Parameter-driven Level of Detail Derivation Method for Semantic Building Facade Model

doi:10.11947/j.JGGS.2024.0304

Abstract

Abstract:

The relentless progress in the research of geographic spatial data models and their application scenarios is propelling an unprecedented rich Level of Detail (LoD) in realistic 3D representation and smart cities. This pursuit of rich details not only adds complexity to entity models but also poses significant computational challenges for model visualization and 3D GIS. This paper introduces a novel method for deriving multi-LOD models, which can enhance the efficiency of spatial computing in complex 3D building models. Firstly, we extract multiple facades from a 3D building model (LoD3) and convert them into individual semantic facade models. Through the utilization of the developed facade layout graph, each semantic facade model is then transformed into a parametric model. Furthermore, we explore the specification of geometric and semantic details in building facades and define three different LODs for facades, offering a unique expression. Finally, an innovative heuristic method is introduced to simplify the parameterized facade. Through rigorous experimentation and evaluation, the effectiveness of the proposed parameterization methodology in capturing complex geometric details, semantic richness, and topological relationships of 3D building models is demonstrated.

Key words: 3D building model; multi-Level of Detail (LoD); semantic facade model; CityGML; 3D GIS

WANG Yuefeng, JIAO Wei. Parameter-driven Level of Detail Derivation Method for Semantic Building Facade Model[J]. Journal of Geodesy and Geoinformation Science, 2024, 7(3): 57-75.

