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Representing 3D Topological Adjacencies between Volumes Using a 36-Intersection Model

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Topological properties of objects should be maintained and preserved to concisely represent objects. However, the implementation of 2D topological rules requires the decomposition of 3D objects into lower dimensions to determine topological relationships. This results in 2D topological relationships although the connected objects are in 3D. Hence, accurate representation of 3D connectivity in 3D models is limited. 3D topological rules can be implemented to include topological connectivity in 3D space. This paper implemented an extension of the 27-Intersection Model (27-IM) called the 36-Intersection Model (36-IM) to represent 3D topological adjacencies of two objects in 3D space. This resulted in a 12 × 3 intersection matrix or 36-IM that represented the intersections in terms of dimension and number of separations. Six cases were tested, consisting of “meets”, “disjoint” “intersects at a line”, “intersects at a point”, “contains”, and “overlaps”. The resulting 36-IM matrices provided an accurate representation of how the objects in 3D space were related and their dimension of intersections. The formalisms of the 36-IM matrices were also interoperable which allowed the interpretation of 36-IM using the 9IM and DE-9IM to determine general topological relationships. By examining the intersection of interiors, boundaries and exteriors of 3D objects without object decomposition, 3D topological relationships can be determined as well as the dimension and manner of intersection.
Słowa kluczowe
Rocznik
Strony
127--155
Opis fizyczny
Bibliogr. 23 poz., rys.
Twórcy
  • Universiti Teknologi Malaysia, Faculty of Built Environment and Surveying, Johor, Malaysia
autor
  • Universiti Teknologi Malaysia, Faculty of Built Environment and Surveying, Johor, Malaysia
  • Universiti Teknologi Malaysia, Faculty of Built Environment and Surveying, Johor, Malaysia
Bibliografia
  • 1. McDonnell R., Kemp K.: International GIS Dictionary. John Wiley & Sons, 1995.
  • 2. Knoth L., Atazadeh B., Rajabifard A.: Developing a new framework based on solid models for 3D cadastres. Land Use Policy, vol. 92, 2020, 104480. https://doi.org/10.1016/j.landusepol.2020.104480.
  • 3. Li L., Luo F., Zhu H., Ying S., Zhao Z.: A two-level topological model for 3D features in CityGML. Computers, Environment and Urban Systems, vol. 59, 2016, pp. 11–24. https://doi.org/10.1016/j.compenvurbsys.2016.04.007.
  • 4. Martinez-Llario J., Coll E., Núñez-Andrés M., Femenia-Ribera C.: Rule-based topology system for spatial databases to validate complex geographic datasets. Computers & Geosciences, vol. 103, 2017, pp. 122–132. https://doi.org/10.1016/j.cageo.2017.03.013.
  • 5. Ivanov R.: An algorithm for on-the-fly K shortest paths finding in multi-storey buildings using a hierarchical topology model. International Journal of Geographical Information Science, vol. 32(12), 2018, pp. 2362–2385. https://doi.org/10.1080/13658816.2018.1510126.
  • 6. Barzegar M., Rajabifard A., Kalantari M., Atazadeh B.: 3D BIM-enabled spatial query for retrieving property boundaries: a case study in Victoria, Australia. International Journal of Geographical Information Science, vol. 43(2), 2019, pp. 251–271. https://doi.org/10.1080/13658816.2019.1658877.
  • 7. Jarząbek-Rychard M., Borkowski A.: 3D building reconstruction from ALS data using unambiguous decomposition into elementary structures. ISPRS Journal of Photogrammetry and Remote Sensing, vol. 118, 2016, pp. 1–12. https://doi.org/10.1016/j.isprsjprs.2016.04.005.
  • 8. Tran H., Khoshelham K., Kealy A.: Geometric comparison and quality evaluation of 3D models of indoor environments. ISPRS Journal of Photogrammetry and Remote Sensing, vol. 149, 2019, pp. 29–39. https://doi.org/10.1016/j.isprsjprs.2019.01.012.
  • 9. Ledoux H., Verbree E., Si H.: Geometric validation of GML solids with the constrained delaunay tetrahedralization. [in:] de Maeyer P., Neutens T., de Rijck M. (eds.), 3D GeoInfo 2009: Proceedings of the 4th International Workshop on 3D Geo-Information, Universiteit Gent, Ghent 2009, pp. 143–148.
