Spatial Statistics and Composite Indicators:                    a review of existing case studies                         ...
SummaryComposite indicators and the spatial dimensionCritical analysis of recent advancesOpen issues for further researchD...
Composite indicatorsMultidimensional measureDescription of complex characteristics of realitySynthesises the effects of a ...
CI: application domainSocio-economic systemsPolicy-making support toolUsually based on a-spatial dataCI reference to spati...
CI: application domain Usually based on a-spatial data CI reference to spatial units (administrative boundary)            ...
Building CIsTheoretical framework                       Weighting and aggregationData selection                           ...
CI and Spatial statistics:                                  understanding the spatial structure            CI values may b...
Spatial Dimension of CI                                                            State of ArtRecent growing interests to...
Analysis of recent advances:                                  Spatial CI MatrixTaxonomy of three main domains:        Indi...
Spatial CI matrix structure:                          Spatial CI                                        Spatial CI Matrix ...
Matrix(1): IndicatorsIndicators give meta-information about CI:        Indicator (name)        Authors        Composite   ...
Matrix (2): Sub-domainSub-domain shows which are the sub-factors considered to define theCI: EconomySocialEnvironment D. T...
Matrix (3): Methods Describes the methodology and technical aspects used for analysingthe spatial dependence of the CI: Sp...
Results CI are often used only in the socio-economic field  Spatial dimension in composite indicator is still a rather une...
Open research issues More research to understand the implication for CIs in terms of spatialdependence New methods to exte...
Thank you  for your attention!  Questions, comments, remarks, suggestions are  welcome!D. Trogu                           ...
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Daniele Trogu and Michele Campagna on "Spatial Statistics and Composite Indicators: a review of existing case studies and open research issues on Spatial Composite Indicators"

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Trogu & Campagna - input2012

  1. 1. Spatial Statistics and Composite Indicators: a review of existing case studies and open research issues on Spatial Composite Indicators by Daniele Trogu, Michele CampagnaD. Trogu daniele.trogu@unica.itM. Campagna campagna@unica.it
  2. 2. SummaryComposite indicators and the spatial dimensionCritical analysis of recent advancesOpen issues for further researchD. Trogu daniele.trogu@unica.itM. Campagna campagna@unica.it
  3. 3. Composite indicatorsMultidimensional measureDescription of complex characteristics of realitySynthesises the effects of a certain set of sub-factorsProvide performance ranking of spatial unitsD. Trogu daniele.trogu@unica.itM. Campagna campagna@unica.it
  4. 4. CI: application domainSocio-economic systemsPolicy-making support toolUsually based on a-spatial dataCI reference to spatial units (administrative boundary)D. Trogu daniele.trogu@unica.itM. Campagna campagna@unica.it
  5. 5. CI: application domain Usually based on a-spatial data CI reference to spatial units (administrative boundary) 1 INDICATOR is AVG. MEASURE ? ? ? 2 ? LARGE SMALL-SCALE SPATIAL UNITNO SPATIAL MEASURES ? ? ? ? ? D. Trogu daniele.trogu@unica.it M. Campagna campagna@unica.it
  6. 6. Building CIsTheoretical framework Weighting and aggregationData selection Robustness and sensitivityImputation of missing data Back to the real dataMultivariate analysis Links to other variables Presentation and visualizationNormalisation (Source: OECD and JRC, 2008) D. Trogu daniele.trogu@unica.it M. Campagna campagna@unica.it
  7. 7. CI and Spatial statistics: understanding the spatial structure CI values may be not random in space CI value patterns may be spatial dependentThus, spatial dependence must be take into account in forecastmodelsIn policy-makingaccounting for the spatial structure allows to better understandphenomena in spatial units D. Trogu daniele.trogu@unica.it M. Campagna campagna@unica.it
  8. 8. Spatial Dimension of CI State of ArtRecent growing interests towards the spatial dimension of CI due to: Advance in technologies (computing power & software)Advance in spatial data availability (e.g. Spatial Data Infrastructures) D. Trogu daniele.trogu@unica.it M. Campagna campagna@unica.it
  9. 9. Analysis of recent advances: Spatial CI MatrixTaxonomy of three main domains: Indicators Sub-domains Methods D. Trogu daniele.trogu@unica.it M. Campagna campagna@unica.it
  10. 10. Spatial CI matrix structure: Spatial CI Spatial CI Matrix Matriix Indicators Sub-domains Methods Indicator Economy Spatial features Authors Social Spatial Units Composite Environmental Study of spatial Domain dependenceD. Trogu daniele.trogu@unica.itM. Campagna campagna@unica.it
  11. 11. Matrix(1): IndicatorsIndicators give meta-information about CI: Indicator (name) Authors Composite Domain D. Trogu daniele.trogu@unica.it M. Campagna campagna@unica.it
  12. 12. Matrix (2): Sub-domainSub-domain shows which are the sub-factors considered to define theCI: EconomySocialEnvironment D. Trogu daniele.trogu@unica.it M. Campagna campagna@unica.it
  13. 13. Matrix (3): Methods Describes the methodology and technical aspects used for analysingthe spatial dependence of the CI: Spatial featuresSpatial unitsStudy of Spatial Dependence D. Trogu daniele.trogu@unica.it M. Campagna campagna@unica.it
  14. 14. Results CI are often used only in the socio-economic field Spatial dimension in composite indicator is still a rather unexploredfieldSpatial units are usually administrative boundarySpatial data are seldom used in CIs construction Spatial location may influence the performance of a given spatialunits D. Trogu daniele.trogu@unica.it M. Campagna campagna@unica.it
  15. 15. Open research issues More research to understand the implication for CIs in terms of spatialdependence New methods to extend CIs design methodologies to the case ofspatial data (i.e. GIS based spatial composite indicators) Possibility to choose spatial units on the basis of particular spatialfeatures of phenomena (e.g. Landscape value or Env. Sustainability) Understand how spatial analysis can help in the definition of SpatialComposite Indicator D. Trogu daniele.trogu@unica.it M. Campagna campagna@unica.it
  16. 16. Thank you for your attention! Questions, comments, remarks, suggestions are welcome!D. Trogu daniele.trogu@unica.itM. Campagna campagna@unica.it
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