Figures/Tables 15

Table 1

Figure 1

Figure 2

Figure 3

Figure 4

Table 2

Figure 5

Figure 6

Figure 7

Figure 8

Figure 9

Figure 10

Figure 11

Table 3

Table 4

References 45

[1]	ZHU Yiqing, LI Nan. Virtual and augmented reality technologies for emergency management in the built environments: a state-of-the-art review[J]. Journal of Safety Science and Resilience, 2021, 2(1): 1-10.
[2]	BORTOLUZZI B, EFREMOV I, MEDINA C, et al. Automating the creation of building information models for existing buildings[J]. Automation in Construction, 2019, 105: 102838.
[3]	MAO Bo, HARRIE L, BAN Yifang. Detection and typification of linear structures for dynamic visualization of 3D city models[J]. Computers, Environment and Urban Systems, 2012, 36(3): 233-244.
[4]	TAKIKAWA T, LITALIEN J, YIN Kangxue, et al. Neural geometric level of detail: real-time rendering with implicit 3D shapes[C]// Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. Nashville, TN: IEEE, 2021: 11353-11362.
[5]	XU Zhihua, QU Lingling. A skeletal camera network for close-range images with a data driven approach in analyzing stereo configuration[J]. Journal of Geodesy and Geoinformation Science, 2022, 5(4): 23-37. DOI: 10.11947/j.JGGS.2022.0403.
[6]	HAN Jiali, ZHU Lingjie, GAO Xiang, et al. Urban scene LOD vectorized modeling from photogrammetry meshes[J]. IEEE Transactions on Image Processing, 2021, 30: 7458-7471.
[7]	ZHAO Zhiyao, FAN Hongchao. Towards exploring patterns of editing behavior on OpenStreetMap[J]. Journal of Geodesy and Geoinformation Science, 2022, 5(2): 85-97. DOI: 10.11947/j.JGGS.2022.0209.
[8]	ZHAO Junqiao, ZHU Qing, DU Zhiqiang, et al. Mathematical morphology-based generalization of complex 3D building models incorporating semantic relationships[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2012, 68: 95-111.
[9]	ZHANG Chenyang, HUANG Teng, SHEN Yueqian. A review of RGB-D camera calibration methods[J]. Journal of Geodesy and Geoinformation Science, 2021, 4(4): 11-33. DOI: 10.11947/j.JGGS.2021.0402.
[10]	ZHAN Wenxiao, CHEN Yuxuan, CHEN Jing. 3D tiles-based high-efficiency visualization method for complex BIM models on the web[J]. ISPRS International Journal of Geo-Information, 2021, 10(7): 476.
[11]	TEO T A, CHO K H. BIM-oriented indoor network model for indoor and outdoor combined route planning[J]. Advanced Engineering Informatics, 2016, 30(3): 268-282.
[12]	GOIA F. Search for the optimal window-to-wall ratio in office buildings in different European climates and the implications on total energy saving potential[J]. Solar Energy, 2016, 132: 467-492.
[13]	BOURHIM E M, CHERKAOUI A. Efficacy of virtual reality for studying people's pre-evacuation behavior under fire[J]. International Journal of Human-Computer Studies, 2020, 142: 102484.
[14]	PARK S, PARK S H, PARK L W, et al. Design and implementation of a smart IoT based building and town disaster management system in smart city infrastructure[J]. Applied Sciences, 2018, 8(11): 2239.
[15]	SHE Jiangfeng, CHEN Bo, TAN Junzhong, et al. 3D building model simplification method considering both model mesh and building structure[J]. Transactions in GIS, 2022, 26(3): 1182-1203.
[16]	XIANG Hanyu, HUANG Xianfeng, LAN Feng, et al. A shape-preserving simplification method for urban building models[J]. ISPRS International Journal of Geo-Information, 2022, 11(11): 562.
[17]	BILJECKI F, LEDOUX H, STOTER J, et al. Formalisation of the level of detail in 3D city modelling[J]. Computers, Environment and Urban Systems, 2014, 48: 1-15.
[18]	TANG Lei, YING Shen, LI Lin, et al. An application-driven LOD modeling paradigm for 3D building models[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2020, 161: 194-207.
[19]	DIXON S, IRSHAD H, PANKRATZ D M, et al. The 2019 Deloitte city mobility index[R]. [S.l.]: Deloitte Insights, 2019.
[20]	VON RICHTHOFEN A, HERTHOGS P, KRAFT M, et al. Semantic City Planning Systems (SCPS): a literature review[J]. Journal of Planning Literature, 2022, 37(3): 415-432.
[21]	ZHANG Xinchang, LI Shaoying, ZHOU Qiming, et al. Logical and innovative construction of digital twin city[J]. Journal of Geodesy and Geoinformation Science, 2021, 4(4): 113-120. DOI: 10.11947/j.JGGS.2021.0409.
[22]	NAPOLITANO R K, SCHERER G, GLISIC B. Virtual tours and informational modeling for conservation of cultural heritage sites[J]. Journal of Cultural Heritage, 2018, 29: 123-129.
[23]	TSCHIRSCHWITZ F, RICHERZHAGEN C, PRZYBILLA H J, et al. Duisburg 1566: transferring a historic 3D city model from Google earth into a virtual reality application[J]. PFG-Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 2019, 87(1-2): 47-56.
[24]	ANAND P B. Assessing smart city projects and their implications for public policy in the Global South[J]. Contemporary Social Science, 2021, 16(2): 199-212.
[25]	DOCHEV I, GORZALKA P, WEILER V, et al. Calculating urban heat demands: an analysis of two modelling approaches and remote sensing for input data and validation[J]. Energy and Buildings, 2020, 226: 110378.
[26]	SANTANA J M, WENDEL J, TRUJILLO A, et al. Multimodal location based services—semantic 3D city data as virtual and augmented reality[M]//GARTNER G, HUANG Haosheng. Progress in Location-Based Services 2016. Cham: Springer, 2017: 329-353.
[27]	EL YAMANI S, ETTARID M, HAJJI R. Building information modeling potential for an enhanced real estate valuation approach based on the hedonic method[J]. WIT Transactions on the Built Environment, 2019, 192: 305-316.
[28]	CHATURVEDI K, WILLENBORG B, SINDRAM M, et al. Solar potential analysis and integration of the time-dependent simulation results for semantic 3D city models using dynamizers[C]// Proceedings of the 12th International 3D GeoInfo Conference 2017. Melbourne: ISPRS, 2017: 25-32.
[29]	RONG Youtong, ZHANG Ting, ZHENG Yanchen, et al. Three-dimensional urban flood inundation simulation based on digital aerial photogrammetry[J]. Journal of Hydrology, 2020, 584: 124308.
[30]	WANG Zhiyong, NIU Lei. A data model for using OpenStreetMap to integrate indoor and outdoor route planning[J]. Sensors, 2018, 18(7): 2100.
[31]	WALMSLEY A, KERSTEN T P. Low-cost development of an interactive, immersive virtual reality experience of the historic city model Stade 1620[C]// Proceedings of the 6th International Workshop LowCost 3D - Sensors, Algorithms, Applications. Strasbourg: ISPRS, 2019: 405-411.
[32]	WANG Yuefeng, FAN Hongchao, ZHOU Guoqing. Reconstructing facade semantic models using hierarchical topological graphs[J]. Transactions in GIS, 2020, 24(4): 1073-1097.
[33]	NYS G A, BILLEN R. From consistency to flexi-bility: handling spatial information schema thanks to a middleware in a 3D city modeling context[J]. Transactions in GIS, 2023, 27(1): 115-133.
[34]	PANTAZATOU K, KANTERS J, OLSSON P O, et al. Input data requirements for daylight simulations in urban densifications[J]. Urban Informatics, 2023, 2(1): 2.
[35]	State of New South Wales. Apartment design guide[S]. New South Wales: Housing and NSW Department of Planning and Environment, 2015.
[36]	HORTON D. Montana commercial energy code summary[S]. New South Wales: National Center for Appropriate Technology, 2015.
[37]	European Union. Amending energy performance of buildings directive (2018/844/EU)[S]. Belgium: Directorate-General for Energy of European Union, 2018.
[38]	Ministry of Housing and Urban-Rural Development of the People's Republic of China, General Administration of Quality Supervision, Inspection and Quarantine of the People's Republic of China. GB 50096-2011 design code for residential buildings[S]. Beijing: China Planning Press, 2012.
[39]	United Kingdom. Energy performance of buildings directive[S]. London: Ministry of Housing Communities & Local Government, United Kingdom Open Government Licence, 2018.
[40]	WAPC. R-Codes state planning policy 3.1 residential design codes[S]. Perth, Western Australia: Western Australian Planning Commission Department of Planning Lands and Heritage, 2018.
[41]	WANG Yanjun, LI Shaochun, WANG Mengjie, et al. A simple deep learning network for classification of 3D mobile LiDAR point clouds[J]. Journal of Geodesy and Geoinformation Science, 2021, 4(3): 49-59. DOI: 10.11947/j.JGGS.2021.0305.
[42]	FAN Hongchao, WANG Yuefeng, GONG Jianya. Layout graph model for semantic facade reconstruction using laser point clouds[J]. Geo-Spatial Information Science, 2021, 24(3): 403-421.
[43]	BILJECKI F, LEDOUX H, STOTER J. An improved LOD specification for 3D building models[J]. Computers, Environment and Urban Systems, 2016, 59: 25-37.
[44]	TAN Yi, LIANG Ying, ZHU Junxiang. CityGML in the integration of BIM and the GIS: challenges and opportunities[J]. Buildings, 2023, 13(7): 1758.
[45]	ZHU Junxiang, WANG Xiangyu, CHEN Meng-cheng, et al. Integration of BIM and GIS: IFC geometry transformation to shapefile using enhanced open-source approach[J]. Automation in Construction, 2019, 106: 102859.