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A  Spatio-morphological  Modelling  for  Spread  Predicting Christine Voiron – Canicio UMR ESPACE - University of Nice Sophia Antipolis / CNRS
The aim of the modelling ,[object Object],[object Object],[object Object],[object Object],[object Object]
Outline ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
What is a spatio-morphological modelling ? ,[object Object],[object Object],[object Object]
Stage 1:  determining the spatial rules
Stage 1:  determining the spatial rules 98% of the new built-up areas have sprawled from the already built-up zones ,[object Object],[object Object]
Stage 1:  determining the spatial rules ,[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],Stage 2:  simulating the spread  by using image processing  dilation size 1 erosion size 1
[object Object],Stage 2:  simulating the spread  by using image processing   The result of a closing is : i) the clustering of parts in the set under study ii) the hole filling action  The spread process will be performed by using conditional closings of increasing size = + a closing size 2
[object Object],Stage 2 :  simulating the spread  by using image processing
Y Coefficient simil Image A1: Built-up areas in 1977 Image B: closing of size i I = i+ 1 simil is  higher ? Elimination of points falling into sea, ponds, protected zones Image A2: observed built-up areas  in 1990 Image B: result of closing simil (A2,B) = surface of intersection (A2,B) / surface of union (A2,B)   Y Matching Flow chart of the spread modelling by image processing N The ctiterion for stopping the spread is the value of simil. The matching is performed for all probable sizes of closing, one takes that which maximizes simil
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Stage 3:  validating the outputs
Application: basic model simil calculated on the new built-up areas = 0.257   Results of the model 71% 65% 58% 48.5% Margin of error 3 pixels Margin of error 2 pixels Margin of error 1 pixel Pixel agreement
Improving the model Subset 1: « attractive zones »: Stage 1: new spread process Subset 2: rest of the built-up areas Stage 2: protocol used to the 1st model
Application: Improved model simil calculated on the new built-up areas = 0.41   Results of the model 77% 72% 65% 58% Improved model 71% 65% 58% 48.5% Basic model Margin of error 3 pixels Margin of error 2 pixels Margin of error 1 pixel Pixel agreement
Stage 4: simulating the future extension of built-up areas This improved model is applied to seek the broad outlines of the future built-up surfaces, up to 2010   2  spread rates have been tested   6  % 3  %
Summary ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Thank you for your attention

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Perugia Voiron

  • 1. A Spatio-morphological Modelling for Spread Predicting Christine Voiron – Canicio UMR ESPACE - University of Nice Sophia Antipolis / CNRS
  • 2.
  • 3.
  • 4.
  • 5. Stage 1: determining the spatial rules
  • 6.
  • 7.
  • 8.
  • 9.
  • 10.
  • 11. Y Coefficient simil Image A1: Built-up areas in 1977 Image B: closing of size i I = i+ 1 simil is higher ? Elimination of points falling into sea, ponds, protected zones Image A2: observed built-up areas in 1990 Image B: result of closing simil (A2,B) = surface of intersection (A2,B) / surface of union (A2,B) Y Matching Flow chart of the spread modelling by image processing N The ctiterion for stopping the spread is the value of simil. The matching is performed for all probable sizes of closing, one takes that which maximizes simil
  • 12.
  • 13. Application: basic model simil calculated on the new built-up areas = 0.257 Results of the model 71% 65% 58% 48.5% Margin of error 3 pixels Margin of error 2 pixels Margin of error 1 pixel Pixel agreement
  • 14. Improving the model Subset 1: « attractive zones »: Stage 1: new spread process Subset 2: rest of the built-up areas Stage 2: protocol used to the 1st model
  • 15. Application: Improved model simil calculated on the new built-up areas = 0.41 Results of the model 77% 72% 65% 58% Improved model 71% 65% 58% 48.5% Basic model Margin of error 3 pixels Margin of error 2 pixels Margin of error 1 pixel Pixel agreement
  • 16. Stage 4: simulating the future extension of built-up areas This improved model is applied to seek the broad outlines of the future built-up surfaces, up to 2010 2 spread rates have been tested 6 % 3 %
  • 17.
  • 18. Thank you for your attention

Notes de l'éditeur

  1. Du fait même de la définition de l’INSEE, sont exclus du recensement tous les logements appartenant à une personne âgée placée dans une institution, les logements en attente de règlement de succession