38 citations as recorded by crossref.

1. 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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3. Comparison of convolutional neural network and support vector machine for identification of forest types and burned areas B. Li et al. 10.1117/1.JRS.18.014531
4. Burned-Area Mapping Using Post-Fire PlanetScope Images and a Convolutional Neural Network B. Kim et al. 10.3390/rs16142629
5. Mechanistic Analysis and Numerical Simulation of the 2021 Post‐Fire Debris Flow in Xiangjiao Catchment, China C. Ouyang et al. 10.1029/2022JF006846
6. 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
7. 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
8. Global mapping of oil palm planting year from 1990 to 2021 A. Descals et al. 10.5194/essd-16-5111-2024
9. Agriculture, Development and Sustainability in the Covid-19 Era A. Halimatussadiah et al. 10.1080/00074918.2022.2056935
10. 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
11. 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
12. 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
13. 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
14. Reimagine fire science for the anthropocene J. Shuman et al. 10.1093/pnasnexus/pgac115
15. 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
16. 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
17. 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
18. Unprecedented fire activity above the Arctic Circle linked to rising temperatures A. Descals et al. 10.1126/science.abn9768
19. Catastrophic impact of extreme 2019 Indonesian peatland fires on urban air quality and health M. Grosvenor et al. 10.1038/s43247-024-01813-w
20. Forty-Year Fire History Reconstruction from Landsat Data in Mediterranean Ecosystems of Algeria following International Standards M. Kouachi et al. 10.3390/rs16132500
21. Slowing deforestation in Indonesia follows declining oil palm expansion and lower oil prices D. Gaveau et al. 10.1371/journal.pone.0266178
22. An automatic procedure for mapping burned areas globally using Sentinel-2 and VIIRS/MODIS active fires in Google Earth Engine A. Bastarrika et al. 10.1016/j.isprsjprs.2024.08.019
23. The Global Forest Fire Emissions Prediction System version 1.0 K. Anderson et al. 10.5194/gmd-17-7713-2024
24. Building a small fire database for Sub-Saharan Africa from Sentinel-2 high-resolution images E. Chuvieco et al. 10.1016/j.scitotenv.2022.157139
25. Burned area detection using convolutional neural network based on spatial information of synthetic aperture radar data in Indonesia A. Lestari et al. 10.24057/2071-9388-2024-3109
26. Mapping sugarcane residue burnt areas in smallholder farming systems using machine learning approaches K. PNVR & V. Bandaru 10.1016/j.atech.2023.100347
27. 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
28. Fire frequency, intensity, and burn severity in Kalimantan’s threatened Peatland areas over two Decades A. Schmidt et al. 10.3389/ffgc.2024.1221797
29. A global behavioural model of human fire use and management: WHAM! v1.0 O. Perkins et al. 10.5194/gmd-17-3993-2024
30. Wetscapes: Restoring and maintaining peatland landscapes for sustainable futures R. Temmink et al. 10.1007/s13280-023-01875-8
31. Identifying long-term burned forests in the rugged terrain of Southwest China:A novel method based on remote sensing and ecological mechanisms E. Yu et al. 10.1016/j.jag.2024.104134
32. Single-Temporal Sentinel-2 for Analyzing Burned Area Detection Methods: A Study of 14 Cases in Republic of Korea Considering Land Cover D. Lee et al. 10.3390/rs16050884
33. Global biomass burning fuel consumption and emissions at 500 m spatial resolution based on the Global Fire Emissions Database (GFED) D. van Wees et al. 10.5194/gmd-15-8411-2022
34. A Novel Spectral Index for Vegetation Destruction Event Detection Based on Multispectral Remote Sensing Imagery C. Zhao et al. 10.1109/JSTARS.2024.3412737
35. Assessing Burned Areas in Sikkim, India through Satellite Mapping K. SHARMA et al. 10.17475/kastorman.1394888
36. Madagascar's burned area from Sentinel-2 imagery (2016–2022): Four times higher than from lower resolution sensors V. Fernández-García et al. 10.1016/j.scitotenv.2024.169929
37. Road fragment edges enhance wildfire incidence and intensity, while suppressing global burned area S. Bowring et al. 10.1038/s41467-024-53460-6
38. Declining severe fire activity on managed lands in Equatorial Asia S. Sloan et al. 10.1038/s43247-022-00522-6