5 papers
Toward AI-Friendly Cartography: Understanding How Color Design Influences Foundation Model Spatial Reasoning on Sequential Choropleth Maps
Yonghe Sun, Zhenjia Liu, Hua Liao +4
Foundation models (FMs) increasingly support multimodal and geospatial reasoning, yet it remains unclear whether cartographic principles designed for human perception are equally e…
Do Maps Still Matter for Machines: Revisiting the Role of Choropleth Maps in Foundation Model Spatial Understanding
Zhiwei Wei, Yonghe Sun, Zhenjia Liu +5
Spatial understanding is crucial for foundation models (FMs), and maps have long helped humans organize and reason about geographic information. This study examines whether choropl…
Evolving Thematic Map Design in Academic Cartography: A Thirty-Year Study Based on Multilingual Journals
Zhiwei Wei, Chenxi Song, Tazhu Wang +4
Thematic maps play a central role in academic communication, yet their large-scale design evolution has rarely been examined empirically. This study presents a longitudinal and mul…
From Static to Dynamic: Evaluating the Perceptual Impact of Dynamic Elements in Urban Scenes via MLLM-Guided Generative Inpainting
Zhiwei Wei, Mengzi Zhang, Boyan Lu +3
Understanding urban perception from street view imagery has become a central topic in urban analytics and human centered urban design. However, most existing studies treat urban sc…
Thinking on Maps: How Foundation Model Agents Explore, Remember, and Reason Map Environments
Zhiwei Wei, Yuxing Liu, Hua Liao +1
Map environments provide a fundamental medium for representing spatial structure. Understanding how foundation model (FM) agents understand and act in such environments is therefor…