Estimation of Peatland Fire Carbon Emissions Using Remote Sensing and GIS

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Research Paper 01/06/2022
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Estimation of Peatland Fire Carbon Emissions Using Remote Sensing and GIS

Ichsan Ridwan, Nurlina, Widya Edma Putri
Int. J. Biosci. 20(6), 246-253, June 2022.
Copyright Statement: Copyright 2022; The Author(s).
License: CC BY-NC 4.0

Abstract

Global warming occurs due to too many greenhouse gases in the atmosphere, especially carbon dioxide (CO2). One of the causes of the increasing amount of CO2 gas is forest and peatland fires. Peatlands are known to store carbon stocks not only above the ground surface but also below the ground surface which if there is a fire it will turn into carbon emissions. The forest and peatland fires in 2015 were one of the worst fire events in Indonesia (Sumatra and Kalimantan) in recent years. Therefore, many researchers have tried to estimate carbon emissions resulting from fires in several areas. This study estimates the number of carbon emissions (above surface and subsurface carbon emissions) from peatland fires in Banjar Regency in 2015 using remote sensing technology (Landsat 8), imagery data and Geographic Information Systems (GIS). Based on two types of vegetation, namely shrubs and agricultural land (the results of land cover classification), that occupy burned peatlands, the resulting carbon emissions above the surface of 1,718.55 tons. Meanwhile, the amount of subsurface carbon emissions (based on the category of depth and peat maturity) is 1,092.14 tons. So the total carbon emissions resulting from peatland fires in Banjar Regency in 2015 were 2,810.69 tons. Overall, our findings indicate that peat fires in the Banjar district produce significantly higher carbon emissions than currently reported in emission inventories, which has consequences for the predicted impacts of peat burning on air quality.

Akbar A, Faidil S. 2014. Forest and Peat Swamp Fires: Causes of Supporting Factors and Alternative Management. Forestry Research Institute. Banjarbaru.

Agus F, Subiksa IMG. 2008. Peatlands: Potential for Agriculture and Environmental Aspects. Soil Research Institute and World Agroforestry Center (ICRAF). Bogor.

Bourgeau-Chavez LL, Grelik SL, Billmire M, Michael, Jenkins LK, Kasischke ES, Turetsky MR. 2020. Assessing Boreal Peat Fire Severity and Vulnerability of Peatlands to Early Season Wildland Fire. Frontiers in Forests and Global Change 3 (February), p 1–13. http://dx.doi.org/10.3389/ffgc.2020.00020

Banjar District Government. 2014. Banjar Regency in Figures. Central Bureau of Statistics Banjar Regency. Banjar.

Couwenberg J, Dommain R, Joosten H. 2010. Greenhouse Gas Fluxes from Tropical Peatswamps in Southeast Asia. Global Change Biology 16(6), 1715-1731.

Chemical Laboratory Staff. 1998. A Guide to Soil and Plant Chemical Analysis. Center for Soil and Agroclimate Research. Bogor.

Che Azmi NA, Apandi MN, Ahmad AS. 2021. Carbon emissions from the peat fire problem—a review. Environmental Science and Pollution Research 28(14), p 16948–16961. http://dx.doi.org/10.1007/s11356-021-12886-x.

Dewanti R. 1999. Condition of Mangrove Forests in East Kalimantan, Sumatra, Java, Bali, and Maluku. LAPAN Magazine Remote Sensing Edition. Jakarta.

French NHF, Goovaerts P, Kasischke ES. 2004. Uncertainty in Estimating Carbon Emissions from Boreal Forest Fires. Journal of Geophysical Research Atmospheres 109, p 14-8. http://dx.doi.org/10.1029/2003JD003635

Hooijer A, Page S, Cadadell JG, Silvius M, Kwadijk J, Wostendan H, Hayasaka J. 2014. Peat-fire-related air pollution in Central Kalimantan, Indonesia. Environmental Pollution 195, p 257–266. http://dx.doi.org/10.1016/j.envpol.2014.06.031.

