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Data formats for exchanging and manipulating 3D city models: Keep it simple

9c7f843b850f4e4beeb53c93893c4ff0?s=47 Hugo Ledoux
December 07, 2021
140

Data formats for exchanging and manipulating 3D city models: Keep it simple

Keynote given at the DTCC Day 2021

https://dtcc.chalmers.se/

9c7f843b850f4e4beeb53c93893c4ff0?s=128

Hugo Ledoux

December 07, 2021
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  1. Hugo Ledoux Data formats for exchanging and manipulating 3D city

    models: keep it simple Digital Twin Cities Centre Day 2021-12-07 Delft University of Technology
  2. Topic of my talk: which format should we use? 2

    .obj ? .gml ? .json ? .shp ? .stl ? 3D city models of large area with textures with semantics with attributes
  3. We want to process and exchange the information 3 •

    ideally directly on the web • with several different software • AutoCAD, GIS, Blender, Rhino, etc solar potential shadow analysis bomb detonation wind turbulence spatial planning
  4. What are our options? 4 OBJ/STL/PLY COLLADA glTF + b3dm

    CityGML LandInfra + InfraGML CityJSON { ✅ very simple ✅ used for 30y+ in computer graphics + engineering ✅ zillions of software ❌ no semantics, no complex geometry, no attributes ✅ for visualisation on the web ✅ great software support 🤨 simple-ish (binary) ❌ no semantics, no complex geometry ✅ OGC standards since 2008/2016 ✅ do everything! ✅ *seem* perfect 🤨 is it the case in practice? 🚀 what I propose, more details in a few slides
  5. 5 International standard (from OGC) for representing and storing 3D

    city models
  6. CityGML files are very complex 6 • files are deeply

    nested • aims at solving many problems • many “points of entry” • many di ff ways to do one thing
  7. Consequence #1: almost no File/Open CityGML 7

  8. “GML madness”: how many ways to store a simple square?

    8 25 different ways
  9. Consequence #2: people will not download your files 9 -Raphaël

    Bovier, from his presentation at the 3D city modelling Workshop, Nordic Cooperation in the fi elds of Spatial Data and Land Administration (2021-09-29)
  10. Consequence #3: no web support 10 No known JavaScript parser

    for CityGML files!?
  11. “But my CityGML dataset is on the web!?” 11

  12. Consequence #4: developers/users will not use your format 12 GML

    3.2.2 specs (427 pages) GeoJSON specs (28 pages )
  13. Consequence #5: scientists in other communities are not involved 13

    • CFD/simulation community == OBJ/STL • Computer Graphics == OBJ/STL • Other communities have scientists involved in the ecosystem
  14. Consequence #6: alienate potential users (eg students) 14 When learning

    about semantic 3D city models Trying to read a CityGML file with Python
  15. Shouldn’t we apply the Rule of Least Power? 15

  16. None
  17. CityJSON v1.1 17 • community standard • compliant with CityGML

    v3.0 • subset of CityGML (~90% of features) • software for full conversion CityGML <-> CityJSON • several software support CityJSON new! new!
  18. Same information as CityGML, but in JSON format 18 {

    "type": “CityJSON", "version": “1.1”, "metadata": { "referenceSystem": "https://www.opengis.net/def/crs/EPSG/0/7415", }, "CityObjects": { "id-1": { "type": "Building", "attributes": { "measuredHeight": 22.3, "roofType": "gable", "owner": “Elvis Presley" }, "geometry": [ { "type": "MultiSurface", "boundaries": [ [[0, 3, 2, 1]], [[4, 5, 6, 7]], [[0, 1, 5, 4]] ] } ] } }, "vertices": [ [23.1, 2321.2, 11.0], [111.1, 321.1, 12.0], ... ], "appearance": { "materials": [], "textures":[], "vertices-texture": [] } } human-readable file computers prefer this over XML web prefers this over XML ~6X compacter than CityGML
  19. Python parsing is very easy 19

  20. Compression of files: Zürich LoD2 buildings 20 CityGML = 3.0GB

    (but 1GB of spaces/CRs/tabs!) CityJSON = 292MB
  21. CityJSON can be easily parsed with JavaScript 21 Developed by

    MSc students
  22. CityJSON is “ready” for machine learning 22 new!

  23. 3D BAG: all 10M+ buildings in the Netherlands 23 https://3dbag.nl

  24. LoD 2.2 
 reconstruction 3D BAG is based on open

    datasets 24 Point cloud (AHN3) Footprint (BAG) + X 10,000,000 100% automatic
  25. 25

  26. Downloads in different formats 26 Stats October/November (~158k downloads; ~2.6k/day)

    CityJSON 72% OBJ 16% GPKG 11% PostgreSQL <1%
  27. thank you. h.ledoux@tudelft.nl 3d.bk.tudelft.nl/hledoux Hugo Ledoux https://cityjson.org https://3dbag.nl