Seismic Activity Characteristics in Sichuan-Yunnan Region Revealed by Big Data Analysis

0. Description

This document presents three distinct big data visualization methods for earthquake catalog data, effectively illustrating the relationships among magnitude, frequency, occurrence time, and epicenter location within large-scale earthquake datasets.

A brief comparison of the advantages and disadvantages of different earthquake catalog visualization approaches is summarized in the table below:

Method	Earthquake Frequency	Occurrence Time	Epicenter Location	Magnitude	Seismic Hazard
Traditional Methods
2D/3D Scatter Plot	○ (shaded)	✕	✓	○ (shaded)	✕
M-T Plot	○ (shaded)	✓	✕	○ (shaded)	✕
Heat Map	○	✕	✓	○	✕
Methods in This Paper
M-F Plot	✓	✕	✓	✓	✕
M-F Plot Based on RBF Kernel	✓	✕	✓	○	✓
Improved M-T Plot	✓	✓	✕	✓	✕

Note:   ✓: Definitely represented       ○: Optionally represented       ✘: Not represented

1. Scatter Plot of the Earthquake Catalog Dataset

2D Scatter Plot

3D Scatter Plot

2. M-T Plot

M-T Plot

3. Earthquake Heat Map

Heat Map

The solid lines in the figures represent the major active faults in the Sichuan-Yunnan region, labeled as follows:

1. Daliangshan Fault
2. Ganzi–Yushu Fault
3. Honghe Fault
4. Minjiang-Huya Fault
5. Lancang Fault
6. Lijiang–Xiaojinhe Fault
7. Litang–Batang Fault
8. Longmenshan Fault
9. Longriba Fault
10. Nantinghe Fault
11. Nujiang–Ayeyarwaddy Fault
12. Weixi–Qiaohou Fault
13. Xianshuihe-Anninghe-Zemuhe-Xiaojiang Fault
14. China-Burma Fault

(Fault Data Source: Follow this link)

4. M-F Plot

M-F Plot

5. M-F Plot Based on RBF Kernel

This plot assesses the damage caused by earthquakes of varying magnitudes, utilizing a visual characterization scheme based on Gaussian kernel functions derived from M-F diagrams.

5.1 Function

Function Image

5.2 Results

M-F Plot Based on RBF Kernel(1970-2020)

M-F Plot Based on RBF Kernel(2000-2010)

6. M-T Hotmap

M-T Hotmap

7. Comprehensive 3D Animation

This video integrates over 420,000 earthquake entries of magnitudes 1.0 and above from the Sichuan-Yunnan region, covering the period from 1970 to 2020. It includes data on more than 160 three-dimensional active faults, high-precision topographic information, community velocity models, and the depth of the Moho surface, elucidating the seismic activity characteristics in this region over the past fifty years.

(Complete 3D Visualization Video: Visit on YouTube)

How to Use

1. Installation

1.1 Clone the Repository

Clone the repository to your local machine:

git clone https://github.com/peixyhe/seismic-catalog_vis_demo.git
cd seismic-catalog_vis_demo-master

1.2 Create a Conda Environment

This project relies on several libraries, which can be installed via the environment.yml file. Key dependencies include:

• VTK: For 3D visualization and rendering.
• Pandas: For data manipulation and analysis.
• NumPy: For numerical operations.
• SciPy: For spatial data processing with cKDTree.
• tqdm: For progress bars.
• joblib: For parallel computation.

Install all required dependencies:

conda env create -f environment.yml
conda activate seismic_vis_env

1.3 Usage

Run the desired script. If there are any unclear areas, please refer to the comments regarding the main function in each script. For example:

Example 1: 3D Earthquake Catalog Scatter Plot

python ./src/catalog_scatter_vis.py 3D ./rawData/CENC_catalog_1970-2020.csv

This command inputs an earthquake catalog CSV file and outputs a PNG result and a VTK file for further visualization.

Example 2: M-T Heat Map

python ./src/MT_hotmap_vis.py ./rawData/CENC_catalog_1970-2020.csv

This command also inputs an earthquake catalog CSV file, generating a PNG result and a VTK file.

Citation

If this work is useful to you, please cite the following source: He Pei et al., "Seismic Activity Characteristics in Sichuan-Yunnan Region Revealed by Big Data Analysis." This work is currently under review, and specific publication details will be provided upon acceptance.

License

This project is licensed under the MIT License. See the MIT License file for details.

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