Unsupervised land-use change detection using multi-temporal POI embedding

• Main Authors: Yao, Yao, Zhu, Qia, Guo, Zijin, Huang, Weiming, Zhang, Yatao, Yan, Xiaoqin, Dong, Anning, Jiang, Zhangwei, Liu, Hong, Guan, Qingfeng
• 其他作者: School of Computer Science and Engineering
• 格式: Article
• 語言: English
• 出版: 2024
• 主題: Computer and Information Science; Embedding Space Alignment; Points of Interest
• 在線閱讀: https://hdl.handle.net/10356/173479
• 機構: Nanyang Technological University

Rapid land-use change detection (LUCD) is pivotal for refined urban planning and management. In this paper, we investigate LUCD through learning embeddings of points of interest (POIs) from multiple temporalities. There are several prominent challenges: (1) the co-occurrence problem of multi-tempora...