A tiled multi-city urban objects dataset for city-scale building energy simulation

City-scale building energy simulation provides a significant reference for planning and urban management. However, large-scale building energy simulation is often not feasible due to the huge amount of computational resources required and the lack of high-precision building models. Here, We developed a tiled multi-city urban objects dataset and a distributed data ontology. Such a data metric not only transforms the conventional whole-city simulation model into patch-based distributed simulations but also incorporates interactive relationships among objects in cities. This dataset stores urban objects (8,196,003 buildings; 238,736 vegetations; 2,381,6698 streets; 430,364 UrbanTiles; 430,464 UrbanPatches), UrbanTiles, and UrbanPatches) from thirty major cities in the United States. It also aggregated morphological features for each UrbanTile.

城市级建筑能耗模拟可为城市规划与城市管理提供重要参考依据。然而，由于所需计算资源体量庞大且缺乏高精度建筑模型，大规模建筑能耗模拟往往难以实现。在此背景下，本研究构建了分块式多城市城市对象数据集（tiled multi-city urban objects dataset）与分布式数据本体（distributed data ontology）。该数据框架不仅将传统的全域城市模拟模型转化为基于分块的分布式模拟，还融入了城市内各对象间的交互关联关系。本数据集收录了美国30个主要城市的城市对象，包含8196003栋建筑、238736处植被、23816698条街道、430364个城市分块（UrbanTiles）以及430464个城市斑块（UrbanPatches）。此外，该数据集还为每个城市分块（UrbanTiles）聚合了形态学特征。