CityJSON and its usability at a national scale

Presentation at the "3D city modelling workshop", an event organized by 3D building production -ad hoc group working under the Nordic cooperation in the fields of spatial data and land administration (https://norden.lmi.is/).

Transcript

1. Hugo Ledoux
   
   
   TU Delft
   CityJSON and its usability at a
   national scale
   3D city modelling workshop
   
   
   Nordic mapping agencies
   
   
   2021-09-29
   

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2. 2
   Data model
   a GML encoding
   3 encodings
   3D City DB
   

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3. CityJSON v1.0
   3
   1. "Building"
   
   
   2. "BuildingPart"
   
   
   3. "BuildingInstallation"
   
   
   4. "Road"
   
   
   5. "Railway"
   
   
   6. "TransportSquare"
   
   
   7. "TINRelief"
   
   
   8. "WaterBody"
   
   
   9. "PlantCover"
   
   
   10. "SolitaryVegetationObject"
   
   
   11. "LandUse"
   
   
   12. "CityFurniture"
   
   
   13. "GenericCityObject"
   
   
   14. "Bridge"
   
   
   15. "BridgePart"
   
   
   16. "BridgeInstallation"
   
   
   17. "BridgeConstructionElement"
   
   
   18. "Tunnel"
   
   
   19. "TunnelPart"
   
   
   20. “TunnelInstallation”
   
   
   21. “CityObjectGroup”
   
   
   • OGC community standard
   
   
   • all modules of CityGML v2.0 are mapped 💪
   
   
   • software for full conversion CityGML <-> CityJSON
   
   
   • several software support it
   
   
   • Extensions (ADEs) are possible, and simplified
   

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4. Same information as CityGML, but in JSON format
   4
   {
   
   
   "type": “CityJSON",
   
   
   "version": “1.0”,
   
   
   "metadata": {
   
   
   "referenceSystem": "urn:ogc:def:crs:EPSG::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
   
   
   ~6X compacter than CityGML
   

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5. Why an alternative encoding?
   5
   TL;DR
   
   
   • developers don’t like nor want to use XML
   
   
   • the OGC is moving away from XML at a
   surprisingly quick pace
   
   
   • CityGML XML-encoding is very complex and
   not web-friendly
   
   
   

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6. “But my CityGML dataset is on the web!?”
   6
   

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7. 7
   Usable for who?
   
   
   1. for developers
   
   
   2. for GIS specialists
   
   
   3. for laypersons
   

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8. National scale = huge datasets
   
   
   CityJSON is 6X compacter
   
   
   than XML-files
   

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9. One example: Zürich LoD2 buildings
   9
   CityGML = 3.0GB
   
   
   (but 1GB of spaces/CRs/tabs!)
   CityJSON = 292MB
   Compression == 7.1X
   

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10. Compression factor == ~6X
    10
    Compression (v0.6)
    file CityGML size
    (original)
    CityGML size (w/o
    spaces)
    textures? CityJSON CityJSON
    compressed
    compression factor
    CityGML demo
    "GeoRes"
    4.3MB 4.1MB yes 582KB 524KB 8.0
    CityGML v2 demo
    "Railway"
    45MB 34MB yes 4.5MB 4.3MB 8.1
    Den Haag "tile 01" 23MB 18MB no, material 3.1MB 2.9MB 6.2
    Montréal VM05 56MB 42MB yes 5.7MB 5.4MB 7.8
    New York LoD2
    (DA13)
    590MB 574MB no 110MB 105MB 5.5
    Rotterdam
    Delfshaven
    16MB 15MB yes 2.8MB 2.6MB 5.4
    Vienna 37MB 36MB no 5.6MB 5.3MB 6.8
    5
    

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11. 3D BAG: all 10M+ buildings in the Netherlands
    11
    https://3dbag.nl
    

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12. LoD 2.2
    

    reconstruction
    3D BAG is based on open datasets
    12
    Point cloud
    (AHN3)
    Footprint (BAG)
    +
    X 10,000,000
    
    
    100% automatic
    

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13. 3 different LoDs
    13
    

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14. 3D BAG is tiled into *small* and *manageable* datasets
    14
    BAG polygons
    Quadtree
    
    
    Max 3500 buildings per tile
    

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15. Whole Netherlands in 3D is available in CityJSON
    15
    ~1000 tiles of 5km X 6.25km
    
    
    10M buildings (in LoD1)
    
    
    Average tile size was 2.5GB
    #FAIL
    

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16. Download is simple and fast
    16
    Stats last 2 weeks
    
    
    (~32000 downloads)
    
    
    CityJSON 56%
    
    
    OBJ 23%
    
    
    GPKG 21%
    

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17. We were very careful about geometric validity
    17
    soon 98% valid
    

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18. Amsterdam put our data in their Unity online platform within days
    18
    

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19. We reached non-geo people
    19
    

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20. People outside our field used the data
    20
    Historical cadastre Shadow analysis
    

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21. Several wrote guides to convert the data to BIM
    21
    

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22. GIS specialists do not all use/have FME: Python parsing is very easy
    22
    CityJSON makes developers
    happy (and thus productive)
    

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23. CityJSON is ready for machine learning
    23
    new!
    

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24. What about CityGML v3?
    24
    Ready in a
    few weeks
    

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25. thank you.
    h.ledoux@tudelft.nl
    
    
    3d.bk.tudelft.nl/hledoux
    Hugo Ledoux
    https://cityjson.org
    

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