The fusion process of LiDAR and map data to generate 3D city and landscape models

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The fusion process of LiDAR and map data to generate 3D city and landscape models. Sander oude elberink Geospatial world forum 16 May 2013. Generation of nationwide 3D city and landscape models using national datasets: 1:1.000, BGT, fused with AHN-2 (~8 p/m^2) - PowerPoint PPT Presentation

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  • THE FUSION PROCESS OF LIDAR AND MAP DATA TO GENERATE 3D CITY AND LANDSCAPE MODELSSANDER OUDE ELBERINKGEOSPATIAL WORLD FORUM 16 MAY 2013

  • Generation of nationwide 3D city and landscape models using national datasets:1:1.000, BGT, fused with AHN-2 (~8 p/m^2)1:10.000, TOP10, fused with AHN-2 (~8 p/m^2)Fusion processResearch questionsHydrocity (1:1.000)3DIMGeo (1:1.000)3DTOP10NL (1:10.000)*

  • EXAMPLE IN FIGURES *

  • BUILDINGS*

  • Which lidar points have to be used to transfer the height to an object?How to use the semantics of the map data?How to assign a height to a point, boundary or surface? What is the quality of that height? How to deal with noise in both the map and lidar data?THE QUESTIONS*

  • FUSING MAP AND LASER DATA*

  • Transfer height from selected points to map pointIn general resulting in at least 2 heights per map point.What to do with the differences?Semantics between classes

    SELECT LASER POINTS PER MAP POINT, PER POLYGON

  • See also presentation of Mark Kroon NeoAim was to keep small relative height differences(but not the ones caused by noise)CurbstonesBoundary between 2 infrastructural polygons (road, sidewalk).Function of object in addition to class label

    HYDROCITYPRODUCE 3D MODEL FOR HYDROLOGICAL APPLICATIONS*

  • Per object: height, infiltration capacity, surface roughnessInterpolated to grid for run off modelling

    HYDROCITYOBJECT BASED*

  • As a product of 3D Pilot, start of 3D SIG NL (see presentation of Jantien Stoter).Based on IMGeo, CityGML standards.Workbench in FME, in cooperation with con terra GmbH (Christian Dahmen).LoD0, LoD1 and LoD2.3DIMGEO1:1.000*

  • Use FME to (summary) Read and validate source data: CityGML 2D IMGeo + LiDAR (AHN-2)'Point-On-Polygon' operation (assign laser data to polygons)Run + manage the complete workflow -> Single User InterfaceUse '3D IMGeo tools' developed by U Twente to:Prepare map data and laser data for the 3D reconstruction.Assign height to the map boundaries for a LoD0 terrain description.Assign a height description inside the 3D polygons. Results are TIN surfaces at LoD0. Calculate LoD1 or LoD2 buildings and forestUse FME again to write result data: CityGML 3D IMGeo

    FME - 3DIMGEO TOOLS - FME*

  • *

  • 1:10.000Fused with AHN-2 (~8 p/m^2)

    3DTOP10NL*

  • TOP10NL: topographic representation, geometric accuracy 2 mAHN-2: geometric 3D representation, geom acc < 0.5 m, 8-10 p/m2 Aim for selecting correct pointsDo we need all laser points?

    IMPLICATIONS OF FUSION

  • RULES TO CALCULATE OBJECT HEIGHT*

    ClassLidar data taken from3D Representation type / Semantic constraintInitial height of object points on boundarySurface descriptionWaterGround Horizontal planeAll object points are set to average heightDetermined by triangulation of boundary object pointsRoadsGroundLocally planarEach object point is determined by height of local fitted planeDetermined by triangulation of boundary object pointsTerrainGroundMay vary locallyEach object point is determined by height of local fitted planeLidar points are inserted inside polygon, followed by constrained triangulationBuildingsNon-groundHorizontal plane, LoD 1All object points are set to average heightDetermined by triangulation of boundary pointsForestNon-groundMay vary locallyEach object point is determined by height of local fitted planeLidar points are inserted inside polygon, followed by constrained triangulation

  • RULES TO COMBINE HEIGHT OF NEIGHBOURING POLYGONS*

    WaterRoadTerrainBuildingForestWaterBoth keep own heightBoth own height, create additional polygon below roadTake water heightBoth keep own height, create wall in-betweenBoth keep own height, create wall in-betweenRoadAverage if close in heightTake road heightBoth keep own height, create wall in-betweenBoth keep own height, create wall in-betweenTerrainTake average of both heightsBoth keep own height, create wall in-betweenBoth keep own height, create wall in-betweenBuildingBoth keep own heightBoth keep own heightForestBoth keep own height

  • *

  • Which lidar points have to be used to transfer the height to an object?Depends on the object.How to use the semantics of the map data?Depends on the map/application.How to assign a height to a point, boundary or surface? Depends on the object.What is the quality of that height?Depends on the workflow.How to deal with noise in both the map and lidar data?Deal with it.THE QUESTIONSAND THE FRUSTRATING ANSWERS*

  • Kadaster will go for 3DTOP10NL3D IMGeo tools are open (since April 2013) and integrated into FMENice link between Geo practice and research

    NEAR FUTURE*

  • MORE INFO*

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