🔥 Wildfire Spread Analysis Dashboard

An interactive wildfire simulation dashboard built using Plotly Dash and Dash Bootstrap Components. This web-based app enables users to simulate and visualize wildfire spread dynamics over a 10x10 grid-based terrain with customizable cell properties, fire behavior controls, and real-time animation.

This dashboard is live on: https://wildfire-spread-analysis.onrender.com/

🚀 Features

• 🌲 Interactive Terrain Configuration
  Customize each grid cell with terrain type, wind direction, moisture levels, and ignition state.

• 🔄 Fire Spread Simulation
  Animated step-by-step simulation showing how fire spreads based on wind, terrain, and moisture.

• 🧠 Smart Control Panel
  Selecting a cell auto-fills the control panel for real-time property editing.

• 🌗 Light/Dark Theme Toggle
  Switch between light and dark mode for comfortable viewing.

• ⏱️ Adjustable Animation Speed
  Control the pace of the fire spread simulation.

• ✅ Responsive UI
  Optimized layout for desktop and tablets using Bootstrap.

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📸 Screenshots

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🧩 Tech Stack

Tool	Purpose
Dash	Frontend framework
Plotly	Grid visualization
Flask	Backend server
Dash Bootstrap Components	UI Styling
Pandas	Grid and state management

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⚙️ Installation

📌 Python 3.8–3.11 recommended. Python 3.13 is not fully supported by all packages.

🐍 1. Clone and create virtual environment

git clone https://github.com/Intell-Alpha/wildfire-spread-analysis.git
cd wildfire-spread-analysis

python -m venv venv
source venv/bin/activate    # On Windows: venv\Scripts\activate

📦 2. Install dependencies

pip install -r requirements.txt

▶️ Running the App Locally

python wildfireTerrainAnimationSteps.py

The app will be available at http://127.0.0.1:8050.

🌐 Deployment (Render / Gunicorn)

1. Make sure the following line exists in wildfireTerrainAnimationSteps.py:

server = app.server

2. Use this Render start command:

gunicorn wildfireTerrainAnimationSteps:server

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🧪 Testing Tips

1. Click a cell to populate control panel fields (wind, terrain, moisture, direction).
2. Modify properties and click Update Cell or Toggle Fire to observe changes.
3. Start simulation and adjust steps to verify spread behavior.
4. Switch themes and confirm immediate style updates.

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✨ Future Work

• 🔍 Heatmap Intensity: Show fire intensity gradient.
• ⛰️ Elevation Modeling: Incorporate terrain elevation.
• 📈 Data Export: Export simulation frames or CSV logs.
• 🧠 ML Prediction: Integrate machine-learning models for predictive spread analysis.

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🤝 Contributing

1. Fork the repository.
2. Create your feature branch: git checkout -b feature/YourFeature
3. Commit your changes: git commit -m 'Add some feature'
4. Push to the branch: git push origin feature/YourFeature
5. Open a Pull Request.

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📄 License

This project is licensed under the MIT License.

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🙌 Acknowledgments

• Built with Dash & Plotly
• UI styled via Dash Bootstrap Components
• Inspiration from real-world wildfire modeling research

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Contributors

1. Kaushal Sambanna
2. Devansh Makam