Geometric-based approach for linking various building measurement data to a 3D city model

Area of Science:

• Geoinformatics
• Urban Planning
• Computer Vision

Background:

• Japan's Ministry of Land, Infrastructure, Transport, and Tourism is developing the open 3D city model, PLATEAU.
• Diverse building measurement data, including private maps and mobile mapping system point clouds, are available.
• Identifying buildings with available measurement data is crucial for enhancing the 3D city model's value.

Purpose of the Study:

• To propose and evaluate an efficient building measurement data matching method using geometric properties.
• To assess the effectiveness of matching various data sources (private maps, aerial images, point clouds) to the PLATEAU 3D city model.

Main Methods:

• Geometric property-based matching algorithm.
• Utilized Zenrin private map data and aerial imagery for building data extraction and matching.
• Employed Level of Detail 1 and 2 models for textured building file creation from mobile mapping system point clouds.

Main Results:

• 90.6% of Zenrin building polygons were successfully matched to PLATEAU IDs.
• 93.6% of buildings extracted from aerial images matched PLATEAU buildings.
• 46 textured building files were created; laser profiling point cloud cover ratio exceeded mobile mapping system data.

Conclusions:

• The proposed geometric matching method is efficient for identifying buildings with available measurement data.
• High matching rates demonstrate the method's effectiveness across different data sources.
• The findings contribute to improving the completeness and utility of the PLATEAU open 3D city model.