3D Space Shift from CityGML LoD3-Based Multiple Building Elements to a 3D Volumetric Object

Shen Ying,Biao He,Renzhong Guo,Jie Yang,Zhigang Zhao,Fengzan Jin

doi:10.3390/ijgi6010017

Shen Ying, Biao He + Show 4 more

Open Access

https://doi.org/10.3390/ijgi6010017

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Abstract

In contrast with photorealistic visualizations, urban landscape applications, and building information system (BIM), 3D volumetric presentations highlight specific calculations and applications of 3D building elements for 3D city planning and 3D cadastres. Knowing the precise volumetric quantities and the 3D boundary locations of 3D building spaces is a vital index which must remain constant during data processing because the values are related to space occupation, tenure, taxes, and valuation. To meet these requirements, this paper presents a five-step algorithm for performing a 3D building space shift. This algorithm is used to convert multiple building elements into a single 3D volumetric building object while maintaining the precise volume of the 3D space and without changing the 3D locations or displacing the building boundaries. As examples, this study used input data and building elements based on City Geography Markup Language (CityGML) LoD3 models. This paper presents a method for 3D urban space and 3D property management with the goal of constructing a 3D volumetric object for an integral building using CityGML objects, by fusing the geometries of various building elements. The resulting objects possess true 3D geometry that can be represented by solid geometry and saved to a CityGML file for effective use in 3D urban planning and 3D cadastres.

Highlights

Introduction and MotivationsThree-dimensional (3D) city models can be created using numerous techniques and have been widely applied in multiple fields such as city planning, architectural design, and wireless communication [1]
Due to the logical criteria involved in 3D cadastres and other applications, this paper aims to represent a building as a single object with closed faces and a computable volume to satisfy the requirements of 3D cadastres and other applications in this paper
//Step 1: Filter and extract building elements according to semantics Select boundary building elements according to semantics based on City Geography Markup Language (CityGML); Retrieve their corresponding geometrics as candidate data describing the boundaries of the later 3D space; Build the topological relationships of all geometrics;

Summary

Introduction and Motivations

Three-dimensional (3D) city models can be created using numerous techniques and have been widely applied in multiple fields such as city planning, architectural design, and wireless communication [1]. In 3D urban planning and management fields, 3D cadastres [2,3,4,5] require the entire 3D closed volumetric space of a building to identify the precise space based on boundary points, lines, and faces, with a particular focus on the outer boundaries of the buildings This volume is an important index used to determine the space occupied by a property to assist with 3D space management and property tax assessments. The building elements represented in CityGML LoD3 are used as input data to calculate the 3D building space This process serves to transfer the geometric structure, which improves the ability to analyse and compute 3D objects. The result is the simplest 3D geometry—a 3D volumetric solid that best fits the original object shape and maintains the precise volume of the original 3D building space

Related Work

Building Models in CityGML

Discussion and Conclusions