标题：A novel multiple change detection approach based on tri-temporal logic-verified change vector analysis in posterior probability space

入藏号：WOS:000811375200001

中国科学院文献情报中心期刊分区：地球科学1区TOP（2022）

本校作者： 王欣；范宣梅

来源出版物：INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION 卷: 111 文献号: 102852

出版年：2022

第一地址： 成都理工大学

关键词：Change detection；Land cover；Change vector analysis；Posterior probability；Tri-temporal images images

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摘要：Detailed land cover change trajectory offers a better opportunity for understanding the dynamic of land surface process. However, change information contained in training samples, which are usually difficult to obtain, needs to be provided in advance to achieve such goal within a complex scenario. A novel multiple change detection approach, namely Tri-temporal Logic-verified Change Vector Analysis (TLCVA) in posterior Probability Space (TLCVAPS), was proposed in this paper. It removes the dependence on change class information contained in training samples, while reducing the detection errors by taking change logic into account for the first time. The proposed approach consists of three steps, including: (1) change vector produced in posterior probability space, (2) binary change detection via TLCVA, and (3) change trajectory identification through combining change vector angle comparison and logic verification in change pattern. We applied the proposed approach on three tritemporal datasets obtained in Nanjing, Xianning, and Zhenjiang, China, respectively. The results confirmed the superiority of TLCVAPS in comparison with state-of-the-art multiple change detection methods with the same prior knowledge.

文章链接地址: https://www.sciencedirect.com/science/article/pii/S1569843222000541?via%3Dihub