173 citations as recorded by crossref.

1. The Collection 6 MODIS burned area mapping algorithm and product L. Giglio et al. 10.1016/j.rse.2018.08.005
2. Reduced global fire activity due to human demography slows global warming by enhanced land carbon uptake C. Wu et al. 10.1073/pnas.2101186119
3. Landsat-8 and Sentinel-2 based Forest fire burn area mapping using machine learning algorithms on GEE cloud platform over Uttarakhand, Western Himalaya S. Bar et al. 10.1016/j.rsase.2020.100324
4. Progress and challenges in remotely sensed terrestrial carbon fluxes T. Wang et al. 10.1080/10095020.2024.2336599
5. Estimation of Forest Fire Burned Area by Distinguishing Non-Photosynthetic and Photosynthetic Vegetation Using Triangular Space Method X. Wang et al. 10.3390/rs15123115
6. Theoretical uncertainties for global satellite-derived burned area estimates J. Brennan et al. 10.5194/bg-16-3147-2019
7. Spatiotemporal pattern of ENSO-induced modulation on landscape fires over Pacific Rim from 2001 to 2020 F. Li et al. 10.1016/j.accre.2024.11.001
8. Fires in the South American Chaco, from dry forests to wetlands: response to climate depends on land cover R. San Martín et al. 10.1186/s42408-023-00212-4
9. Spatiotemporal analysis of wildfires and their relationship with climate and land use in the Gran Chaco and Pantanal ecoregions C. Vidal-Riveros et al. 10.1016/j.scitotenv.2024.176823
10. Quantitative assessment of fire and vegetation properties in simulations with fire-enabled vegetation models from the Fire Model Intercomparison Project S. Hantson et al. 10.5194/gmd-13-3299-2020
11. A patch-based algorithm for global and daily burned area mapping M. Campagnolo et al. 10.1016/j.rse.2019.111288
12. Understanding and modelling wildfire regimes: an ecological perspective S. Harrison et al. 10.1088/1748-9326/ac39be
13. Mapping Cropland Burned Area in Northeastern China by Integrating Landsat Time Series and Multi-Harmonic Model J. Liu et al. 10.3390/rs13245131
14. Performance Analysis of Deep Convolutional Autoencoders with Different Patch Sizes for Change Detection from Burnt Areas P. de Bem et al. 10.3390/rs12162576
15. Assessing the Accuracy of MODIS MCD64A1 C6 and FireCCI51 Burned Area Products in Mediterranean Ecosystems T. Katagis & I. Gitas 10.3390/rs14030602
16. Accounting for forest fire risks: global insights for climate change mitigation L. Chu et al. 10.1007/s11027-023-10087-0
17. Accuracy estimation of two global burned area products at national scale T. Katagis & I. Gitas 10.1088/1755-1315/932/1/012001
18. Temporal Anomalies in Burned Area Trends: Satellite Estimations of the Amazonian 2019 Fire Crisis J. Lizundia-Loiola et al. 10.3390/rs12010151
19. Burned area detection and mapping using time series Sentinel-2 multispectral images P. Liu et al. 10.1016/j.rse.2023.113753
20. Evaluation and comparison of Sentinel-2 MSI, Landsat 8 OLI, and EFFIS data for forest fires mapping. Illustrations from the summer 2017 fires in Tunisia H. Achour et al. 10.1080/10106049.2021.1980118
21. A remote sensing-based approach to estimating the fire spread rate parameter for individual burn patch extraction M. Humber et al. 10.1080/01431161.2022.2027544
22. Assessment of k-Nearest Neighbor and Random Forest Classifiers for Mapping Forest Fire Areas in Central Portugal Using Landsat-8, Sentinel-2, and Terra Imagery A. Pacheco et al. 10.3390/rs13071345
23. Deep Learning Approaches for Wildland Fires Using Satellite Remote Sensing Data: Detection, Mapping, and Prediction R. Ghali & M. Akhloufi 10.3390/fire6050192
24. Interannual variability and climatic sensitivity of global wildfire activity R. Tang et al. 10.1016/j.accre.2021.07.001
25. Central African biomass carbon losses and gains during 2010–2019 Z. Zhao et al. 10.1016/j.oneear.2024.01.021
26. Optimizing afforestation and reforestation strategies to enhance ecosystem services in critically degraded regions . Fahrudin et al. 10.1016/j.tfp.2024.100700
