Integrating High-Resolution UAV Data and Machine Learning for Monitoring and Analyzing Soil Erosion in an Agricultural Landscapes

This project aims to improve the monitoring and management of soil erosion in agricultural landscapes using advanced technologies like combinations of optical and LiDAR data from remotely piloted aircraft with machine learning. By creating detailed, high-resolution models of soil erosion and deposition, the project will help quantify erosion processes more efficiently than traditional methods. The expected benefits to participating institutions include enhancing their research capabilities through collaboration, providing valuable data for conservation efforts, and helping them develop more effective strategies for soil and water management. This approach will improve the precision of erosion assessments based on remote sensing data, assist in identifying critical areas for intervention, and contribute to more sustainable land management practices

Faculty Supervisor:

Derek Robinson

Student:

Partner:

Lviv Polytechnic National University

Discipline:

Earth science

Sector:

Environmental Science and Technology; Sustainability & the Environment; Agriculture and Food

University:

University of Waterloo

Program: