Hazrat-Ali9/EuroSAT-Satellite-Image-Land-Use-Classification

🛰️ EuroSAT Satellite Image Land Use Classification 🌍📡

EuroSAT-Satellite-Image-Land-Use-Classification is a computer vision project that leverages Deep Learning and CNN architectures to classify satellite images into different land use and land cover categories. Built on the EuroSAT dataset (based on Sentinel-2 satellite imagery), this project showcases how AI can support environmental monitoring, agriculture, and urban planning through automated satellite image classification.

✨ Key Features

🌍 Land Use Classification: Classify satellite images into 10 categories (e.g., Residential, Industrial, Pasture, Forest, River, Sea/Lake, etc.)

🖼️ High-Resolution Satellite Data: Uses the EuroSAT dataset with 27,000+ labeled images

🧠 Deep CNN Models: Custom CNNs + pretrained architectures (ResNet, VGG16, DenseNet, EfficientNet)

🧹 Preprocessing: Normalization, resizing, and augmentation for improved accuracy

📊 Evaluation Metrics: Accuracy, Precision, Recall, F1-score, Confusion Matrix

📈 Visualization: Training curves, classification reports, Grad-CAM heatmaps for model interpretability

🌐 Deployment Ready: Flask/Streamlit-based web app for uploading satellite images and real-time classification

🧰 Tech Stack

Programming: Python 🐍

Deep Learning: TensorFlow / Keras or PyTorch

Libraries: NumPy, Pandas, OpenCV, Matplotlib, Seaborn, Scikit-learn

Deployment (Optional): Flask, Streamlit, FastAPI

📁 Project Structure
📁 dataset/ # EuroSAT dataset (RGB bands)
📁 preprocessing/ # Data cleaning & augmentation scripts
📁 models/ # Deep CNN & pretrained architectures
📁 notebooks/ # Jupyter notebooks for experiments
📁 results/ # Metrics, confusion matrix, Grad-CAM visualizations
📁 app/ # Web app for image upload & prediction

🚀 Getting Started
git clone https://github.com/yourusername/EuroSAT-Satellite-Image-Land-Use-Classification.git
cd EuroSAT-Satellite-Image-Land-Use-Classification
pip install -r requirements.txt
jupyter notebook

📌 Use Cases

🌱 Agriculture: Crop and farmland monitoring

🏙️ Urban Planning: Detect residential, industrial, and commercial land use

🌳 Environmental Monitoring: Forest cover and deforestation analysis

🌊 Water Resource Management: Identification of rivers, lakes, and sea regions

📡 Remote Sensing Research: Benchmark for applying AI to geospatial data

🤝 Contributing

Contributions are welcome! You can extend the project by adding new model architectures, improving accuracy, or integrating with geospatial applications.

📜 License

MIT License – Free to use for research, education, and open-source collaboration.

⭐ Support

If you find this project useful, please consider giving it a star ⭐ to support AI in remote sensing & Earth observation.