探讨,并对光谱特征变异法、假彩色合成法、主成分分析法、图像代数法和波段替代法等方法进行了系统分析与比较。实践证明,在科学的图像处理的基础上,综合应用上述方法,能够高效、准确地自动检测出LUCC信息,具有传统的人工目视解译方法无法比拟的优势。 With the fast development of economic construction, LUCC are changing with each passing day in China, and how to acquire changing information has become one of the key technologies in LUCC research. Taking SPOT-Pan image and TM image as a case study, this paper discussed the methods of automatic detection for LUCC, and spectrum feature changing method, pseudo-color composition method etc. were analyzed and compared systemically. It is proved that the LUCC information can be detected efficiently and accurately by using the above methods and which are superior to the traditional comparing detection method by visual interpretation.
出处 《地球信息科学》 CSCD 2007年第3期116-122,共7页 Geo-information Science
基金 国家自然科学基金项目(40571010).
关键词 遥感 土地利用/覆被变化 自动检测 图像处理 RS, LUCC, automatic detection, image processing
  • 相关文献

参考文献9

二级参考文献49

  • 1张红,舒宁,刘刚.多时相组合分类法在土地利用动态监测中的应用[J].武汉大学学报(信息科学版),2005,30(2):131-134. 被引量:22
  • 2李全,李霖,赵曦.基于Landsat TM影像的城市变化检测研究[J].武汉大学学报(信息科学版),2005,30(4):351-354. 被引量:13
  • 3Ashbindu Singh. Digital change detection techniques using remotely-sensed data[J]. Int J Remote Sensing,1989,10:989.
  • 4Gopal S, Woodcock C. Remote sensing of forest change using artificial neural networks [J]. IEEE Transactions on Geoscience and Remote Sensing, 1996, 34:398.
  • 5Richard O D, Peter E H, David G S. Pattern classifica-tion second edition[M]. New York: Published by John Wiley and Sons Inc, 2001.
  • 6Hurn M A, Mardia K V. Bayesian fused classification of medical images[J]. IEEE Trans Geoscience and Remote Sensing, 1999, 37:1292.
  • 7Toth D, Aach T, Metzler V. Illumination-invariant change detection[J ]. 4th EE Southwest Symposium on Image Analysis and Interpretation, 2000.3-7.
  • 8Baronti S, Carla R, Sigismondi S, et al. Principal component analysis for change detection on polarimetric multitemporal SAR data [ J ].Geoscience and Remote Sensing Symposium, 1994,94(4) :2152-2154.
  • 9Qiu B, Prinet V, Perrier E, et al. Multi-block PCA method for image change detection[A]. Proceedings of the 12th International Conference on Image Analysis and Processing(ICIAP'2003)[C] ,2003.
  • 10Michael Collins, Sanjoy Dasgupta, Robert E. Schapire. A Generalization of Principal Component Analysis to the Exponential Family. NIPS'2001.

共引文献278

同被引文献249

引证文献23

二级引证文献127

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