This repository hosts the Land Type Classification using Sentinel-2 Satellite Images project, which focuses on developing a powerful deep learning model to classify different land types using multispectral satellite imagery. By harnessing the capabilities of Sentinel-2 data and Deep Neural Networks (DNNs), the project aims to contribute to crucial fields such as:
- Urban Planning 🏙️
- Agriculture 🌾
- Environmental Conservation 🌳
- Multispectral Data Analysis: Utilizing Sentinel-2 satellite imagery for precise land classification.
- Deep Learning: Implementing robust DNN architectures to achieve high classification accuracy.
- Real-World Applications: Supporting informed decision-making in sustainable development, resource management, and environmental monitoring.
The project is structured into clear phases to ensure thorough data processing, model training, evaluation, and deployment. Key milestones include:
- Data Collection and Preprocessing
- Model Development and Optimization
- Deployment and Usability Testing
This project sets the foundation for continuous improvement and scalability, offering valuable insights for future research and applications.
Alpha 5 will build innovative solutions for a sustainable future. 🌟
- Aly El-Deen Yasser Ali (Known By Aly El-Badry) -- Linkedin
- Mohammed Walid (Known by Mohammed Gafour) -- Linkedin
- Amr Yasser -- Linkedin
- Dina Zahran -- Linkedin
- Sherin Mohamed -- Linkedin
This project is licensed under the MIT License.