Perugia Voiron

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Third International Workshop on "Geographical Analysis, Urban Modeling, Spatial Statistics"

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  • 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
  • Perugia Voiron

    1. 1. A Spatio-morphological Modelling for Spread Predicting Christine Voiron – Canicio UMR ESPACE - University of Nice Sophia Antipolis / CNRS
    2. 2. The aim of the modelling <ul><li>The aim </li></ul><ul><ul><li>Predicting the broad outlines of a built-up areas extension </li></ul></ul><ul><ul><li>Providing decision makers with a tool which allows them to explore spatial consequences of different urbanisation policies </li></ul></ul><ul><li>The challenge </li></ul><ul><li>Finding a compromise between the level of generalisation and the level of accuracy </li></ul>
    3. 3. Outline <ul><li>What is a spatio-morphological modelling ? </li></ul><ul><li>A model to predict the built-up areas spread in the coastal region of Languedoc (Southern France) </li></ul><ul><li>The stages of the modelling : </li></ul><ul><li>1) determining the spatial rules of the model </li></ul><ul><li>2) simulating in a retrospective way the progressive extension of </li></ul><ul><li>the built-up areas </li></ul><ul><li>3) validating the model. </li></ul><ul><li>4) using the validated model to simulate the future extension of built-up areas. </li></ul>
    4. 4. What is a spatio-morphological modelling ? <ul><li>A spatial modelling performed by image processing and algorithms of Mathematical Morphology. MM is suited to spread models and to propagation simulations. </li></ul><ul><li>In this application, the model is deterministic, it assumes that the spatial spread depends on both distance and morphology of the built-up areas. </li></ul><ul><li>The spreading process essentially complies with elementary rules of distance to the built-up areas which are supposed to explain the major part of the spread. </li></ul>
    5. 5. Stage 1: determining the spatial rules
    6. 6. Stage 1: determining the spatial rules 98% of the new built-up areas have sprawled from the already built-up zones <ul><li>The spatial diffusion mode is that of « expansion diffusion » </li></ul><ul><li>Since 2000, the French law only permits new constructions which are contiguous to already built-up zones. </li></ul>
    7. 7. Stage 1: determining the spatial rules <ul><li>Spatial rules : </li></ul><ul><li>The new built-up areas can spread from the existing built-up elements only. </li></ul><ul><li>The spread is forbidden wherever protected natural zones exist. </li></ul><ul><li>The extension of built-up areas occurs by the progressive connection of the nearest elements. </li></ul><ul><li>These connections are performed by using operators of image analysis. </li></ul>
    8. 8. <ul><li>The spread process is performing by using 3 basic operations of Mathematical Morphology : the dilation , the erosion and the closing </li></ul><ul><li>A dilation corresponds to a thickening process of a given size </li></ul><ul><li>An erosion corresponds to a thining process </li></ul>Stage 2: simulating the spread by using image processing dilation size 1 erosion size 1
    9. 9. <ul><li>A closing is a dilation of a given size + an erosion of the same size </li></ul>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
    10. 10. <ul><li>We deal with bmp images: </li></ul>Stage 2 : simulating the spread by using image processing
    11. 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. 12. <ul><li>« The predictive models are not expected to be accurate at the pixel scale but they are expected to predict the approximative shapes and locations of the phenomenon » (Power, Simms and White, 2001) </li></ul><ul><ul><li>1) The evaluation of similarity takes into account margins of error of : </li></ul></ul><ul><li>1 pixel (37 m) </li></ul><ul><li>2 pixels (74 m) </li></ul><ul><li>3 pixels (117 m) </li></ul><ul><li>by dilating the new predicted surfaces by 1, 2 or 3 pixels successively, before performing the intersection with the new observed surfaces. </li></ul><ul><ul><li>The visual comparison can suggest the need of local calibrations </li></ul></ul>Stage 3: validating the outputs
    13. 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. 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. 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. 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. 17. Summary <ul><li>Modelling by image processing is rich in potential. MM is well adapted to spatial analysis, especially to spatial propagation simulations. </li></ul><ul><li>This model has been performed to measure how much the urban spread depends on elementary rules of distance and morphology. </li></ul><ul><li>The results give the broad outlines of the future urbanisation to be discussed with the local autorithies. </li></ul><ul><li>New spatial rules can be added to take into account the topography and the road network of the region under study. </li></ul><ul><li>This model is deterministic. We are working on a randomisation of the urban spread by combining both « dilation » operation and Poisson points diffusion. </li></ul><ul><li>In other applications as risks the prediction is based on probabilistic approaches and simulations with random spread models. </li></ul>
    18. 18. Thank you for your attention

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