Foundational Development of Drone-Based AI for Early Weed Detection in Tropical Reforestation

Principal Investigator

Reforestation in tropical regions faces a major ecological and operational challenge: the rapid proliferation of aggressive weed species during the early growth stages of trees. These weeds often outcompete young seedlings for critical resources such as light, nutrients, and water, leading to high mortality rates and undermining the success of environmental restoration, carbon sequestration, and biodiversity initiatives. Current weed monitoring methods are manual, labor-intensive, and impractical for large-scale or remote reforestation projects. This project proposes to address this challenge by developing an AI-powered aerial monitoring system that uses drones to detect and map weed infestations in tropical reforestation zones. Year 1 will focus on establishing the technical foundation for this system, including sensor configuration, data collection protocols, dataset creation, and initial model development.

01 Nov 2025 - 08 Jan 2027

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