Maltinti, Melis and Annunziata - input2012
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Francesca Maltinti, Daniela Melis and Francesco Annunziata on "GIS applications for vulnerability assessment of a road network"

Francesca Maltinti, Daniela Melis and Francesco Annunziata on "GIS applications for vulnerability assessment of a road network"

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Maltinti, Melis and Annunziata - input2012 Presentation Transcript

  • 1. by F. Maltinti, D. Melis, F. AnnunziataSeventh International Conference on Informatics and Urban and Regional Planning, University of Cagliari 10-12 May 2012
  • 2. IntroductionAimDescribing methodologyCase studyConclusion and Further studies. input 2012, F. Maltinti "Gis applications for vulnerability assessment of a road network"
  • 3. Transport infrastructures guarantee accessibilityImportance of accessibility during emergencysituationsKnowledge of road network vulnerability isfundamental to manage risks input 2012, F. Maltinti "Gis applications for vulnerability assessment of a road network"
  • 4. Studying a new methodology for assessing roadnetwork vulnerability to: Identify a vulnerability index correlated to design and geometric characteristics of roads Identify critical links of a road network to define improvements priorities Guarantee accessibility during emergency situations input 2012, F. Maltinti "Gis applications for vulnerability assessment of a road network"
  • 5. Territorial analysis Road network analysis Identification of weak links Link interruption Calculation of shortest paths matrix Calculation of vulnerability index Maps of vulnerability and priority input 2012, F. Maltinti "Gis applications for vulnerability assessment of a road network"
  • 6. The proposed Total vulnerability index is expressed by: vulnerktot=vulnerkglob-norm+vulnerkO/Dresc-norm+vulnerkshorth-path-norm where: is the normalized indicator for vulnerability assessment1) vulnerkglob-norm=f[ΣiΣj (tkij-t0ij)] connected to the whole network [i, j =urban nodes, k=weak links] is the normalized indicator for the vulnerability2) vulnerkO/Dresc-norm=f[ΣiΣj (tkij-t0ij)] assessment connected to the rescue operation [i, =relief operation centres, j= urban nodes destination of relief]3) vulnerkshorth-path-norm=f[ΣiΣj (nkij)] is the normalized indicator for the vulnerability 1 if ∆tkij>0 assessment connected to the number of shortest pathsnkij= involved in a link closure 0 if ∆tkij<0 input 2012, F. Maltinti "Gis applications for vulnerability assessment of a road network"
  • 7. The index to assess municipality exposure is: exposurei=f[(ΣkΣj(tkij–t0ij)] To consider population the function can be rewrite as follows: exposureweii=f[Pi/Ptot,ΣkΣj(tkij–t0ij)] We used: • ArcView GIS, to record georeference and process data, and finally to realize the network vulnerability map; • ArcGis Network Analyst extension to calculate the matrix of the shortest paths, and also to construct the matrix of road distances. We have obtained travel time by dividing the length by the travel speed of the road link and travel speed by the design characteristics of the horizontal alignment of the road to which the link belongs input 2012, F. Maltinti "Gis applications for vulnerability assessment of a road network"
  • 8. Hypotheses (coming from Italian Geometric Design Standards of Roads):• the vehicle is isolated: its speed is not affected by traffic conditions;• the road gradient does not influence vehicle speed;• on tangents the vehicle follows the equations of uniformly accelerated linear motion until it reaches the designed speed limit;• on curves vehicle speed depends on the radius of the curves and on the road category.The first one is not easily verified, but it appears valid for roads located in sparselypopulated areas with low traffic volume. input 2012, F. Maltinti "Gis applications for vulnerability assessment of a road network"
  • 9. This road network has beeninterrupted because of landslidesand floods on different occasions.Figure shows the vulnerability mapof the road network. The methodology wasCentral links are the most applied to Ogliastra roadvulnerable: network. Ogliastra is a they belong to different sparsely populated area shortest paths located in Sardinia (Italy). they are used for rescue services for which there are no alternative routes.
  • 10. These figures show municipality exposure to the event:The figure on the left shows that more vulnerable municipalities are localized in central-southern area of the region characterized by low population density. The situation is completely different (see the figure on the right) using function considering local population: more vulnerable municipalities are localized in north- eastern and south- eastern area of the region because they are more populated than central-southern area exposurei=f[(ΣkΣj(tkij–t0ij)] exposureweii=f[Pi/Ptot,ΣkΣj(tkij–t0ij)]
  • 11. The proposed methodology:• expresses vulnerability of a road network considering geometric and design characteristics of the elements of road.• attaches more importance to peripheral links which are particularly critical because they have not alternative paths and their closure can completely isolate an area. The methodology is specifically effective in areas of low population density and where traffic flow is poor. It could represent a new tool for roads administrators to define improvement priorities and to manage emergency situations.The study is going on including other road design characteristics (e.g. road gradient),identifying combinations of link failures and considering different hazards in thedefinition of the index. input 2012, F. Maltinti "Gis applications for vulnerability assessment of a road network"
  • 12. F. Maltinti "Gis applications for vulnerability assessment of a road network" Seventh International Conference on Informatics and Urban and Regional Planning, University of Cagliari 10-12 May 2012