Jauhiainen. 2010. Current and Future CO2 Emissions from Drained Peatlands in Southeast Asia. Biogeosciences 7, 1505-1514.

Key CH, Benson NC. 2005. Landscape assessment: Ground Measure of Severity, the Composite Burn Index and Remote Sensing of Severity, The Normalized Burn Ratio in FIREMON: Fire Effects Monitoring and Inventory System. U. S. Dept. of Agricultural, Utah.

Lestari P, Muthmainnah F, Permadi DA. 2020. Characterization of carbonaceous compounds emitted from Indonesian surface and sub surface peat burning. Atmospheric Pollution Research 11(9), p 1465–1472. http://dx.doi.org/10.1016/j.apr.2020.06.001.

Lillesand TM, Kiefer RW. 1979. Remote Sensing and Image Interpretation. John Wiley and Sons, New York.

Luta W, Ahmed OH, Heng RKJ, Choo LKN. 2017. Water table fluctuation and carbon dioxide emission from a tropical peat soil cultivated with pineapples (Ananas comosus L . Merr). 6655, p 172–178.

Nurlina, Kadir S, Kurnain A, Ilham W. 2021. Comparison of Maximum Likelihood and Support Vector Machine Classifiers For Land Use/Land Cover Mapping Using Multitemporal Imagery. 12 (June), 12(1), p 126-139.  ARInt.2021 (12.1-12).pdf. http://www.savap.org.pk/journals/ARInt./

Nurlina, Ridwan I, Putri WE. 2018. Analisis Kebakaran Lahan Gambut Menggunakan Citra Satelit Multitemporal. In Banjarbaru: Lembaga Penelitian dan Pengabdian kepada Masyarakat, Universitas Lambung Mangkurat, p 352–355. Available at: http://snllb.ulm.ac.id/prosiding/index.php/snllb-lit/article/viewFile/78/76.

Poulter B, Christensen NL, Halpin PN. 2006. Carbon emissions from a temperate peat fire and its relevance to interannual variability of trace atmospheric greenhouse gases. Journal of Geophysical Research Atmospheres 111(6). http://dx.doi.org/10.1029/2005JD006455.

Purbowaseso B. 1995. Applied Remote Sensing. The publisher the University of Indonesia. Jakarta.

Rimal B, Rijal S, Kunwar R. 2020. Comparing Support Vector Machines and Maximum Likelihood Classifiers for Mapping of Urbanization. Journal of the Indian Society of Remote Sensing 48(1), p .71–79. http://dx.doi.org/10.1007/s12524-019-01056-9.

Soil Survey Staff. 1998. Keys to Soil Taxonomy. United States Department of Agriculture (USDA). National Resources Conservation Services.

Smith AMS, Crystal AK, Wade TT, Alan FT, John DM, Andrew TH, Luigi B, Michael JF, Jonathan AG, John WA, Andrew K, Lilian A, Robert FK, James RG. 2014. Remote sensing the vulnerability of vegetation in natural terrestrial ecosystems. Remote Sensing of Environment 154, p 322-337, ISSN 0034-4257. https://doi.org/10.1016/j.rse.2014.03.038.

USGS. 2013. Landsat 8. (Accessed February 10, 2017). http://landsat.usgs.gov/landsat8php

Wahyunto S, Ritung, Subagjo H. 2004. Map of Peatland Distribution, Area and Carbon Content in Kalimantan / Map of Peatland Distribution Area and Carbon Content in Kalimantan, 2000 – 2002. 1st Edition. Wetlands International – Indonesia Program and Wildlife Habitat Canada (WHC). Bogor.

Wilbur RB, Christensen NL. 1983. Effects of Fire on Nutrient Availability in a North Carolina Coastal-Plain Pocosin. The American Midland Naturalist. 110, 54-61.

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