1. 3D LANDSCAPE MODELLING SANDER OUDE ELBERINK

2. FACULTY OF GEO-INFORMATION SCIENCE AND EARTH OBSERVATION Copyright Gerard Kuster

3. 3D TOPOGRAPHIC MODEL LANDSCAPE AND CITY MODELS GIN OOST28 April 2016

4.  Understand:  How to properly fuse a point cloud with a topographic data set to obtain a semantically correct 3D landscape model;  How to use theory in practice;  What are the remaining challenges in this field; THREE MAIN OBJECTIVES GIN OOST28 April 2016

5. FUSION OF LIDAR AND MAP DATA WHAT ARE WE FUSING GIN OOST28 April 2016

6. FUSION OF LIDAR AND MAP DATA WHAT ARE WE FUSING GIN OOST MapPoint cloud X, Y, label (ID, class, function,..) X,Y,Z,… PolygonsPoints InterpretedUninterpreted – interpreted (filtered, classified,..) Period APeriod B 28 April 2016

7. Footprint “wall at ground” Footprint “roof outline” GIN OOST28 April 2016

8. A CLOSER LOOK DATA FROM UTRECHT, IN HYDROCITY PROJECT LED BY NEO GIN OOST28 April 2016

9. HEIGHT CALCULATION AT POLYGON BOUNDARIES GIN OOST28 April 2016

10.  Transfer height (depending on class) from selected points to map point  In general resulting in at least 2 heights per map point.  What to do with the differences?  Semantics between classes, inspired by Koch (2004) SELECT LASER POINTS PER MAP POINT, PER POLYGON GIN OOST Koch, A., 2004. An Approach for the Semantically Correct Integration of a DTM and 2D GIS Vector Data, XXth ISPRS Congress: Geo-Imagery Bridging Continents. IAPRS, Istanbul, Turkey. 28 April 2016

11. GIN OOST 2D edge -> 2 3D edges Terrain connects to water Water is flat

12. THEORY: A NICE TOOL BUILT FOR TILES OF 1X1 KM. GIN OOST28 April 2016

13.  Project led by Kadaster  Partners: Conterra, Geodan, TU Delft and UT  2013-2014 3D TOP10NL 28 April 2016GIN OOST

14. THEORY: A NICE TOOL BUILT FOR TILES OF 1X1 KM. GIN OOST28 April 2016

15. IN PRACTICE: REPEAT 30.000 X * MAKE NEIGHBORING TILES CONNECT * The use of a supercomputer is recommended. GIN OOST28 April 2016

16.  Supercomputer SARA was used, reducing processing time by factor >100  For NL:  640 billion lidar points  15 million map polygons  80.000 process hours PROCESSING TILE BY TILE AT A NATIONAL LEVEL GIN OOST28 April 2016

17. 3DTOP10NL GIN OOST28 April 2016

18. 3DTOP10NL GIN OOST28 April 2016

19. GIN OOST28 April 2016

20.  Also for BGT  Closed polygons  No gaps, no overlap TOOLS ARE MADE FOR OBJECT BASED MAPS 28 April 2016GIN OOST

21. EXAMPLE OF WORKBENCH FUSING ALS AND MAP PREPARED BY CONTERRA, FOR DUTCH PILOT 3D Available on geonovum.nl GIN OOST28 April 2016

22. GIN OOST28 April 2016

23. Kadaster IT dagen

24. APPLICATIONS WATER RUN OFF MODELLING GIN OOST28 April 2016

25. GIN OOST More detailed building models

26. 3D MODELS TO BETTER INTERPRET SATELLITE/AERIAL IMAGERY FOR CHANGE DETECTION GIN OOST28 April 2016

27.  Automation in change detection and updating  What happened in between map & point cloud acquisition dates?  What happened until now? (3D model is based on historical data)  AHN3 – image based point clouds  Smarter fusion and object based processing  3D BGT and BAG, hmm… first 2D BGT CURRENT CHALLENGES 28 April 2016GIN OOST

28. 28 April 2016GIN OOST Smart point cloud reduction

29. 28 April 2016GIN OOST Make it fit: 3D model that complies to BAG + BGT + AHN2