Computing Aboveground Carbon Stocks Using Ground-Based and Sentinel Imagery Approach

Trees serve as natural carbon sinks and are crucial in sequestering carbon in biomass and soil. This study aimed to compute aboveground carbon stocks and species diversity and established correlations between the Normalized Difference Vegetation Index (NDVI) and carbon content for trees, poles, and regeneration species. Additionally, it sought to identify correlations between NDVI and biodiversity indices. Three community forests (CFs) located in the Mahottari district of Nepal, namely Bahunijhora, Kalikhola, and Markaurra, were selected to conduct this research. Systematic random sampling was adopted, resulting in 90 plots distributed across the three community forests, with 30 plots allocated to each. Rectangular plots of 20 × 25 m2 were set up for measuring tree dimensions. In contrast, 10 × 10 m2 plots were assigned for poles, and 5 × 5 m2 plots were utilized for assessing other regeneration species. The results indicated that the highest species diversity was observed in the Markaurra community forest, with a value of 0.5. At the same time, the lowest was recorded in the Bahunijhora forest, with a value of 0.14. Similarly, carbon stock was highest in Markaurra Community Forest, totaling 137.83 tha−1, and lowest in Bahunijhora Community Forest, with a measurement of 96.21 tha−1. Moreover, evenness and species richness were highest in Markaurra, with values of 0.71 and 10.19, respectively, and lowest in Bahunijhora Community Forest, with values of 0.57 and 7.06, respectively. Furthermore, NDVI values were calculated for each plot, revealing a linear pattern where increasing carbon stock corresponded to higher NDVI values and vice versa. This model can simplify aboveground biomass (AGB) calculations and carbon stock estimations.