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Cluster Analysis and Discriminant Analysis for Determining Post-Earthquake Road Recovery Patterns
Jieling Wu1, Mitsugu Saito1, Noriaki Endo2
1Design and Media Technology, Graduate School of Engineering, Iwate University, Morioka 020-8551, Japan.
Sensors (Basel, Switzerland)
|March 26, 2022
Summary
This study validates road recovery patterns after the 2011 Tohoku earthquake using discriminant analysis. Findings show road recovery correlates with topography and road importance, aiding future disaster response planning.
Area of Science:
- Disaster management
- Transportation engineering
- Geospatial analysis
Background:
- The 2011 Tohoku earthquake severely damaged Japan's transport network.
- Assessing post-earthquake road recovery is crucial but time-consuming.
- Previous cluster analysis of road usage data lacked validation.
Purpose of the Study:
- To propose a framework for determining post-earthquake road recovery patterns.
- To validate previous cluster analysis findings using discriminant analysis.
- To identify common characteristics of road recovery patterns.
Main Methods:
- Applied discriminant analysis to validate previous cluster analysis results.
- Mapped road recovery patterns to identify common characteristics.
- Analyzed objective data on regional characteristics like topography and road importance.
Main Results:
- Validated road recovery patterns identified through cluster analysis.
- Identified common characteristics of road recovery patterns.
- Found that road recovery conditions correlate with topography and road importance.
Conclusions:
- The proposed framework effectively determines post-earthquake road recovery patterns.
- Topography and road importance are key factors influencing road recovery.
- Findings can inform future disaster response and infrastructure management.
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