AI-powered climate and environment monitoring (Mozambique)
ο»Ώ# π Climate and Environment Monitoring Platform
An **AI-powered climate and environment monitoring system for Mozambique**, built using **Flask (Python)** with integrated satellite data, NDVI vegetation analysis, air quality tracking, and flood risk detection.
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## βοΈ Run the Web App Locally
Follow these steps to install and run the platform on your own computer.
### 1οΈβ£ Clone this repository
```bash
git clone
github.com
cd climate_monitoring
python -m venv .venv
.\.venv\Scripts\Activate.ps1
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
python run.py
Then open your browser and go to:
π
127.0.0.1
Youβll see the live dashboard interface with:
π± Vegetation (NDVI) charts
π«οΈ Air quality forecast (Open-Meteo)
π Flood and cyclone monitoring
π§ Health indicators visualization
climate_monitoring/
β
βββ app/
β βββ templates/ # Frontend HTML pages
β βββ static/ # CSS, JS, images, plots
β βββ routes_environment.py # Environment page logic
β βββ routes_satellite.py # NDVI & satellite features
β βββ database.py # SQLite data access
β
βββ run.py # Flask app entry point
βββ requirements.txt # Python dependencies
βββ .gitignore # Ignored files (env, data, etc.)
Notes
You donβt need API keys to test most pages.
If you want to use Google Earth Engine features, run earthengine authenticate first and add your credentials (not required for local demo).
Database (data/climate_app.db) is included or auto-created if missing.
Author
Sheyd ChaΓΊque
Bachelor Thesis β AI-powered Climate and Environmental Monitoring (Mozambique)
Technologies: Python, Flask, TensorFlow, Google Earth Engine, Plotly.