GeoScITY Lab at 3D GeoInfo & Smart Data Smart Cities Conference



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GeoScITY Lab contributed to the 3D GeoInfo & Smart Data Smart Cities joint conference, held in Kashiwa, Japan, from September 2–5. The conference was hosted by the Center for Spatial Information Science (CSIS), University of Tokyo, in collaboration with Japan's Ministry of Land, Infrastructure, Transport and Tourism (MLIT). Huge thanks to the local organizing committee for making this event a success!
Our researchers presented contributions ranging from technical discussions to epistemological reflections on Urban Digital Twins and their applications.
The papers will be available soon and include:
  • A Lightweight Framework for Seamless Integration of Building Energy Simulations into Urban Digital Twins
    Joint work with the Thermodynamics Lab (Mazarine Roquet and Pierre Dewallef ) at the University of Liège and (Rafika Hajji) the Hassan II Institute of Agronomy and Veterinary Medicine. Special thanks to Yassine Oudadda, who implemented a fully automated and lightweight framework to integrate energy-related data, namely heating demand and solar potential into urban digital twins. 
  • Beyond Twinness and Twinning: Reflections on Urban Digital Twinnation from the Namur 3D Project
    Led by Hadrien Macq, this work introduces the notion of "twinnation" to capture the gradual process of transformation in how cities are represented and governed through digital twins. It lays the groundwork for fostering transdisciplinary research and collaborations with stakeholders in developing data-driven infrastructures for urban governance.
  • Automatic Detection, 3D Localization, and Semantic Enrichment of Commercial Signboards Using 360° Mobile Mapping Imagery: A Case Study in Temara, Morocco
    Led by Hiba Doi and Rafika Hajji, this paper presents a novel pipeline for the automatic detection, tracking, geolocation, and textual identification of storefront signboards from 360° street-level imagery acquired via Mobile Mapping Systems (MMS). The approach provides a scalable alternative to manual inspection, offering precise spatial and semantic information about urban signage. 
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