Above-ground Carbon Storage Estimation of a Reforestation Site at Mae Moh Mine, Lampang Province, Using Sentinel-2 Satellite Data

Main Article Content

Weeraphart Khunrattanasiri
Alongkorn Amarakul
Laddawan Rianthakool
Thitinan Hutayanon

Abstract

This research aimed to determine the relationship between above-ground carbon sequestration and vegetation index derived from Sentinel-2 satellite data to estimate the above-ground carbon sequestration of a reforestation site at Mae Moh mine in the Lampang province. Twenty five permanent plots of size 40 m × 40 m were selected and tree data, including diameter at breast height (DBH) and total height (H), were collected. An allometric equation was developed to determine the relationship between the above-ground carbon sequestration and vegetation index through linear regression. The results showed that the above-ground carbon sequestration estimated through RVI (ratio vegetation index) was sufficiently accurate. The model was of the form y = - 65.57 + 57.57x (R2 = 0.75), with an RMSE of 11.14 tons of carbon dioxide equivalent per hectare. The average estimated above-ground carbon sequestration was 41.56 tons of carbon per hectare, while the total above-ground carbon sequestered at the reforestation site was 81,843.28 tons of carbon. The average carbon dioxide adsorption was 152.53 tons of carbon dioxide equivalent per hectare, while the total carbon dioxide adsorbed by the reforestation site being 300,374.28 tons of carbon dioxide equivalent.

Article Details

How to Cite
Khunrattanasiri, W., Amarakul, A., Rianthakool, L., & Hutayanon, T. (2023). Above-ground Carbon Storage Estimation of a Reforestation Site at Mae Moh Mine, Lampang Province, Using Sentinel-2 Satellite Data . Thai Journal of Forestry, 42(2), 113–122. Retrieved from https://li01.tci-thaijo.org/index.php/tjf/article/view/259449
Section
Original Articles

References

Ali, A., Ullah, S., Bushra, S., Ahmad, N., Ali, A., Khan, M.A. 2018. Quantifying forest carbon stocks by integrating satellite images and forest inventory data. Austrian Journal of Forest Science, 135(2): 93-117.

Boonsang, S. 2011. Estimation of Above - ground Carbon Sequestration of Forest Area by Using Remote Sensing Techniques at Mae Tuen Wildlife Sanctuary, Tak Province. M.S. Thesis, Kasetsart University, Bangkok, Thailand. (in Thai)

Department of National Parks, Wildlife and Plant Conservation. 2014. Survey and Assessment of Carbon Sequestration in Forest Areas. The Agricultural Co-operative Federation of Thailand (ACFT), Bangkok, Thailand. (in Thai)

Electricity Generating Authority of Thailand. 2016. Measures to Prevent and Correct Environmental Impacts from Mining. https://mmmenv.egat.co.th/egatmmm/web/management.php, 27 February 2023. (in Thai)

European Space Agency. 2015. Sentinel-2 User Handbook. https://sentinels.copernicus.eu/web/sentinel/user-guides/document-library/-/asset_publisher/xlslt4309D5h/content/sentinel-2-user-handbook, 25 November 2021.

Herold, M., Carter, S., Avitabile, V., Espejo, A.B., Jonckheere, I., Lucas, R., McRoberts, R.E., Næsset, E., Nightingale, J., Petersen, R., Reiche, J., Romijn, E., Rosenqvist, A., Rozendaal, D.M.A., Seifert, F.M., Sanz, M.J., De Sy, V. 2019. The role and need for space-based forest biomass-related measurements in environmental management and policy. Surveys in Geophysics, 40: 757-778.

Intergovernmental Panel on Climate Change (IPCC). 2003. Good Practice Guidance for Land Use, Land-Use Change and Forestry. The Institute for Global Environmental Strategies (IGES), Hayama, Japan.

Katong, R. 2018. Comparative Study of Landsat 8 and Sentinel-2 Data for Above-ground Carbon Sequestration Estimation at Reforestation Site of Mae Moh Mine, Lampang Province. M.S. Thesis, Kasetsart University, Bangkok, Thailand. (in Thai)

Khunrattanasiri, W. 2020. Satellite Imagery for Forest Resource Survey. Kasetsart University, Bangkok, Thailand. (in Thai)

Nuanurai, N. 2005. Comparison of Leaf Area Index, Above-ground Biomass and Carbon Sequestration of Forest Ecosystems by Forest Inventory and Remote Sensing at Kaeng Krachan National Park, Thailand. M.S. Thesis, Chulalongkorn University, Bangkok, Thailand. (in Thai)

Office of Natural Resources and Environmental Policy and Planning. 2020. Thailand Third Biennial Update Report. Office of Natural Resources and Environmental Policy and Planning, Bangkok, Thailand. (in Thai)

Ogawa, H., Yoda, K., Ogino, K., Kira, T. 1965. Comparative ecological studies on three main types of forest vegetation in Thailand II Plant biomass. Nature and Life in Southeast Asia, 4: 49-80.

Puliti, S., Breidenbach, J., Schumacher, J., Hauglin, M., Klingenberg, T.F., Astrup, R. 2021. Above-ground biomass change estimation using national forest inventory data with Sentinel-2 and Landsat. Remote Sensing of Environment, 265: 112644. doi:10.1016/j.rse.2021.112644.

Revision of Mine Master Plan Committee. 2020. Review Mae Moh Mine Master Plan. Electricity Generating Authority of Thailand, Nonthaburi, Thailand. (in Thai)

Sibanda, M., Mutanga, O., Rouget, M. 2015. Examining the potential of Sentinel-2 MSI spectral resolution in quantifying above-ground biomass across different fertilizer treatments. ISPRS Journal of Photogrammetry and Remote Sensing, 110: 55-65. doi:10.1016/j.isprsjprs.2015.10.005.

TEAM Consulting Engineering and Management Public Co. Ltd. 2017. Environmental Health Impact Assessment: Project to Expand the Power Plant for Replacement Power Plants in Mae Moh Machine 4-7. TEAM Consulting Engineering and Management Public Co. Ltd., Bangkok, Thailand. (in Thai)

Thailand Greenhouse Gas Management Organization. 2016. Thailand Voluntary Emission Reduction Program Reference Manual: Forestry and Agriculture Sector. Thailand Greenhouse Gas Management Organization, Bangkok, Thailand. (in Thai)

Tomppo, E., Gschwantner, T., Lawrence, M., McRoberts, R.E. 2010. National Forest Inventories: Pathways for Common Reporting. Springer, Berlin, Germany.

Viriyabuncha, C. 2020. A Guide to Studying Carbon Stocks Source in Natural Forests. Department of National Park, Wildlife and Plant Conservation, Bangkok, Thailand. (in Thai)

Xue, J., Su, B. 2017. Significant remote sensing vegetation indices: A review of developments and applications. Journal of Sensors, 2017: 1353691. doi:10.1155/2017/1353691.