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

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

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...

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Bibliographic Details
Main Authors:	Yao, Yao, Zhu, Qia, Guo, Zijin, Huang, Weiming, Zhang, Yatao, Yan, Xiaoqin, Dong, Anning, Jiang, Zhangwei, Liu, Hong, Guan, Qingfeng
Other Authors:	School of Computer Science and Engineering
Format:	Journal Article
Language:	English
Published:	2024
Subjects:	Computer and Information Science Embedding Space Alignment Points of Interest
Online Access:	https://hdl.handle.net/10356/173479

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