3D Data Integration in the Voxel Domain

Abstract

The interest in 3D data integration is growing as the concept of Spatial Digital Twins gains traction among local governments and stakeholders. Spatial data is typically organized into standardised themes such as buildings, transport, and vegetation, or as ad hoc data products in either 2D or 3D dimensions. However, integrating these data sets into a cohesive 3D model presents several challenges. The foundational data sets may vary in terms of accuracy, resolution, representation, and actuality due to differences in creation standards and procedures. Consequently, inconsistencies often arise within the 3D models, making them difficult to identify and rectify. Many of these data integration issues can be traced back to the 3D vector representation. Vector 3D models exhibit significant geometric diversity, which complicates the computational operations required for examining and validating the models. In this paper, we propose a novel voxel-based approach for integrating 3D data. Voxels, analogous to pixels in 2D raster images, inherit several key properties. We employ a dedicated voxel data structure and a set of operations tailored for this purpose. First, we voxelise vector datasets, converting continuous geometric information into discrete voxel representations. Next, we merge voxel layers using a specialized voxel overlay operation. The resulting 3D model adheres to most validity and integrity requirements. To highlight the flexibility of our voxel data structure, we transformed it into point clouds for visualisation in ArcGIS Pro, enabling the addition of 3D base maps and GIS layers. We then published these datasets to Scene Services, granting public access. This allows users to easily explore the 3D scenes through a web browser, making complex geographic data more accessible. By leveraging voxels, our approach facilitates efficient and accurate 3D data integration, making it a valuable contribution to the field.