Review and prospect in change detection of multi-temporal remote sensing images

doi:10.11947/j.AGCS.2022.20220070

Abstract

Abstract: Change detection (CD), as one of the hot spots in the field of photogrammetry and remote sensing, is a technology branch with important research value in artificial intelligence (AI) systems. The rapid development and deep integration of the two subjects have made it possible to automatic and intelligent process the massive, complex and diverse remote sensing datasets. It has been widely used in many areas, such as resources monitoring, urban planning, disaster assessment, etc. With the development of the remote sensing and computing power, change detection is also evolving. This paper mainly analyzes and summarizes the current change detection methods from the perspectives of geometry and semantics. We focus on the utilization of geometric information and the feature fusion method of deep neural networks. Furthermore, the paper provides a summary of open datasets derived from different sensors, along with information related to change detection. Finally, we point out the challenges of the change detection and the future trends of the area are summarized and prospected.

Key words: photogrammetry, remote sensing images, multi-temporal, change detection, review

CLC Number:

P237

ZHANG Zuxun, JIANG Huiwei, PANG Shiyan, HU Xiangyun. Review and prospect in change detection of multi-temporal remote sensing images[J]. Acta Geodaetica et Cartographica Sinica, 2022, 51(7): 1091-1107.

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