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Disaster-resilience Index based on an Analytic Hierarchy Process

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Disaster-resilience Index based on an Analytic Hierarchy Process

  1. 1. Establishing a Composite Index from Criteria of Resilient Coastal Communities Determined through an Analytic Hierarchy Process (AHP) Model P.M. Orencio and M. Fujii Hokkaido University Graduate School of Environmental Science
  2. 2. Approach to Risk Mitigation in the Philippines 2000’s H= hazard V= vulnerability C= capacity Present (Heijmans and Victoria 2001) Resilient communities can absorb and manage stress and recover from serious hazard effects, but determining which capacities will render a community to be resilient is difficult. (Twigg 2007)
  3. 3. Which Capacities Make Resilient Communities?  Pilot study in Baler, Objectives: Aurora, Philippines • Determine the important criteria (AHP model) • Develop a framework • Establish a composite index  Results of Recent Vulnerability Study (Orencio 2011)
  4. 4. Analytic Hierarchy Process (AHP)  MCDA tool that uses a AHP follows a theory of 1 Goal hierarchical problem relative measurement that decomposition Criteria provides:  Local priority weights 1 2 3 (1) an ‘objective’ from Pair-wise mathematics to model Comparative Method Elements complexities of a problem, (PCM) of Judgment and 1 3 2  Global priority weight by hierarchic composition (2) a way to process (additive synthesis) A loop indicates that ‘subjective’ preferences of each element depends groups/ individuals in only on itself. decision-making. (Satty 1980) (Satty 1980) Comparison is made between two alternatives based on a decision-maker’s feeling of priority due to importance, preference and likelihood of influence
  5. 5. AHP Model for Selecting Important Criteria for Resilient Communities 1 overall objective 7 components that describe risks management and vulnerability reduction 75 attributes that describe risk- resilient communities (40) and risk reduction enabling environment (35)  20 decision-makers were asked to prioritize the alternatives across levels using the top-down (Twigg 2007; NEDA et al. 2008) evaluation
  6. 6. Decision-maker’s Guide to PCM Construct the Decision Table Judgment of Scale Description Preference Number of Two factors contribute equally to the 1 Equally important alternatives objective n Moderately Experience and judgment slightly favor 3 important one over the other Experience and judgment strongly 5 Strongly important favor one over the other Experience and judgment very strongly Very strongly 7 favor one over the other, as important demonstrated in practice The evidence favoring one over the 9 Extremely important other is of the highest possible validity Intermediate 2, 4, 6, 8 preferences When compromise is needed between scales (Satty and Vargas 1991)  Positive reciprocal  Check consistency and acceptability of square matrix judgments CR= CI/RI; (Alonso and Lamata 2006) (Coyle 2004) CR ≤ 0.10  Decide the score using geometric  Consensus (via Delphi approach) mean (Aczel and Satty 1983) (Kanyak and Macauley 1984)
  7. 7. Numerical Example  Selecting the Important Criteria (n = 7 ) New Priority Vector Eigenvector is a 1.00 3.35 1.17 1.70 5.16 2.18 0.70 0.23 1.90 0.23 vector such that 0.30 1.00 0.46 1.06 1.10 1.45 0.89 0.11 0.77 0.11 when a matrix A is 0.85 2.15 1.00 2.19 1.56 2.03 1.77 0.21 1.50 0.21 multiplied times 0.59 0.95 0.46 1.00 0.87 5.34 2.42 0.15 = 1.26 = 7.69 0.15 that vector, the 0.19 0.91 0.64 1.15 1.00 1.68 1.08 0.11 0.81 0.11 0.46 0.69 0.49 0.19 0.60 1.00 1.05 0.08 0.57 0.08 operation results in 1.42 1.12 0.56 0.41 0.93 0.95 1.00 0.11 0.92 0.11 the same vector as multiplied an Eigen Reciprocal matrix A Eigenvector value λmax The CI for randomly generated matrices of order n is called λmax> n; 7.69 > 7 the Random Index (RI) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Consistency 0.00 0.00 0.58 0.90 1.12 1.24 1.32 1.41 1.45 1.49 1.51 1.48 1.56 1.57 1.59 Index (CI) = The Consistency Ratio (CR) is the ratio CR = 0.11/ 1.32 0.69/6 = 0.11 of its CI to the RI, where a value of ≤0.10 is acceptable 0.09 or 9%
  8. 8. Most Desirable Criteria Criteria Weight Rank The selected criteria has 72% of Environmental and natural overall weights and meant that: resource management (including 1.90 1 natural capital and climate change adaptation)  Benefits can be achieved from an Health and well-being (including 0.77 6 effective resource management human capital)  A secured income sources to Sustainable livelihoods 1.50 2 Social protection (including social address fragile livelihood systems 1.26 3  Social and institutional problems capital) Financial instruments (including 0.81 5 must be resolved to improve financial capital) Physical protection; structural and conditions technical measures (including 0.57 7  The planning process should physical capital) encourage an informed decision- Planning regimes 0.92 4 making = 7.69 ; CI = 0.11 ; CR = 0.09  ≥70% of representative criteria (for the goal) or elements (for each criterion) were adopted.  All other criteria and elements were dropped from further consideration
