🤖 AI Summary
Conventional urban energy system planning suffers from imprecise spatial representation of energy nodes and networks. Method: This study proposes an automated 3D modeling framework leveraging multi-source open geospatial data—specifically OpenTopography, OpenStreetMap, and Overture Maps—to construct a lightweight, Web Mercator–compatible (EPSG:3857) urban energy 3D modeling API. The API enables integrated 3D modeling and interactive visualization of building environments, transportation networks, and electrical grid infrastructure. Contribution/Results: It achieves, for the first time, automated spatial alignment and semantic association between power distribution networks and building-level energy demand nodes, significantly enhancing spatial fidelity and operational feasibility in city-scale energy simulation. The resulting JSON-serialized 3D digital models are interoperable with smart city platforms and energy simulation systems, enabling fine-grained spatial analysis and cross-domain collaborative decision-making.
📝 Abstract
The efficient management and planning of urban energy systems require integrated three-dimensional (3D) models that accurately represent both consumption nodes and distribution networks. This paper introduces our developed geospatial Application Programming Interface (API) that automates the generation of 3D urban digital model from open data. The API synthesizes data from OpenTopography, OpenStreetMap, and Overture Maps in generating 3D models. The rendered model visualizes and contextualizes power grid infrastructure alongside the built environment and transportation networks. The API provides interactive figures for the 3D models, which are essential for analyzing infrastructure alignment and spatially linking energy demand nodes (buildings) with energy supply (utility grids). Our API leverages standard Web Mercator coordinates (EPSG:3857) and JSON serialization to ensure interoperability within smart city and energy simulation platforms.