使用程序建模的机载LiDAR数据和OpenStreetMap自动生成3D建筑模型

Inf. Comput. Pub Date : 2023-07-11 DOI:10.3390/info14070394
R. Zupan, Adam Vinković, Rexhep Nikçi, Bernarda Pinjatela
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引用次数: 1

摘要

本研究主要集中在利用可用的机载激光雷达数据和来自OpenStreetMap (OSM)数据库的空间数据来生成大规模城市地区建筑物的3D模型。斯洛文尼亚卢布尔雅那市中心被选为研究区域,因为数据的可用性和建筑形状、高度和功能的多样性,这对自动生成3D模型提出了挑战。为了提取建筑高度,使用了一系列数据源,包括OSM属性数据、地理参考和分类点云和数字高程模型(DEM),这些数据来自斯洛文尼亚环境署公开提供的LiDAR调查数据。利用处理后的激光雷达数据建立了数字地表模型(DSM)和数字地形模型(DTM)。从OSM中提取建筑物轮廓和属性,并使用QGIS进行处理。研究区域建筑物的OSM数据的空间覆盖非常好,而只有18%的属性描述了建筑物的外观,6%的属性描述了屋顶类型。使用LASTools软件(rapidlasso GmbH, Friedrichshafener Straße 1,82205 Gilching, GERMANY)从分割点云的三维坐标中导出并分配建筑物高度。对程序建模的各种软件选项进行了比较,由于能够处理OSM数据,文档的可用性和低计算要求,选择了Blender。使用程序建模,一个3D模型与细节水平(LOD) 1是完全自动化创建的。在分析屋顶类型后,使用LOD2为87.64%的建筑物全自动创建了3D模型。对于剩余的建筑,进行了程序屋顶建模和手动屋顶编辑的比较。最后,将生成的三维模型与Google Earth模型进行视觉比较。本研究的主要目的是展示使用开放数据和免费软件的高效建模过程,并与之前的LOD2迭代相比,提高了3D建筑模型的准确性。
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Automatic 3D Building Model Generation from Airborne LiDAR Data and OpenStreetMap Using Procedural Modeling
This research is primarily focused on utilizing available airborne LiDAR data and spatial data from the OpenStreetMap (OSM) database to generate 3D models of buildings for a large-scale urban area. The city center of Ljubljana, Slovenia, was selected for the study area due to data availability and diversity of building shapes, heights, and functions, which presented a challenge for the automated generation of 3D models. To extract building heights, a range of data sources were utilized, including OSM attribute data, as well as georeferenced and classified point clouds and a digital elevation model (DEM) obtained from openly available LiDAR survey data of the Slovenian Environment Agency. A digital surface model (DSM) and digital terrain model (DTM) were derived from the processed LiDAR data. Building outlines and attributes were extracted from OSM and processed using QGIS. Spatial coverage of OSM data for buildings in the study area is excellent, whereas only 18% have attributes describing external appearance of the building and 6% describing roof type. LASTools software (rapidlasso GmbH, Friedrichshafener Straße 1, 82205 Gilching, GERMANY) was used to derive and assign building heights from 3D coordinates of the segmented point clouds. Various software options for procedural modeling were compared and Blender was selected due to the ability to process OSM data, availability of documentation, and low computing requirements. Using procedural modeling, a 3D model with level of detail (LOD) 1 was created fully automated. After analyzing roof types, a 3D model with LOD2 was created fully automated for 87.64% of buildings. For the remaining buildings, a comparison of procedural roof modeling and manual roof editing was performed. Finally, a visual comparison between the resulting 3D model and Google Earth’s model was performed. The main objective of this study is to demonstrate the efficient modeling process using open data and free software and resulting in an enhanced accuracy of the 3D building models compared to previous LOD2 iterations.
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