A FRAMEWORK FOR THE REPRESENTATION OF TWO VERSIONS OF A 3D CITY MODEL IN 4D SPACE

Abstract. 3D city models are being increasingly adopted by organisations in order to serve application needs related to urban areas. In order to fulfil the different requirements of various applications, the concept of Level of Detail (LoD) has been incorporated in 3D city models specifications, such as CityGML. Therefore, datasets of different LoDs are being created for the same areas by several organisations for their own use cases. Meanwhile, as time progresses newer versions of existing 3D city models are being created by vendors. Nevertheless, the existing mechanisms for representating multi-LoD data has not been adopted by the users and there has been little effort on the implementation of a mechanism to store multiple revisions of a city model. This results in redundancy of information and the existence of multiple datasets inconsistent with each other. Alternatively, a representation of time or scale as additional dimensions to the three spatial ones has been proposed as a better way to store multiple versions of datasets while retaining information related to the corresponding features between datasets. In this paper, we propose a conceptual framework with initial considerations for the implementation of a 4D representation of two states of a 3D city model. This framework defines both the data structure of such an approach, as well as the methodology according to which two existing 3D city models can be compared, associated and stored with their correspondences in 4D. The methodology is defined as six individual steps that have to be undertaken, each with its own individual requirements and goals that have to be challenged. We, also, provide some examples and considerations for the way those steps can be implemented.

[1]  PASCAL LIENHARDT,et al.  N-Dimensional Generalized Combinatorial Maps and Cellular Quasi-Manifolds , 1994, Int. J. Comput. Geom. Appl..

[2]  Waldemar Celes Filho,et al.  A topological data structure for hierarchical planar subdivisions , 1995 .

[3]  Paolo Cignoni,et al.  Metro: Measuring Error on Simplified Surfaces , 1998, Comput. Graph. Forum.

[4]  Jinmu Choi,et al.  3D Geo-Network for Agent-based Building Evacuation Simulation , 2009 .

[5]  Jantien E. Stoter,et al.  5D Data Modelling: Full Integration of 2D/3D Space, Time and Scale Dimensions , 2010, GIScience.

[6]  Armin B. Cremers,et al.  AUTOMATED UPDATING AND MAINTENANCE OF 3D CITY MODELS , 2010 .

[7]  Nobuhiro Ishimaru,et al.  4D-GIS (4 dimensional GIS) as spatial-temporal data mining platform and its application to managementand monitoring of large-scale infrastructures , 2011, Proceedings 2011 IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services.

[8]  Christine Solnon,et al.  Polynomial algorithms for subisomorphism of nD open combinatorial maps , 2011, Comput. Vis. Image Underst..

[9]  Guillaume Damiand,et al.  Combinatorial Maps: Efficient Data Structures for Computer Graphics and Image Processing , 2014 .

[10]  Guillaume Damiand,et al.  Topological Reconstruction of Complex 3D Buildings and Automatic Extraction of Levels of Detail , 2014, UDMV.

[11]  G. Damiand,et al.  Automatic Semantic Labelling of 3D Buildings Based on Geometric and Topological Information , 2014 .

[12]  Peter van Oosterom,et al.  Vario-scale data structures supporting smooth zoom and progressive transfer of 2D and 3D data , 2014, Int. J. Geogr. Inf. Sci..

[13]  Filip Biljecki,et al.  Error propagation in the computation of volumes in 3D city models with the Monte Carlo method , 2014 .

[14]  Filip Biljecki,et al.  Improving the Consistency of Multi-LOD CityGML Datasets by Removing Redundancy , 2015 .

[15]  Jantien E. Stoter,et al.  An evaluation and classification of nD topological data structures for the representation of objects in a higher-dimensional GIS , 2015, Int. J. Geogr. Inf. Sci..

[16]  J. Stoter,et al.  Modeling a 3 D City Model and Its Levels of Detail as a True 4 D Model , 2015 .

[17]  G.A.K. Arroyo Ohori,et al.  Storing a 3d City Model, its Levels of Detail and the Correspondences Between Objects as a 4d Combinatorial Map , 2015 .

[18]  G. Gesquière,et al.  Change Detection of Cities , 2015 .

[19]  Sylvie Servigne,et al.  An Automatic Comparison Approach to Detect Errors on 3D City Models , 2016, UDMV.

[20]  Ursula Eicker,et al.  Planning Tools to Simulate and Optimize Neighborhood Energy Systems , 2017 .

[21]  Lars Harrie,et al.  Topological Reconstruction of 3D City Models with preservation of semantics , 2018 .