Project
Remote sensing of carbon stocks in tropical offset plantations using high-resolution RGB imageryForest reforestation is a promising nature-based solution to climate change, especially in tropical regions where high tree productivity and fewer disturbances like fires help preserve carbon stocks. However, monitoring these projects is often difficult due to high costs and challenging and time-consuming fieldwork. To address this, we propose using RGB (red-green-blue) drone-based imagery to improve carbon monitoring in tropical plantations. Our AI-enhanced algorithms will enable us to segment tree crowns, estimate above-ground biomass and identify species. LiDAR data will be collected at the Agua Salud plantation site in Panama and will be used to validate and train our canopy height, crown density and taxonomic identification models, helping to improve biomass and carbon estimates. This technology could drastically reduce the need for field measurements, automating the process and enabling non-experts to collect essential data quickly and efficiently. Using consumer drones equipped with RGB cameras, this method will democratize access to advanced carbon monitoring technology, empowering local and indigenous communities to participate in the voluntary carbon market. By giving them the tools to control plantation monitoring, our approach promotes equity and sustainability in carbon offset projects. We have already established a partnership with the Smithsonian Tropical Research Institute for our fieldwork and started collecting data.
