Kernel Density Estimation Methods for a Geostatistical Approach in Seismic Risk Analysis: the Case Study of Potenza Hillto...
The problem: the seismic approach Program of prevision, prevention and protection Seismic event consequences evaluation an...
Analysis of seismic damage scenarios: instruments European Macroseismic Macroscale 1998 Vulnerability classes Damage level...
Analysis of seismic damage scenarios: limits <ul><li>Seismogeological effects </li></ul><ul><li>Mutual pounding of adjacen...
Methods: the Kernel Density Estimation (KDE)
KDE: intensity <ul><li>“ 3rd dimension” of the distribution </li></ul><ul><li>Measure identifying event strength  </li></u...
KDE: intensity and its measures First order effects (Absolute location)  Second order effects ( Relative location ) Proper...
KDE: kernel functions
KDE: grid resolution
KDE: bandwidth Smaller Bandwidth (Levine, 1999) Greater Bandwidth (Levine, 1999) Relation between the bandwidth dimension ...
KDE: bandwidth approaches
KDE: a method for the right choose of bandwidth Nearest-Neighbor Index Nearest-Neighbor Expected Distance NNI > 1     obs...
KDE: classification of results
The case of study: Potenza hilltop town 1857 1930 1980 Over-consolidated clayey substratum Sandy-conglomerate deposit lays...
The case of study: Potenza hilltop town
The case of study: parameters selection <ul><li>Intensity choice </li></ul><ul><li>Building as autonomous scale (EMS98) </...
The case of study: parameters selection Intensity choice 6 5 D5 5 4 D4 3 3 D3 2 2 D2 1 1 D1 Intensity in northern sector I...
The case of study: parameters selection Kernel choice Cell size choice 0.1m
The case of study: parameters selection Bandwidth choice 6.8 Nearest neighbour mean calculated for  whole point pattern Fi...
The case of study: parameters selection Bandwidth choice Sum of two resultant raster   3.9 6.8 D1-2-3 damage level: averag...
The case of study: parameters selection Bandwidth choice Sum of two resultant raster 1.4÷9.9 6.8 4.1 D1-2-3 damage level: ...
Results
Conclusions and future developments <ul><li>The use of geostatistics to process historical macro-seismic data is a new fie...
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Danese Murgante Lazzari Risk

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

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Danese Murgante Lazzari Risk

  1. 1. Kernel Density Estimation Methods for a Geostatistical Approach in Seismic Risk Analysis: the Case Study of Potenza Hilltop Town (southern Italy) Maria Danese * , **, Maurizio Lazzari * , Beniamino Murgante ** International Conference on Computational Science and Its Applications (ICCSA 2008) - 30June -3July 2008 - Perugia, Italy * National Counsil of Research Archaeological and Monumental Heritage Institute, ** Università degli Studi della Basilicata, Dipartimento di Architettura, Pianificazione ed Infrastrutture di Trasporto
  2. 2. The problem: the seismic approach Program of prevision, prevention and protection Seismic event consequences evaluation and damages quantification Analysis of seismic damage scenarios
  3. 3. Analysis of seismic damage scenarios: instruments European Macroseismic Macroscale 1998 Vulnerability classes Damage levels Historical macroseismic scenarios Relationships between macroseismic intensity and damage levels
  4. 4. Analysis of seismic damage scenarios: limits <ul><li>Seismogeological effects </li></ul><ul><li>Mutual pounding of adjacent buildings </li></ul>Factors that needs a better evaluation “ The increase in shaking due to soil amplification or topographical conditions is part of the effects that intensity is a record of, and part of the hazard to which the built environment is exposed” * * Grünthal, G. G.: European Macroseismic Scale 1998. Conseil de l’Europe Cahiers du Centre Européen de Géodynamique et de Séisomologie, vol. 15 Luxembourg (1998) Importance of the spatial component in seismic damage scenarios
  5. 5. Methods: the Kernel Density Estimation (KDE)
  6. 6. KDE: intensity <ul><li>“ 3rd dimension” of the distribution </li></ul><ul><li>Measure identifying event strength </li></ul><ul><li>Connected to the case study nature </li></ul>
  7. 7. KDE: intensity and its measures First order effects (Absolute location) Second order effects ( Relative location ) Properties of a spatial distribution* *Gatrell et al. (1996)
  8. 8. KDE: kernel functions
  9. 9. KDE: grid resolution
  10. 10. KDE: bandwidth Smaller Bandwidth (Levine, 1999) Greater Bandwidth (Levine, 1999) Relation between the bandwidth dimension and the study area
  11. 11. KDE: bandwidth approaches
  12. 12. KDE: a method for the right choose of bandwidth Nearest-Neighbor Index Nearest-Neighbor Expected Distance NNI > 1  observed distance is higher than the expected distance; events are more scattered than expected. NNI < 1  observed distance is smaller than expected distance Nearest-Neighbor Observed Distance
  13. 13. KDE: classification of results
  14. 14. The case of study: Potenza hilltop town 1857 1930 1980 Over-consolidated clayey substratum Sandy-conglomerate deposit lays Narrow asymmetrical ridge
  15. 15. The case of study: Potenza hilltop town
  16. 16. The case of study: parameters selection <ul><li>Intensity choice </li></ul><ul><li>Building as autonomous scale (EMS98) </li></ul><ul><li>Relationship within buildings through reciprocal proximity and morphological factors </li></ul>
  17. 17. The case of study: parameters selection Intensity choice 6 5 D5 5 4 D4 3 3 D3 2 2 D2 1 1 D1 Intensity in northern sector Intensity in middle-southern sector Damage level
  18. 18. The case of study: parameters selection Kernel choice Cell size choice 0.1m
  19. 19. The case of study: parameters selection Bandwidth choice 6.8 Nearest neighbour mean calculated for whole point pattern Fixed for whole point pattern 1 KD map t (m) Methods used to estimate t Bandwidth approach Case
  20. 20. The case of study: parameters selection Bandwidth choice Sum of two resultant raster 3.9 6.8 D1-2-3 damage level: average of building’s minimum semi-dimension. D4-5 damage level: nearest neighbour mean calculated for whole point pattern. Two different fixed bandwidths 2 KD map t (m) Methods used to estimate t Bandwidth approach Case
  21. 21. The case of study: parameters selection Bandwidth choice Sum of two resultant raster 1.4÷9.9 6.8 4.1 D1-2-3 damage level: building’s minimum semi- Dimension D4-5 damage level: Building’s area ≤ mean + sd nearest neighbour mean calculated for whole point pattern Building’s area > mean + sd nearest neighbour mean calculated for whole point pattern multiplied by correction. One KDE with Fixed method, one with Adaptive method 3 KD map t (m) Methods used to estimate t Bandwidth approach Case
  22. 22. Results
  23. 23. Conclusions and future developments <ul><li>The use of geostatistics to process historical macro-seismic data is a new field of application of these techniques and represents a new approach to territorial analysis. </li></ul><ul><li>Developments of the spatial analysis </li></ul><ul><ul><li>Considering more parameters that can influence the result </li></ul></ul><ul><li>Fields of application </li></ul><ul><ul><li>Possibility to define urban areas historically most exposed to seismic risk, achieving useful knowledge bases for emergency planning in case of earthquakes. This work could be also a good basis for Civil Defence Plan re-examination concerning the definition of waiting and refuge areas and strategic points of entrance to old town centre. </li></ul></ul><ul><ul><li>Possibility to define monumental heritage and strategic buildings that could be most exposed to seismic risk </li></ul></ul>
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