A REVIEW OF MULTI-TEMPORAL REMOTE SENSING DATA CHANGE DETECTION ALGORITHMS
A REVIEW OF MULTI-TEMPORAL REMOTE SENSING DATA CHANGE DETECTION ALGORITHMS
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发表时间：
2008
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通讯作者：
Jianya Gong;Haigang Sui;Guorui Ma;Qiming Zhou
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作者：
Jianya Gong;Haigang Sui;Guorui Ma;Qiming Zhou
地表变化信息在局部、区域和全球资源环境监测中的作用越来越重要。大量的过去和现在的遥感图像的收集使得有可能分析环境要素的时空格局和人类活动的影响，在过去的几十年。30.关于遥感变化探测和监测方法的研究已得到广泛报道。本文综述了各种检测方法，并得出了许多有益的结论。本文在前人分类方法的基础上，从本质上将变化检测方法分为直接比较法、分类法、面向对象法、模型法、时间序列分析法、可视化分析法和混合法七类。同时，在前处理中，讨论了几何校正和辐射校正的作用和方法，在精度评定中，将现有的方法归纳为外检和内检，并重点讨论了如何获取地面真值。最后讨论了变化检测所面临的挑战和可能的应对措施。
: Change information of the earth’s surface is becoming more and more important in monitoring the local, regional and global resources and environment. The large collection of past and present remote sensing imagery makes it possible to analyze spatio-temporal pattern of environmental elements and impact of human activities in past decades. Research has been widely reported on methodology of remote sensing change detection and monitoring. The present reviews have assorted the detection approaches and drawn many useful conclusions. Based on the former classification methods, this article classifies change detection methods from its essence into seven groups, including direct comparison, classification, object-oriented method, model method, time-series analysis, visual analysis and hybrid methods. At the same time, in pre-processing, the effect and methods of geometric correction and radiometric correction is discussed, and in accuracy assessment, this paper summarize the present methods into exterior check and interior check and emphasis on that how to get the ground truth. The challenges that the change detection is currently facing and possible counter measures are also discussed.