Integrating Deep Learning and Machine Learning Techniques for Maize Yield Monitoring with Earth Observation and Climate Data to Ensure Food Security in Dry Regions

Our project aims to improve maize production efficiency and mitigate the impacts of climate change. By combining advanced computing, artificial intelligence, and remote sensing techniques, we will analyze data on maize cultivation, climate patterns, and soil health. This collaboration between institutions in both countries seeks to enhance agricultural sustainability, increase food security, and contribute valuable insights to global efforts addressing climate challenges. The participating institutions stand to benefit from shared expertise, fostering innovation in agricultural practices, and establishing a foundation for ongoing collaboration in addressing shared environmental concerns.

Faculty Supervisor:

Chunhua Zhang

Student:

Partner:

Sol Plaatje University

Discipline:

Earth science

Sector:

Education

University:

Algoma University

Program: