4 papers
CoST: Semantic-Aware Urban Understanding via Spatial-Temporal Alignment
Yutian Jiang, Jiabo Liu, Xixuan Hao +1
Geospatial representation learning from satellite imagery is a fundamental problem for large-scale urban analysis and real-world applications. Despite recent advances, current meth…
Multi-Agent Collaborative Reasoning with Tool-Augmented Evidence for Urban Region Profiling
Xixuan Hao, Yutian Jiang, Jiabo Liu +4
Urban region profiling constitutes a core problem in urban computing, supporting applications such as population estimation, economic assessment, and environmental monitoring. Exis…
CLIPPan: Adapting CLIP as A Supervisor for Unsupervised Pansharpening
Lihua Jian, Jiabo Liu, Shaowu Wu +1
Despite remarkable advancements in supervised pansharpening neural networks, these methods face domain adaptation challenges of resolution due to the intrinsic disparity between si…
Geospatial Representation Learning: A Survey from Deep Learning to The LLM Era
Xixuan Hao, Yutian Jiang, Xingchen Zou +6
The ability to transform location-centric geospatial data into meaningful computational representations has become fundamental to modern spatial analysis and decision-making. Geosp…