Articles | Volume 13, issue 11 
            
                
                    
            
            
            https://doi.org/10.5194/essd-13-5353-2021
                    © Author(s) 2021. This work is distributed under 
the Creative Commons Attribution 4.0 License.
                the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-13-5353-2021
                    © Author(s) 2021. This work is distributed under 
the Creative Commons Attribution 4.0 License.
                the Creative Commons Attribution 4.0 License.
Refined burned-area mapping protocol using Sentinel-2 data increases estimate of 2019 Indonesian burning
David L. A. Gaveau
CORRESPONDING AUTHOR
                                            
                                    
                                            TheTreeMap, Bagadou Bas, 46600 Martel, France
                                        
                                    Adrià Descals
                                            CREAF, Centre de Recerca Ecològica i Aplicacions Forestals,
E08193 Bellaterra (Cerdanyola de Vallès), Catalonia, Spain
                                        
                                    Mohammad A. Salim
                                            TheTreeMap, Bagadou Bas, 46600 Martel, France
                                        
                                    Douglas Sheil
                                            Forest Ecology and Forest Management Group, Wageningen University and Research, P.O. Box 47, 6700 AA, Wageningen, the Netherlands
                                        
                                    Sean Sloan
                                            Department of Geography, Vancouver Island University, Nanaimo, BC,
Canada
                                        
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- Reconstructing 34 Years of Fire History in the Wet, Subtropical Vegetation of Hong Kong Using Landsat A. Chan et al. 10.3390/rs15061489
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- Burned-Area Mapping Using Post-Fire PlanetScope Images and a Convolutional Neural Network B. Kim et al. 10.3390/rs16142629
- Mapping forest fire severity using bi-temporal unmixing of Sentinel-2 data - Towards a quantitative understanding of fire impacts K. Pfoch et al. 10.1016/j.srs.2023.100097
- Global mapping of oil palm planting year from 1990 to 2021 A. Descals et al. 10.5194/essd-16-5111-2024
- Agriculture, Development and Sustainability in the Covid-19 Era A. Halimatussadiah et al. 10.1080/00074918.2022.2056935
- Monitoring active fires in Borneo from Sentinel-2 MSI images X. Guo et al. 10.1080/15481603.2025.2539551
- Assessing Burned Area Detection in Indonesia Using the Stacking Ensemble Neural Network (SENN): A Comparative Analysis of C- and L-Band Performance D. Sudiana et al. 10.3390/computers14080337
- Mono-temporal and multi-temporal approaches for burnt area detection using Sentinel-2 satellite imagery (a case study of Rokan Hilir Regency, Indonesia) N. Afira & A. Wijayanto 10.1016/j.ecoinf.2022.101677
- Reimagine fire science for the anthropocene J. Shuman et al. 10.1093/pnasnexus/pgac115
- Gastrointestinal parasites of wild Bornean orang-utans (Pongo pygmaeus) in a habitat affected by wildfire smoke A. Gwynn et al. 10.1016/j.gecco.2024.e03214
- Unprecedented fire activity above the Arctic Circle linked to rising temperatures A. Descals et al. 10.1126/science.abn9768
- Catastrophic impact of extreme 2019 Indonesian peatland fires on urban air quality and health M. Grosvenor et al. 10.1038/s43247-024-01813-w
- In Search of Fire Villains V. Schreer 10.1215/22011919-11327404
- Enhanced CH4 emissions from global wildfires likely due to undetected small fires J. Zhao et al. 10.1038/s41467-025-56218-w
- A Hybrid Convolutional Neural Network and Random Forest for Burned Area Identification with Optical and Synthetic Aperture Radar (SAR) Data D. Sudiana et al. 10.3390/rs15030728
- Fire frequency, intensity, and burn severity in Kalimantan’s threatened Peatland areas over two Decades A. Schmidt et al. 10.3389/ffgc.2024.1221797
- A global behavioural model of human fire use and management: WHAM! v1.0 O. Perkins et al. 10.5194/gmd-17-3993-2024
- OtsuSeg: an R package implementing Otsu’s thresholding technique for mapping forest fire scars with integrated accuracy assessment H. Achour et al. 10.1007/s41324-025-00644-x
- Wetscapes: Restoring and maintaining peatland landscapes for sustainable futures R. Temmink et al. 10.1007/s13280-023-01875-8
- Monthly mapping of Indonesia’s burned areas: implementation, history, techniques, and future directions Y. Vetrita et al. 10.1080/01431161.2024.2421942
- Burned area semantic segmentation: A novel dataset and evaluation using convolutional networks T. Ribeiro et al. 10.1016/j.isprsjprs.2023.07.002
- Mechanistic Analysis and Numerical Simulation of the 2021 Post‐Fire Debris Flow in Xiangjiao Catchment, China C. Ouyang et al. 10.1029/2022JF006846
- Sentinel-2 sampling design and reference fire perimeters to assess accuracy of Burned Area products over Sub-Saharan Africa for the year 2019 D. Stroppiana et al. 10.1016/j.isprsjprs.2022.07.015
- A comprehensive assessment of the FireCCILT11 global burned area product D. Chen & L. Giglio 10.1016/j.jag.2025.104893
- Fire Impacts, vegetation Recovery, and environmental drivers in West African savannas (2014–2023): A High-Resolution remote sensing assessment B. Ouattara et al. 10.1016/j.jag.2025.104783
- Enhancing Fire Monitoring Method over Peatlands and Non-Peatlands in Indonesia Using Visible Infrared Imaging Radiometer Suite Data A. Indradjad et al. 10.3390/fire7010009
- Influence of wildfires on the conflict (2006–2022) in eastern Ukraine using remote sensing techniques (MODIS and Sentinel-2 images) F. Rodriguez-Jimenez et al. 10.1016/j.rsase.2024.101240
- Multi-decadal trends and variability in burned area from the fifth version of the Global Fire Emissions Database (GFED5) Y. Chen et al. 10.5194/essd-15-5227-2023
- Assessing space-based smoldering peatland in the tropics with atmospheric products from multi-sensor satellites P. Sofan et al. 10.1007/s40808-023-01793-4
- FIREMAP: Cloud-based software to automate the estimation of wildfire-induced ecological impacts and recovery processes using remote sensing techniques J. Fernández-Guisuraga et al. 10.1016/j.ecoinf.2024.102591
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- Assessing Burned Areas in Sikkim, India through Satellite Mapping K. SHARMA et al. 10.17475/kastorman.1394888
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1 citations as recorded by crossref.
Latest update: 31 Oct 2025
Short summary
                    Severe burning struck Indonesia in 2019. Drawing on new satellite imagery, we present and validate new 2019 burned-area estimates for Indonesia. 
We show that > 3.11 million hectares (Mha) burned in 2019, double the official estimate from the Indonesian Ministry of Environment and Forestry. Our relatively more accurate estimates have important implications for carbon-emission calculations from forest and peatland fires in Indonesia.
                    Severe burning struck Indonesia in 2019. Drawing on new satellite imagery, we present and...
                    
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