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Geovisualization of coastal areas from heterogeneous spatio-temporal data (Antoine Masse)

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On coastal areas, recent increase in production of open-access high-quality data over large areas reflects high interests in modeling and geovisualization, especially for applications of sea level rise prediction, ship traffic security and ecological protection. Research interests are due to tricky challenges from the intrinsic nature of the coastal area, which is composed of complex geographical objects of which spatial extents vary in time, especially in the intertidal zone (tides, sands, etc.). Another interest is the complex modeling of this area based on imprecise cartographic objects (coastline, highest/lowest water level, etc.). The challenge of visualizing such specific area comes thus from 3D+t information, i.e. spatio-temporal data, and their visual integration.

In this paper, we present a methodology for geovisualization issues over coastal areas. The first challenge consists in integrating multi-source heterogeneous data, i.e. raster and vector, terrestrial and hydrographic data often coming from various ‘paradigms’, while providing a homogeneous geovisualization of the coastal area and in particular the phenomenon of the water depth. The second challenge consists in finding various possibilities to geovisualize this dynamic geographical phenomenon in controlling the level of photorealism in hybrid visualizations. Our approach is based on the use of a high-resolution Digital Terrain Model (DTM) coming from high resolution LiDAR data point cloud, tidal and topographic data. We present and discuss homogeneous hybrid visualizations, based on LiDAR and map, and on, LiDAR and orthoimagery, in order to enhance the realism while considering the water depth.

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Geovisualization of coastal areas from heterogeneous spatio-temporal data (Antoine Masse)

