Post-Earthquake Building Damage and Fatality Estimation System (Ebdfes)

1. System Functionality

Ebdfes is a real-time earthquake impact estimation system that automatically triggers the evaluation of building loss and fatality. It provides probability distributions and spatial distribution results to help quickly assess post-earthquake impacts.

2. Environment Requirements

• Operating System: Windows
• Python: Version 3.11 or higher
• Dependencies: requests, json, apscheduler, pandas, numpy, scipy, math, random, threading, queue, warnings
• Database: MySQL (pymysql and dbutils packages required)
• Frontend and API: See /api and /frontend directories
• Local Storage: Analysis results can be saved to a custom path using /example/Example_Estimation.py

3. Basic Files

Users need to prepare the following basic data:

• Location data of locations of interest
• Exposure data
• Vulnerability models

Example data can be found in the /exposure_data directory.

4. Usage

4.1 Automatic Operation

• Main Program: /code/Main.py
• Function: Continuously monitors earthquake events and automatically triggers analysis
• Setting Time Interval: Adjust the minutes parameter in sched.add_job to balance timeliness and computational cost
• Avoiding Duplicate Events: The system creates a MySQL table to avoid processing the same earthquake event multiple times
• Deployment: Configure the MySQL connection and run /code/Main.py

4.2 Single Earthquake Assessment

• Script: /example/Example_Estimation.py
• Function: Set earthquake source parameters and run the script to perform the assessment
• Example: Predefined parameters for the 2024 Noto Peninsula earthquake
• Execution: Run the script directly, and the progress will be displayed in the console

5. API and Frontend

• Function: Provides an intuitive display of earthquake consequences
• Deployment: Relevant programs can be found in the /frontend/src/api and /frontend directories

6. Supporting Literature

• [1] ZHAO D, WANG Z, WANG J, et al. A Rapid Estimation Method for Post-earthquake Building Losses [J]. International Journal of Disaster Risk Science, 2023: 1-12.
• [2] WANG Z, ZHAO D, WANG J, et al. Application of an integrated earthquake loss estimation method in the 2024 Hualien Mw7.4 earthquake [J] Natural Hazards. 2025: 1-25.
• [3] Zhao D, Wang Z, Liu Y, et al. Seismic loss uncertainty analysis based on actual seismic data from New Zealand [J]. Earthquake Engineering and Engineering Dynamics, 2021, 41(02): 84-95.
• [4] Zhou Y, Wang Z, Shi L et al. Spatial correlation of earthquake loss and its impact on earthquake loss distribution estimation [J]. World Earthquake Engineering, 2022, 38(02): 151-9.
• [5] Zhao D, Wang Z, Li Z, et al. Luding Ms6.8 Earthquake Rapid Assessment of Building Losses [J]. World Earthquake Engineering, 2023, 39(2).