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A Novel Method for Estimating Biomass and Carbon Sequestration in Tropical Rainforest Areas Based on Remote Sensing Imagery: A Case Study in the Kon Ha Nung Plateau, Vietnam

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  • Hoi Nguyen Dang

    (Institute of Tropical Ecology, Joint Vietnam–Russia Tropical Science and Technology Research Center, № 63, Nguyen Van Huyen Str., Cau Giay District, Hanoi 122102, Vietnam)

  • Duy Dinh Ba

    (Institute of Tropical Ecology, Joint Vietnam–Russia Tropical Science and Technology Research Center, № 63, Nguyen Van Huyen Str., Cau Giay District, Hanoi 122102, Vietnam)

  • Dung Ngo Trung

    (Institute of Tropical Ecology, Joint Vietnam–Russia Tropical Science and Technology Research Center, № 63, Nguyen Van Huyen Str., Cau Giay District, Hanoi 122102, Vietnam)

  • Hieu Nguyen Huu Viet

    (Forest Inventory and Planning Institute (FIPI), Vinh Quynh Commune, Thanh Tri District, Hanoi 134500, Vietnam)

Abstract

Forest ecosystems play a key role in sustaining life on this planet, given their functions in carbon storage, oxygen production, and the water cycle. To date, calculations of the biomass and carbon absorption capacity of forest ecosystems—especially tropical rainforests—have been quite limited, especially in Vietnam. By applying remote sensing materials, geographic information systems (GIS) facilitate the synchronized estimation of both biomass and ability of forest ecosystems to absorb carbon over large spatial ranges. In this study, we calculated the biomass of tropical rainforest vegetation in the Kon Ha Nung Plateau, Vietnam, according to four regression models based on Sentinel-2 satellite image data, forest reserve maps, and forest survey standard cell data (including 19 standard cells for 2016 and 44 standard cells for 2021). The results of the data comparison for the four biomass computing models (log-log, log-lin, lin-log, and lin-lin) demonstrated that the models with the highest accuracy were the lin-log model for 2016 (with a correlation coefficient of R 2 = 0.76) and the lin-log model for 2021 (with a correlation coefficient of R 2 = 0.765). Based on the analytical results and the selection of biomass estimation models, biomass maps were developed for the Kon Ha Nung Plateau area, Vietnam, in 2016 and 2021, with a predominant biomass value of 80–180 tons/ha (Mg/ha); furthermore, biomass fluctuations were analyzed for the period 2016–2021. Accordingly, the ability to absorb carbon and CO 2 equivalents in this research area for 2016 and 2021 was calculated based on the estimated biomass values. In summary, we present a method for estimating biomass via four basic linear regression models for tropical rainforest areas based on satellite image data. This method can serve as a basis for managers to calculate and synchronize the payment of carbon services, which contributes to promoting the livelihoods of local people.

Suggested Citation

  • Hoi Nguyen Dang & Duy Dinh Ba & Dung Ngo Trung & Hieu Nguyen Huu Viet, 2022. "A Novel Method for Estimating Biomass and Carbon Sequestration in Tropical Rainforest Areas Based on Remote Sensing Imagery: A Case Study in the Kon Ha Nung Plateau, Vietnam," Sustainability, MDPI, vol. 14(24), pages 1-20, December.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:24:p:16857-:d:1004620
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    References listed on IDEAS

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    1. Chaofan Wu & Huanhuan Shen & Ke Wang & Aihua Shen & Jinsong Deng & Muye Gan, 2016. "Landsat Imagery-Based Above Ground Biomass Estimation and Change Investigation Related to Human Activities," Sustainability, MDPI, vol. 8(2), pages 1-13, February.
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    Cited by:

    1. Yi Le & Sheng-Yang Huang, 2023. "Prediction of Urban Trees Planting Base on Guided Cellular Automata to Enhance the Connection of Green Infrastructure," Land, MDPI, vol. 12(8), pages 1-18, July.

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