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

• المؤلفون الرئيسيون: Yao, Yao, Zhu, Qia, Guo, Zijin, Huang, Weiming, Zhang, Yatao, Yan, Xiaoqin, Dong, Anning, Jiang, Zhangwei, Liu, Hong, Guan, Qingfeng
• مؤلفون آخرون: School of Computer Science and Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2024
• الموضوعات: Computer and Information Science; Embedding Space Alignment; Points of Interest
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/173479
• المؤسسة: 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...