Integration of raster and vector data for 3D city modelling URMO3D Orfeo Project OR/02/02 Dennis Devriendt Prof. Rudi Goossens

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Integration of raster and vector data for 3D city modelling URMO3D Orfeo Project OR/02/02 Dennis Devriendt Prof. Rudi Goossens 1

Presentation overview URMO3D In one sentence Objectives Study areas Methodology 2

Presentation overview Flowchart Discussion Conclusion Related projects : DIFDEM & MAMUD 3

VHR sensors deliver high quality stereo pairs with images from one orbital pass (IKONOS, QuickBird, Pleiades) Spatial resolution : 1 m Suitable for urban 3D modelling Improvement of current methods URMO3D 4

in one sentence Extracting hybrid 3D city model based on raster and vector data from the same data source, i.e. satellite stereo pair (Pleiades) Raster = Digital Surface Model Vector = 3D features of the built-up area 5

Goals of the project Defining a methodology to model and visualise an urban scene in three spatial dimensions, based on satellite images (future Pleiades) 6

Goals of the project Optimising and assessing the accuracy of raster DSM and 3D vector extraction from VHR stereo pairs Integration of three basic photogrammetric products (DSM, 3D features and orthoimages) in a hybrid 3D city model Testing the multi-temporal analytical capabilities of the developed model in a rapidly changing urban environment (Cairo, Egypt) 7

Ghent 2003-09-18 11:07 GMT Azimuth: 210.4809 degrees Elevation: 68.83065 degrees Azimuth: 346.8062 degrees Elevation: 78.86692 degrees 8

Cairo 2005-01-20 08:43 GMT Azimuth: 155.8838 degrees Elevation: 66.94662 degrees Azimuth: 52.3463 degrees Elevation: 68.90756 degrees 9

Fieldwork Cairo Measuring Ground Control Points with C-NAV differential GPS - receiver - antenna - laptop 10

Fieldwork Cairo 11

Methodology Creating a hybrid 3D city model from VHR stereo pairs (raster * vector) Using the vector model to compensate for shortcomings of the raster model and vice versa 12

Raster and Vector Surface Model Raster : area covering, suffers from occlusion Vector : very good to represent 3D features from built-up area, not all features 13

Raster and Vector Surface Model 14

Hybrid Surface Model 15

Data retrieved from satellite stereopair 16

17

18

Ground Control Points (GCP) VHR satellite stereopair satellite image metadata (viewing angles) relative and absolute orientation of the satellite images in epipolar projection => Stereomodel 3D polygons for buildings raster DSM covering 100% of the area Remove occlusion from the raster DSM: Results in raster, with no height information for the buildings (from 3D polygons) and their occlusion zone Interpolate Raster DSM for missing areas Occlusion map Convert 3D polygons to 3D volumes, retrieving additional information from the interpolated raster DSM Hybrid 3D city model 19

Optimising raster DSM extraction from satellite stereopair Optimal match window & window spacing for the matching algorithm (VirtuoZo software) Test on rural and urban area from the same IKONOS stereopair All test areas are approx. 1600 by 1300 pixels 20

Ghent, urban 21

urban 100,0 95,0 90,0 85,0 80,0 succesful match % 5 7 9 11 13 15 17 19 1 3 5 7 9 11 13 15 17 19 75,0 col/row space 22

Cairo urban 1 23

cairo matching series - urban 1 0,900 0,850 0,800 0,750 0,700 5 7 9 11 13 15 17 19 0,650 1 3 5 7 9 11 13 15 17 19 24

Ground Control Points (GCP) VHR satellite stereopair satellite image metadata (viewing angles) relative and absolute orientation of the satellite images in epipolar projection => Stereomodel 3D polygons for buildings raster DSM covering 100% of the area Remove occlusion from the raster DSM: Results in raster, with no height information for the buildings (from 3D polygons) and their occlusion zone Interpolate Raster DSM for missing areas Occlusion map Convert 3D polygons to 3D volumes, retrieving additional information from the interpolated raster DSM Hybrid 3D city model 25

Initial raster DSM and 3D features 26

Combined occlusion map 27

Raster DSM without occlusion and building 28

Interpolation Overestimation height Effect of occlusion reaches beyond occlusion area 29

Converting 3D features to solids New 3D features at ground level. Any errors in the raster interpolation influence the quality of this product 30

Conclusion and future work (1) Raster DSM extraction from VHR stereopairs optimised Generating occlusion maps : workable method, improvement possible Direct projection of 3D features on raster DSM Influence of vegetation Conversion of 3D features to 3D solids 31

Conclusion and future work (2) Continue DSM production and processing for Cairo test sites Accuracy analysis for the test areas in Ghent 32

Questions and discussion 33