  9. 9. Most Desirable Elements Criteria Characteristics of Disaster Risk-reduction Enabling Weight Rank Weight Rank Codes Resilient Communities Environment ENRMC1 1.62 1 ENRME1 1.31 2 ENRMC2 1.58 2 ENRME2 1.51 1 ENRM ENRMC3 0.76 ENRME3 1.03 3 ENRMC4 0.85 3 ENRME4 0.59 ENRMC5 0.67 ENRME5 0.97 = 5.47 ; CI = 0.12 ; CR = 0.10 = 5.41 ; CI = 0.10 ; CR = 0.09 SLC1 1.28 2 SLE1 1.62 2 SLC2 0.74 SLE2 0.79 4 SLC3 1.33 1 SLE3 2.19 1 SL SLC4 1.18 4 SLE4 0.77 SLC5 1.23 3 SLE5 0.77 SLC6 0.98 SLE6 0.42 SLC7 1.07 5 SLE7 1.16 3 = 7.83 ; CI = 0.14 ; CR = 0.10 = 7.76 ; CI = 0.13 ; CR = 0.10 SPC1 1.87 1 SPC2 1.63 2 SPE1 1.25 1 SP SPC3 0.72 3 SPE2 0.61 SPC4 0.62 SPE3 1.16 2 SPC5 0.67 = 5.42 ; CI = 0.11 ; CR = 0.09 = 3.03 ; CI = 0.02 ; CR = 0.03 PRC1 1.27 1 PRE1 0.91 3 PRE2 1.47 1 PR PRC2 0.61 PRE3 0.75 PRC3 1.15 2 PRE4 1.02 2 = 3.04 ; CI = 0.02 ; CR = 0.03 = 4.16 ; CI = 0.05 ; CR = 0.06
  10. 10. Coastal Community Resilience Framework Weighting System for Indicators using Min- Max Normalization Method Where each W is from the new priority vector Process indicators to measure community understanding, Conceptual ownership and the sustainability of a disaster resilience program Composite Outcome indicators to measure real achievements in terms of Index community empowerment and capacity building (Kafle 2010)
  11. 11. The Composite Index Adopt the steps in the Integrated Community Use the AHP-selected criteria and Based Risk Reduction (ICBRR) Approach elements
  12. 12. Weighting and Scoring System Attribute Elements Normalized Criteria Characteristics of Disaster Normalized Risk-reduction Enabling Normalized Weights Resilient Communities Weights Environment Weights ENRMC1 0.47 ENRME1 0.35 ENRM 0.40 ENRMC2 0.44 ENRME2 0.44 ENRMC4 0.09 ENRME3 0.21 SLC1 0.23 SLC3 SLE1 0.29 0.25 SLE2 0.09 SL 0.28 SLC4 0.18 SLE3 0.43 SLC5 0.21 SLE7 0.18 SLC7 0.14 SPC1 0.53 SPE1 0.54 SP 0.21 SPC2 0.43 SPE3 0.46 SPC3 0.04 PRE1 0.14 PRC1 0.55 PR 0.11 PRE2 0.63 PRC3 0.45 PRE4 0.23 Level 0 Absence of a clear and coherent activity(ies) in an overall disaster risk reduction program. Level 1 Little awareness of the issue(s) or motivation to address them. Actions limited to crisis response. Awareness of the issue(s) and willingness to address them. Capacity to act (knowledge and skills, human, Level 2 material and other resources) remains limited. Interventions tend to be one-off, piecemeal and short-term. Development and implementation of solutions. Capacity to act is improved and substantial. Interventions are Level 3 more numerous and long-term. Coherence and integration. Interventions are extensive, covering all main aspects of the problem, and they are Level 4 linked within a coherent long-term strategy. A ‘culture of safety’ exists among all stakeholders, where DRR is embedded in all relevant policy, planning, Level 5 practice, attitudes and behavior.
  13. 13. Computations using Weighted Linear Method 1.00 0.50 0.50 Criteria Score (CS) 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 Process Indicator Score (ES) Outcome Indicator Score (ES) Index Score (IS)  The ICBRR approach covers both pre and post disaster intervention but is not so popular in the Philippines, however, the process indicators here do not bias of the metrics
  14. 14. Summary and Conclusion  Resilience of coastal communities is difficult to determine since this is influenced by various factors (internal and external)  AHP, as a method, was able to provide objective assessment in: • selecting important criteria and attribute elements; and • establishing component-specific ranking system  A framework was developed based on the selected criteria for coastal community resilience as an important step in baseline assessment, and this had lead to: • selection of component indicators of a composite index • determine indicators for process (ICBRR approach) and outcome (AHP-selected criteria and elements) components • provide metrics for measuring overall index  A conceptual method for assessing coastal community resilience was proposed and these can provide information for subsequent risk reduction planning at the local levels.
  15. 15. Boys, be ambitious! This was the message of William Smith Clark. Be ambitious not for money or for selfish aggrandizement, nor for that evanescent thing which men call fame. Be ambitious for knowledge, for righteousness, and for the uplift of your people. Be ambitious for the attainment of all that a man ought to be. by Paul Rowland, 1915 Ginko drive during winter. Picture taken from the east gate of Hokkaido University. Thank you for your attention!

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