  1. 1. Antoine Masse, Sidonie Christophe IGN, COGIT Laboratory France GeoVIS 2015 - ISPRS Geospatial Week - 10/01/2015
  2. 2. GeoVIS 2015 - ISPRS Geospatial Week - 10/01/2015 2 • Coastal area Between highest astronomical tide (shoreline) and lowest astronomical tide (drying line) • Spatio-temporal objects & phenomena • Uncertainty: in motion (tides, sands) • Incompleteness of data: underwater observation problems • Imprecision: different definitions of an object at different scale Sea/Land interface ShorelineDrying line Point Reyes, California Red : DTM data (res. 1m, prec. 0,2m) Yellow : 1:15,000 topomap Blue : 1:50,000 topomap Motivation: coastal area geovisualization Different Shoreline definition
  3. 3. 3 Different uses & users  Different geovis Limitations:  Visual discontinuities and heterogeneity between sea & land  Perception of tides and/or water depth for non-specialist users C-Map®, navigation software ScanLittoral®, Touristic/Public map Interactive elevation simulation of lake Erie, USA (NOAA) Ortho-image of La Grande Motte, Google Maps® Ocean seafloor map of Hawai'i GeoVIS 2015 - ISPRS Geospatial Week - 10/01/2015 Motivation: coastal area geovisualization
  4. 4. Purpose of the talk 4 • To convey sea dynamic information to users Example of tide dynamic for informational purposes • Hypothesis: – Using heterogeneous data (maps, ortho-imagery, LiDAR)… – … to make homogeneous visualizations between sea & land – … by controlling photo-realism/abstraction – … to convey tides & water depth perception GeoVIS 2015 - ISPRS Geospatial Week - 10/01/2015
  5. 5. Implementation GeoVIS 2015 - ISPRS Geospatial Week - 10/01/2015 5 Lidar acquisition (land/sea) SHOM 0 5 10 Water elevation (in meters) Tidal data, REFMAR® project DTM (land/sea) SHOM Resolution: 1m/5m (land/sea) Vertical precision: 0.2m/0.5m (land/sea) Style Rendering Engine Final Rendering Perception Geographic feature External data Visual Variables Inspiration sources Colors, … Maps, ortho-imagery, … Abstraction, ortho-image-realism
  6. 6. Proposition of geovisualizations 6 GeoVIS 2015 - ISPRS Geospatial Week - 10/01/2015 4 examples for water depth visualization, static and dynamic Same data, different stylization of water depth: - Abstraction maps - (Ortho) photo-realism 0 5 10 Water elevation (in meters) Data Inspiration
  7. 7. 7 Inspiration: Map abstraction (1:25,000) Location: Lanildut, Finistère, France Data: DTM: Litto3D OpenData Tidal data: REFMAR OpenData Cartographic database Color map 1st example: perception of water depth by intervals Low tide 05/28/2009 14:00 Depth (m) 0 -5 -10 -20 Color Uses: Tourism, Hiking, Fishing Issues: ≠ producers ≠ uses no tidal information (ex: accessibility of Ile de Melon) GeoVIS 2015 - ISPRS Geospatial Week - 10/01/2015 High tide 05/28/2009 19:00
  8. 8. 8 1st example: perception of water depth intervals Time x4000 GeoVIS 2015 - ISPRS Geospatial Week - 10/01/2015
  9. 9. 9 Inspiration: Map abstraction 2nd example: continuous perception of water depth Location: Lanildut, Finistère, France Data: DTM: Litto3D OpenData Tidal data: REFMAR OpenData Cartographic database Colormap (interpolated) Low tide 05/28/2009 14:00 High tide 05/28/2009 19:00 GeoVIS 2015 - ISPRS Geospatial Week - 10/01/2015 Depth (m) 0 -5 -10 -20 Color
  10. 10. 10 2nd example: continuous perception of water depth Time x4000 GeoVIS 2015 - ISPRS Geospatial Week - 10/01/2015
  11. 11. 11 Inspiration: Ortho-image photo-realism Location: Lanildut, Finistère, France Data: DTM: Litto3D OpenData Tidal data: REFMAR OpenData IGN BD Ortho (land part) Colormap (interpolated) 3rd example: continuous water depth perception Depth (m) 0 -5 -10 -20 Color Uses: Exploration, landscape survey, … Issues: Color gaps Depth gaps no tidal information visualization of a specific tidal stage Low tide 05/28/2009 14:00 High tide 05/28/2009 19:00 GeoVIS 2015 - ISPRS Geospatial Week - 10/01/2015
  12. 12. 12 3rd example: water depth perception Brightness +20% Contrast +40% Time x4000 GeoVIS 2015 - ISPRS Geospatial Week - 10/01/2015
  13. 13. 13 Location: Vannes, Morbihan, France Data: DTM: Litto3D® OpenData Tidal data: REFMAR® OpenData IGN BD Ortho® (land part) Colormap (interpolated) 4th example: water depth perception Depth (m) 0 -5 -10 -20 Color Uses: Exploration, landscape survey, … Issues: Sands Sea infiltration at high tide High tide 03/21/2015 16:30 Low tide 03/21/2015 10:20 GeoVIS 2015 - ISPRS Geospatial Week - 10/01/2015 Inspiration: Ortho-image photorealism
  14. 14. 14 4th example: water depth perception Brightness +20% Contrast +40% Time x4000 GeoVIS 2015 - ISPRS Geospatial Week - 10/01/2015
  15. 15. Conclusion GeoVIS 2015 - ISPRS Geospatial Week - 10/01/2015 15 Goal: Convey sea dynamic information to geovisualization users Thoughts for coastal geovisualization: • Important: Data precision and land/sea visual continuity  improve water depth perception • Static and dynamic visualization -> different use, complementary • Abstraction/Photo-realism: same data, different stylization
  16. 16. 16 - User Evaluation: uses and users? • readability, handling, adaptation to specific use, integration in final-user applications, etc. • Task examples: How deep it is? When is it accessible? - Tool adaptability • Other data for validation • Realism improvements • With new data (ex: seafloor cover) • With new stylization tools (expressive textures like waves and sea stream, shaded relief) Perspectives Our method with other data Carmel-by-the-sea, CA, USA NOAA for DTM (sea) / Google Maps (land) Shaded relief (Yu, 2005) GeoVIS 2015 - ISPRS Geospatial Week - 10/01/2015Water texture
  17. 17. Thanks 17 mapstyle.ign.fr antoinemasse.froxygene-project.sourceforge.net/ nice software nice project nice speaker GeoVIS 2015 - ISPRS Geospatial Week - 10/01/2015

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