  • 10. Lee J., Kwan M.-P.: A Combinatorial Data Model for Representing Topological Relations Among 3D Geographical Features in Micro-Spatial Environments. International Journal of Geographical Information Science, vol. 19(10), 2005, pp. 1039–1056. https://doi.org/10.1080/13658810500399043.
  • 11. Ohori K.A., Ledoux H., Stoter J.: An evaluation and classification of nD topological data structures for the representation of objects in a higher-dimensional GIS. International Journal of Geographical Information Science, vol. 29(5), 2015, pp. 825–849. https://doi.org/10.1080/13658816.2014.999683.
  • 12. ESRI: Topology Basics – ArcMap | Documentation. ArcGIS Desktop, https://desktop.arcgis.com/en/arcmap/latest/manage-data/topologies/topology-basics.htm [access: 7.08.2021].
  • 13. Abdul-Rahman A., Pilouk M.: Spatial Data Modelling for 3D GIS. Springer Science & Business Media, 2007.
  • 14. Ujang U., Anton Castro F., Azri S.: Abstract Topological Data Structure for 3D Spatial Objects. ISPRS International Journal of Geo-Information, vol. 8(3), 2019, 102. https://doi.org/10.3390/ijgi8030102.
  • 15. Salleh S., Ujang U., Azri S., Choon T.L.: Spatial Adjacency Analysis of CityGML Buildings via 3D Topological Data Structure. ISPRS The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XLII-4/W16, 2019, pp. 573–579. https://doi.org/10.5194/isprs-archives-XLII-4-W16-573-2019.
  • 16. Salleh S., Ujang U., Azri S., Choon T.L.: 3D Topological Validation of Compact Abstract Cell Complexes (CACC) Data Structure for Buildings in CityGML. International Journal of Built Environment and Sustainability, vol. 7(2), 2020, pp. 25–32. https://doi.org/10.11113/ijbes.v7.n2.457.
  • 17. Boguslawski P., Gold C.: The Dual Half-Edge – A Topological Primal/Dual Data Structure and Construction Operators for Modelling and Manipulating Cell Complexes. ISPRS International Journal of Geo-Information, vol. 5(2), 2016, 19. https://doi.org/10.3390/ijgi5020019.
  • 18. Boguslawski P., Gold C.M., Ledoux H.: Modelling and analysing 3D buildings with a primal/dual data structure. ISPRS Journal of Photogrammetry and Remote Sensing, vol. 66(2), 2011, pp. 188–197. https://doi.org/10.1016/j.isprsjprs.2010.11.003.
  • 19. Solihin W., Eastman C., Lee Y.-C.: Multiple representation approach to achieve high-performance spatial queries of 3D BIM data using a relational database. Automation in Construction, vol. 81, 2017, pp. 369–388. https://doi.org/10.1016/j.autcon.2017.03.014.
  • 20. Strobl C.: Dimensionally Extended Nine-Intersection Model (DE-9IM). [in:] Shekhar S., Xiong H. (eds.), Encyclopedia of GIS, Springer, Boston, MA 2008, pp. 240–245. https://doi.org/10.1007/978-0-387-35973-1_298.
  • 21. Ellul C., Haklay M.: Requirements for Topology in 3D GIS. Transactions in GIS, vol. 10(2), 2006, pp. 157–175. https://doi.org/10.1111/j.1467-9671.2006.00251.x.
  • 22. Zhou M., Guan Q.: A 25-Intersection Model for Representing Topological Relations between Simple Spatial Objects in 3-D Space. ISPRS International Journal of Geo-Information, vol. 8(4), 2019, 182. https://doi.org/10.3390/ijgi8040182.
  • 23. Shen J., Zhou T., Chen M.: A 27-intersection model for representing detailed topological relations between spatial objects in two-dimensional space. ISPRS International Journal of Geo-Information, vol. 6(2), 2017, 37. https://doi.org/10.3390/ijgi6020037.
Uwagi
PL
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu „Społeczna odpowiedzialność nauki” - moduł: Popularyzacja nauki i promocja sportu (2022-2023)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-5e1ac50f-2605-42f3-aa3a-da60e517a226
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