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3D Cadaster Creation from Generalized Blueprint Based on Semantic Boundary Point Extraction

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Abstract  

3D cadaster is essential for city management along with the construction of skyscrapers and underground infrastructures. Traditionally, the boundary points of cadaster are manually defined and drawn by the survey services. However, new building structures are becoming increasingly complex, which makes the direct survey of 3D boundary points difficult and costly. This paper proposes a 3D cadastral boundary point extraction method using the generalized CAD blueprint. Furthermore, a semantic feature detection algorithm with graph analysis is suggested to automatically generate the semantic 3D cadaster objects such as rooms or corridors from the boundary points. The experimental results show that the proposed method can correctly extract the boundary points from CAD blueprint and generate the semantic 3D cadaster map for complex buildings.

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References 

  • Arroyo OK, Diakité A, Krijnen T, Ledoux H, Stoter J (2018) Processing BIM and GIS Models in Practice: Experiences and Recommendations from a GeoBIM Project in The Netherlands. ISPRS Int J Geo-Inf 7:311. https://doi.org/10.3390/ijgi7080311

  • Asghari A, Kalantari M, Rajabifard A (2019) A structured framework for 3D cadastral data validation − a case study for Victoria, Australia, Land Use Policy. ISSN 104359:0264–8377

    Google Scholar 

  • Cemellini B, van Oosterom P, Thompson R, de Vries M (2020) Design, development and usability testing of an LADM compliant 3D Cadastral prototype system, Land Use Policy, 2020. ISSN 104418:0264–8377

    Google Scholar 

  • Diakité AA, Zlatanova S (2018) Spatial subdivision of complex indoor environments for 3D indoor navigation. Int J Geogr Inf Sci 32(2):213–235. https://doi.org/10.1080/13658816.2017.1376066

    Article  Google Scholar 

  • Drobež P, Fras MK, Ferlan M, Lisec A (2017) Transition from 2D to 3D real property cadastre: the case of the Slovenian cadastre. Comput Environ Urban Syst 62(2017):125–135

  • Du SH, Luo LQ, Cao K, Shu M (2016) Extracting building patterns with multilevel graph partition and building grouping. ISPRS J Photogramm Remote Sens 122(2016):81–96

    Article  Google Scholar 

  • Fan ZW, Zhu LJ, Li HH, Zhu SY, Tan P (2021) FloorPlanCAD: a large-scale CAD drawing dataset for panoptic symbol, Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), October, 2021

  • Gkeli M, Potsiou C, Ioannidis C (2019) A technical solution for 3D crowdsourced cadastral surveys, Land Use Policy, 2019. ISSN 104419:0264–8377

    Google Scholar 

  • Guo RZ, Li L, Ying S, Luo P, He B, Jiang RR (2013) Developing a 3D cadastre for the administration of urban land use: a case study of Shenzhen, China, Computers, Environment and Urban Systems, Vol. 40, 2013, pp 46–55, ISSN 0198–9715,

  • Hamieh A, Makhlouf AB, Louhichi B, Deneux D (2020) A BIM-based method to plan indoor paths, Automation in Construction, Vol. 113, 2020, 103120, ISSN 0926–5805,

  • He XJ, Zhang XC, Xin QC (2018) Recognition of building group patterns in topographic maps based on graph partitioning and random forest. ISPRS J Photogramm Remote Sens 136(2018):26–40

    Article  Google Scholar 

  • Horna S, Damiand G, Meneveaux D, Bertrand Y (2007) Building 3d indoor scenes topology from 2D architectural plans. In Proc. of 2nd International Conference on Computer Graphics Theory and Applications, pp 37–44, Barcelona, Spain, March 2007.

  • Karki S, Thompson R, McDougall K (2013) Development of validation rules to support digital lodgement of 3D cadastral plans, Computers, Environment and Urban Systems, Vol. 40, 2013, pp 34–45, ISSN 0198–9715,

  • Kim JS, Li KJ (2019) Simplification of geometric objects in an indoor space, ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 147, 2019, pp 146–162, ISSN 0924–2716,

  • Kim S, Heo J (2019) Registration of 3D underground parcel in Korean cadastral system, Cities, Vol. 89, 2019, pp 105–119, ISSN 0264–2751,

  • Li QQ, Sun X, Yang BS, Jiang S (2013) Geometric structure simplification of 3D building models, ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 84, 2013, pp 100–113, ISSN 0924–2716,

  • Lin YH, Liu YS, Gao Ge, Han XG, Lai CY, Ming Gu (2013) The IFC-based path planning for 3D indoor spaces, Advanced Engineering Informatics, 27(2), 2013, pp 189–205, ISSN 1474–0346,

