Integrating Drone Imagery, advanced AI, and Remote Sensing for Assessing Success Rate of Natural and Artificial Forest Regeneration in Post-Wildfire Landscapes

This research project aims to address the existing knowledge gap regarding the effectiveness of drone-based reforestation compared to natural forest regeneration in post-wildfire areas. This study seeks to provide valuable insights into its benefits, limitations, and potential for large-scale reforestation efforts. The research outcomes will contribute to the scientific understanding of drone-based reforestation, guide reforestation strategies, and inform decision-making by stakeholders. Collaborating on this research project will provide substantial benefits to the TreeTrack. Firstly, their involvement will allow them to improve their existing drone tree planting methods through a comprehensive scientific evaluation. The research findings will enable the TreeTrack to fine-tune their operations, identify areas for optimization, and enhance the overall efficiency of their reforestation efforts. Additionally, being associated with a rigorous scientific study will enhance the TreeTrack’s reputation as a leader in the field and provide them with a competitive edge in the emerging market of drone-based reforestation.

Faculty Supervisor:

Siamak Arzanpour

Student:

Partner:

Tree Track Intelligence

Discipline:

Earth science

Sector:

Agriculture

University:

Simon Fraser University

Program: