AI RESEARCH
Exploring Urban Land Use Patterns by Pattern Mining and Unsupervised Learning
arXiv CS.LG
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ArXi:2604.13050v1 Announce Type: cross Urban areas are intricate systems shaped by socioeconomic, environmental, and infrastructural factors, with land use patterns serving as aspects of urban morphology. This paper proposes a novel methodology leveraging frequent item set mining and unsupervised learning techniques to identify similar cities based on co-occurring land use patterns. The Copernicus program's Urban Atlas data are used as source data.