Year: 2024
Type: conference-paper
Abstract: The unpredictability of earthquakes causes severe damage and loss to communities due to inadequate disaster preparedness and management strategies.Geographic information systems can employ relational geodatabase models to incorporate massive geospatial layers to assess regional seismic risks and quantify building and population vulnerabilities.This review discusses and compares recent literature on GIS-based earthquake risk models to identify similarities and novelties in methodologies and calculations using geostatistical functions and multi-criteria decision analysis.Generated maps illustrate different approaches to visualizing risk levels and damage and loss estimation.Insights on the visualized data were provided to assess the correlation between overlain data layers and their influence on the resulting risk assessment.Research gaps were identified and outlined to encourage further research on seismic risk using dynamic relational geodatabases in the Philippines.Addressing the identified research gaps and focusing on the suggested improvement areas can enhance seismic risk assessments.
DOI: 10.5109/7323342
Authors: Jomari Tan, Mary Joanne Aniñon
Institution: De La Salle University
Language: English
Subfield: Civil and Structural Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4404647648