  • Mao B, Harrie L, Ban Y (2012) Detection and typification of linear structures for dynamic visualisation of 3D city models. Comput Environ Urban Syst 35(3):233–244

    Article  Google Scholar 

  • Mao B, Li B (2020) Graph-based 3D building semantic segmentation for sustainability analysis. J Geovis Spat Anal 4:4. https://doi.org/10.1007/s41651-019-0045-y

    Article  Google Scholar 

  • Meng LQ, Forberg A (2007) 3D building generalisation, Editor(s): William A. Mackaness, Anne Ruas, L. Tiina Sarjakoski, In International Cartographic Association, Generalisation of Geographic Information, Elsevier Science B.V., 2007, pp 211–231, ISBN 9780080453743,

  • Ślusarczyk G, Łachwa A, Palacz W, Strug B, Paszyńska A, Grabska E (2017) An extended hierarchical graph-based building model for design and engineering problems. Autom Constr 74(2017):95–102

    Article  Google Scholar 

  • Stoter J, Salzmann M (2003) Towards a 3D cadastre: where do cadastral needs and technical possibilities meet?, Computers, Environment and Urban Systems, 27(4), 2003. ISSN 395–410:0198–9715

    Google Scholar 

  • Tang L, Ying S, Li L, Biljecki F, Zhu H, Zhu Y, Yang F, Su F (2020) An application-driven LOD modeling paradigm for 3D building models, ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 161, 2020, pp 194–207, ISSN 0924–2716,

  • Tarcisio MF, Roxin A, Christophe N (2018) A rule-based methodology to extract building model views. Automation in Construction. 92:214–229. https://doi.org/10.1016/j.autcon.2018.03.035

  • Thakur A, Banerjee AJ, Gupta SK (2009) A survey of CAD model simplification techniques for physics-based simulation applications, Computer-Aided Design, Vol. 41, Iss. 2, 2009, pp 65–80, ISSN 0010–4485,

  • Thompson RJ (2015) A model for the creation and progressive improvement of a digital cadastral data base, Land Use Policy, Vol. 49, 2015, pp 565–576, ISSN 0264–8377.

  • Tse R, Gold C (2003) A proposed connectivity-based model for a 3-D cadastre, Computers, Environment and Urban Systems, 27(4), 2003, pp 427–445, ISSN 0198–9715.

  • UN DESA report (2018) https://www.un.org/development/desa/en/news/population/2018-revision-of-world-urbanization-prospects.html. Accessed 2022.6.5

  • Wang H, Pan Y, Luo X, (2019) Integration of BIM and GIS in sustainable built environment: a review and bibliometric analysis, Automation in Construction, Vol. 103, 2019, pp 41–52, ISSN 0926–5805.

  • Ying S, Chen N, Li W, Li CP, Guo RZ (2019) Distortion visualization techniques for 3D coherent sets: a case study of 3D building property units, Computers, Environment and Urban Systems, Vol. 78, 2019, 101382, ISSN 0198–9715.

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Funding

This work is supported by the Natural Science Foundation of the Jiangsu Higher Education Institutions of China (21KJB520032), the 2021 Computer Basic Education Teaching Research Project of the National Institute of Computer Basic Education in Colleges and Universities of China (2021-AFCEC-282), Qing Lan Project of Jiangsu Province (Outstanding Young Teachers 2022), Open Project Program of Jiangsu Provincial Collaborative Innovation Centre for Modern Grain Circulation and Safety (XDLS20220201), the Open Fund of Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources (Grant No. KF-2019–04-016).

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Authors and Affiliations

  1. College of Marine Engineering, Electrization and Intelligence, Jiangsu Maritime Institute, Nanjing Jiangsu, 211170, China

    Bingchan Li

  2. College of Food Science and Engineering, Collaborative Innovation Centre for Modern Grain Circulation and Safety, Nanjing University of Finance and Economics, Nanjing, 210023, China

    Bo Mao

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  1. Bingchan Li
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  2. Bo Mao
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There is no ethical issues involved in this study. The submission has been received explicitly from all co-authors, and the authors whose names appear on the submission have contributed sufficiently to the scientific work and therefore share collective responsibility and accountability for the results. This article does not contain any studies with human participants or animals performed by any of the authors. In this experiment, we did not collect any samples of human and animals.

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Li, B., Mao, B. 3D Cadaster Creation from Generalized Blueprint Based on Semantic Boundary Point Extraction. J geovis spat anal 6, 21 (2022). https://doi.org/10.1007/s41651-022-00113-1

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