Undergraduate Research on Carbon Sequestration Forest at Chula, Saraburi, Wins National Academic Conference Award 

The Regional Learning Network Center, in collaboration with the Department of Biology, Faculty of Science, Chulalongkorn University, recently presented a research study comparing carbon sequestration using traditional methods (plotting and measuring trees in forest areas on the ground) with the use of Unmanned Aerial Vehicles (UAVs) in the carbon sequestration forest area at Chulalongkorn University, Saraburi. The study was showcased at the 1st National Conference on “Sustainable Development,” hosted by the Faculty of Environment and Resource Studies, Mahidol University, and was selected as one of the nine recipients of the Outstanding Paper Awards. 

The comparative study in Chulalongkorn University’s carbon sequestration forest area in Saraburi focused on two teak plantation plots of different planting ages. The first plot was planted with “Mahesak” and “Sak Siamin” teak varieties under the royal project titled “Ruamjai Phak Planting Mahesak-Sak Siamin in Tribute to His Majesty the King on the Occasion of His 84th Birthday,” launched on June 26, 2013. This plot contains 1,100 teak trees over 11 rai (about 4.3 acres). 

The second plot is an eco-friendly forest plantation (carbon credit forest) planted in 2022 by alumni from the 15th graduating class. It was later developed into a model for sustainable forest planting with improved seedling survival rates using bioplastics and superabsorbent polymers, in collaboration with the Thai Bioplastics Industry Association in 2023. This plot includes 1,220 teak trees over 15 rai (about 5.9 acres). 

The study found a statistically significant difference in carbon sequestration estimates between the two methods. The UAV method produced lower carbon estimates than the traditional method because the UAV technology currently lacks the ability to distinguish tree trunks accurately. Therefore, further development is needed—potentially integrating new tools such as ground-based LiDAR for improved accuracy. 

The data from this research can be applied to support forest management planning, replanting efforts, and the creation of high-resolution maps to monitor tree growth in Chulalongkorn University’s carbon credit learning forest in Saraburi, as well as in other university-led reforestation projects. 

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