Title: GeoAI-enabled multi-scale cartography: progress and a research agenda
Abstract:
Multi-scale spatial representation is a crucial mechanism for describing facts about the real world and for managing and communicating spatial data efficiently and effectively. To enable such multi-scale spatial representation, map generalization has thus been developed. The advances of GeoAI, which focus on spatially oriented deep learning and process understanding with AI techniques, have brought about a new paradigm for map generalization. In this talk, I will present the latest research progress on GeoAI-enabled map generalization supported by the Swiss National Science Foundation (SNSF). This work spans the full GeoAI workflow: from geospatial problem formulation and spatial data modeling to spatially aware deep learning architectures and explainable AI techniques. Building on these developments, I will also discuss key technical challenges and research opportunities for applying GeoAI to multi-scale cartography, with the aim of informing and inspiring future innovation in the field.
Short bio:
Dr. Zhiyong Zhou is a Swiss postdoctoral research fellow and a visiting scholar at the GeoDS Lab, University of Wisconsin-Madison, which is supported by the SNSF Postdoc.Mobility Fellowship. Prior that, he was a postdoc at the Department of Geography, University of Zurich, Switzerland. He holds a Ph.D. in Geography/Earth System Science from the University of Zurich, as well as an M.E. degree and a B.E. degree with Honors from China University of Geosciences (Wuhan). His research focuses on human-centered geospatial AI. He primarily investigates human–space interactions and develop human-adaptive, spatially explicit techniques for spatial data generalization, smart mobility, and sustainable built environments. Additionally, he serves as vice-chair of the ICA Commission on Location-Based Services.
Personal website: https://www.zhouzhiyong.com/
