Articles | Volume 22, issue 16
https://doi.org/10.5194/bg-22-4291-2025
https://doi.org/10.5194/bg-22-4291-2025
Research article
 | 
28 Aug 2025
Research article |  | 28 Aug 2025

Assessing the effect of forest management on above-ground carbon stock by remote sensing

Sofie Van Winckel, Jonas Simons, Stef Lhermitte, and Bart Muys

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Cited articles

Askar, Nuthammachot, N., Phairuang, W., Wicaksono, P., and Sayektiningsih, T.: Estimating Aboveground Biomass on Private Forest Using Sentinel-2 Imagery, J. Sensors, 6745629, 2018, https://doi.org/10.1155/2018/6745629, 2018. 
Belgium: National Inventory Report (NIR), United Nations Framework Convention on Climate Change, https://unfccc.int/documents/224891 (last access: 20 November 2023), 2020. 
Berben, J.: Dendrometrische studie van de Corsikaanse den, LISEC, Genk, 1983. 
Bolar, K.: STAT: Interactive Document for Working with Basic Statistical Analysis, R package version 0.1.0, CRAN [code], https://CRAN.R-project.org/package=STAT (last access: 10 December 2024), 2019. 
Brabantse Wouden: https://www.vlaamsbrabant.be/nl/natuur-en-milieu/brabantse-wouden, last access: 23 October 2023. 
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Short summary
Insights on management's impact on forest carbon stocks are crucial for sustainable forest management practices. However, accurately monitoring carbon stocks remains a technological challenge. This study estimates above-ground carbon stock in managed and unmanaged forests using passive optical, synthetic aperture radar (SAR), and light detection and ranging (lidar) remote sensing data. Results show promising potential in using multiple remote sensing predictors and publicly available high-resolution data for mapping forest carbon stocks.
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