Earthquake Analysis Dashboard and Predictive Modeling

Overview

This project provides a comprehensive analysis of global earthquake data from 1995 to 2023 using interactive visualizations and predictive modeling. The project is divided into two main components:

1. Earthquake Dashboard: A web-based interactive dashboard built with Dash and Plotly to visualize global earthquake distributions, identify high-risk zones, and analyze correlations between seismic parameters.
2. Predictive Modeling: Python-based scripts for exploratory data analysis (EDA), visualization, and machine learning to predict seismic impact metrics like CDI and MMI.

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Features

Earthquake Dashboard

• Global Map Visualization: Interactive map showcasing global earthquake distributions with magnitudes, depths, and risk zones.
• High-Risk Zones: Highlighting zones prone to both high seismicity and tsunamis.
• Correlation Analysis: Heatmap visualization of correlations among seismic attributes like magnitude, depth, and intensity (SIG).

Predictive Modeling

• Exploratory Data Analysis (EDA) using Pandas, Matplotlib, and Seaborn.
• Geospatial visualization using GeoPandas and Cartopy.
• Predictive models for seismic impact metrics (CDI and MMI) using RandomForestRegressor with hyperparameter tuning via GridSearchCV.

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Installation

Prerequisites

• Python 3.8 or higher
• Required libraries:
  • pandas
  • dash
  • dash-bootstrap-components
  • plotly
  • matplotlib
  • seaborn
  • geopandas
  • cartopy
  • scikit-learn

Usage Running the Dashboard -python dashboard.py Running the Predictive Model -python main.ipynb