Enugu State CityGML LOD1 3D Building Model: The First Open-Access Semantic 3D City Model for Nigeria and Among the First in Sub-Saharan Africa

Overview This dataset presents the first city-scale CityGML Level of Detail 1 (LOD1) 3D building model for Enugu State, Nigeria, and to the authors' knowledge, the first openly published semantic 3D city model for any city in Sub-Saharan Africa. The dataset covers the urban extent of Enugu, comprising thousands of building footprints extruded to terrain-referenced heights using a DEM-based methodology. It was produced entirely with open-source tools and is published under an open licence to support urban planning, disaster risk reduction, and geospatial research in African cities. Methodology Building footprints were sourced from OpenStreetMap and validated against satellite imagery. Heights were derived from a Digital Elevation Model (DEM) using terrain-referenced extrusion, with relative building heights estimated from contextual analysis. The CityGML conversion and attribute-enrichment pipeline was built in FME Workbench, producing a valid CityGML 2.0 dataset that conforms to OGC standards. The model was validated in 3DCityDB and visualised in CesiumJS as part of a broader smart city platform developed for Enugu. Significance The global 'awesome-citygml' registry, the most comprehensive list of open CityGML datasets, covering 21 countries and 66+ cities with over 215 million buildings, yet contains no African city. This dataset begins to address that gap. Enugu is a rapidly urbanising city of approximately 1 million people that experiences recurring flood events. A city-scale 3D model provides a foundational spatial layer for flood modelling, urban heat analysis, solar potential estimation, network analysis, and digital twin development. Applications This dataset supports: • Flood risk modelling and disaster risk reduction • Urban climate and heat island analysis • Solar energy potential estimation • Urban digital twin development • 3D GIS research and education in African urban contexts • Benchmarking LOD1 generation methods in data-scarce environments概述 本数据集为尼日利亚埃努古州提供了首个城市级别的城市地理标记语言（CityGML）细节层次1（LOD1）3D建筑模型，据作者所知，这也是撒哈拉以南非洲地区所有城市中首个公开发布的语义化3D城市模型。该数据集覆盖埃努古市区范围，包含数千栋建筑基底，采用基于数字高程模型（DEM）的方法将建筑基底拉伸至与地形匹配的高度。本数据集完全通过开源工具制作，并以开放许可发布，旨在支撑非洲城市的城市规划、灾害风险防控与地理空间研究工作。 研究方法 建筑基底数据源自开放街道地图（OpenStreetMap），并通过卫星影像完成校验。建筑高度通过数字高程模型（DEM）采用地形匹配拉伸法获取，建筑相对高度则通过上下文分析估算得到。城市地理标记语言转换与属性富集流程基于FME Workbench开发，生成符合开放地理空间信息联盟（OGC）标准的合规CityGML 2.0数据集。该模型已在3DCityDB中完成校验，并在CesiumJS中实现可视化，作为埃努古智慧城市综合平台的组成部分。 研究意义 全球“awesome-citygml”数据集收录库是目前最全面的开放CityGML数据集汇总，覆盖21个国家的66座以上城市，包含超过2.15亿栋建筑，但尚未收录任何非洲城市。本数据集填补了这一空白。埃努古是一座快速城市化的城市，人口约100万，且频发洪涝灾害。城市级3D模型可为洪涝模拟、城市热环境分析、太阳能潜力评估、网络分析以及数字孪生开发提供基础空间数据层。 应用场景 本数据集可支撑以下应用场景： • 洪涝风险建模与灾害风险防控 • 城市气候与热岛效应分析 • 太阳能潜力评估 • 城市数字孪生开发 • 非洲城市场景下的3D地理信息系统（GIS）研究与教学 • 数据稀缺环境下LOD1生成方法的基准测试