A4 - Woloszyn et Leduc. Caractérisation du potentiel paysager par le dimensionnement spatial des champs d’ambiances du piéton en milieu urbain

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  • 1. 1st  intercon+nental  Conference  of  Territorial  Intelligence    IT-Gatineau 2011, Oct. 12-14, 2011 A landscape potential characterization: spatial template of pedestrian ambient fields within the urban fabric P. Woloszyn and T. Leduc ESO and CERMA Laboratories, CNRS, France
  • 2. Outline  Context and motivations  Visual perception using isovists field  The method we developed  Use case and results  Conclusion and outlook
  • 3. Context and motivations : the socio-ecological transition trade-off Income  distribu7on  law   Powerty/inequality  measurements   Economical   NEEDS   Social   Entropy   Socioeconomical  weight     Entropy   RESOURCE   DEVELOPMENT   Econogical   weight     Socioecological  weight   Environmental   Entropy   Microambients  economics  
  • 4. Focus on visual ambiences : isovists field  The isovist is simply the Gibsonian optic array, with the wavelength and intensity information omitted,  It describes local geometrical properties of spaces with respect to individual observation points and weight all the possible view directions equally. It is a 2D horizontal slice of pedestrians surrounding space;  The set of all points in an environment of opaque surfaces that are visible from a given view-point;  A useful tool to define the open space concept (= the empty space, the void, between the surrounding buildings).
  • 5. Our proposal  Combine:   A sort of “surface ray casting” strategy (an angular abscissa sampling of the star-shaped isovist),   With a tool from information theory (Shannon entropy),  So as to produce:   A sensory based Digital Terrain Model
  • 6. Some more details  sample the region of interest into a set of punctual positions  in each of these punctual locations, determine the corresponding partial isovist  convert all these isovists (2D star shaped polygons) into a set of function of radial distances (dimension reduction operation)  lets assume that each function of radial distances represent a 1D random variable, and compute the corresponding Shannon entropy value  represent all these entropy values into a raster color map
  • 7. Function of radial distances and dimension reduction operation  Nyquist–Shannon sampling theorem  Shannon entropy computation
  • 8. Use case  Place Royale square
  • 9. Position #1 H=0.77
  • 10. Position #2 H=0.78
  • 11. Position #3 H=0.86
  • 12. Position #4 H=0.87
  • 13. Position #5 H=0.88
  • 14. Conclusion and outlookDone- landscape visual space geo-topical modeling- angular perspective variability computation- spatial potential, allowing a pedestrian to diversify hisvisual landscape during his walk - advanced overview of the complexity and the richness of the urban fabricFutureChallenge is to investigate the inter-sensorial ambient-scape as a basis of a multi-sensory conception intownscape planning and design
  • 15. AcknowledgementsTo:F Gonzalez Cortés (Spain) for all the developmentsperformed on the GearScape GIS.And to:Assistant Professor B Suner (from the National Schoolof Architecture of Nantes city, France) for his significanthelp in the production of the panoramic snapshots.
  • 16. References