27. Burned Area Detection and Mapping: Intercomparison of Sentinel-1 and Sentinel-2 Based Algorithms over Tropical Africa M. Tanase et al. 10.3390/rs12020334
28. Validating MCD64A1 and FireCCI51 burned area mapping in the Qinghai-Tibetan Plateau Y. Huang et al. 10.1080/10106049.2023.2285345
29. Modeling and prediction of fire occurrences along an elevational gradient in Western Himalayas S. Bar et al. 10.1016/j.apgeog.2022.102867
30. Observational evidence of wildfire-promoting soil moisture anomalies S. O et al. 10.1038/s41598-020-67530-4
31. Validation of Earth Observation Time-Series: A Review for Large-Area and Temporally Dense Land Surface Products S. Mayr et al. 10.3390/rs11222616
32. High-resolution atmospheric mercury emission from open biomass burning in China: Integration of localized emission factors and multi-source finer resolution remote sensing data Z. Xu et al. 10.1016/j.envint.2023.108102
33. Exploitation of Sentinel-2 Time Series to Map Burned Areas at the National Level: A Case Study on the 2017 Italy Wildfires F. Filipponi 10.3390/rs11060622
34. A Preliminary Global Automatic Burned-Area Algorithm at Medium Resolution in Google Earth Engine E. Roteta et al. 10.3390/rs13214298
35. IntelliSense silk fibroin ionotronic batteries for wildfire detection and alarm Q. Liu et al. 10.1016/j.nanoen.2022.107630
36. Assessment of Burned Areas during the Pantanal Fire Crisis in 2020 Using Sentinel-2 Images Y. Shimabukuro et al. 10.3390/fire6070277
37. Heating effect on chromium speciation and mobility in Cr-rich soils: A snapshot from New Caledonia G. Thery et al. 10.1016/j.scitotenv.2024.171037
38. Forty-Year Fire History Reconstruction from Landsat Data in Mediterranean Ecosystems of Algeria following International Standards M. Kouachi et al. 10.3390/rs16132500
39. Implementation of the Burned Area Component of the Copernicus Climate Change Service: From MODIS to OLCI Data J. Lizundia-Loiola et al. 10.3390/rs13214295
40. Mapping tropical forest degradation with deep learning and Planet NICFI data R. Dalagnol et al. 10.1016/j.rse.2023.113798
41. Evaluating the Abilities of Satellite-Derived Burned Area Products to Detect Forest Burning in China X. Wang et al. 10.3390/rs15133260
42. Response of simulated burned area to historical changes in environmental and anthropogenic factors: a comparison of seven fire models L. Teckentrup et al. 10.5194/bg-16-3883-2019
43. Global Detection of Long-Term (1982–2017) Burned Area with AVHRR-LTDR Data G. Otón et al. 10.3390/rs11182079
44. Spatiotemporal dynamics of ecosystem fires and biomass burning-induced carbon emissions in China over the past two decades A. Chen et al. 10.1016/j.geosus.2020.03.002
45. A novel deep Siamese framework for burned area mapping Leveraging mixture of experts S. Seydi et al. 10.1016/j.engappai.2024.108280
46. Assessing satellite-derived fire patches with functional diversity trait methods M. Moreno et al. 10.1016/j.rse.2020.111897
47. High Resolution (30 m) Burned Area Product Improves the Ability for Carbon Emission Estimation in Africa B. Qi et al. 10.1029/2024EF005051
48. The Landscape Fire Scars Database: mapping historical burned area and fire severity in Chile A. Miranda et al. 10.5194/essd-14-3599-2022
49. Refining historical burned area data from satellite observations V. Fernández-García & C. Kull 10.1016/j.jag.2023.103350
50. Future climate change impact on wildfire danger over the Mediterranean: the case of Greece A. Rovithakis et al. 10.1088/1748-9326/ac5f94
51. Fire decline in dry tropical ecosystems enhances decadal land carbon sink Y. Yin et al. 10.1038/s41467-020-15852-2
52. Using An Attention-Based LSTM Encoder–Decoder Network for Near Real-Time Disturbance Detection Y. Yuan et al. 10.1109/JSTARS.2020.2988324
53. Suitability of band angle indices for burned area mapping in the Maule Region (Chile) P. Oliva et al. 10.3389/ffgc.2022.1052299
54. Analysis of Trends in the FireCCI Global Long Term Burned Area Product (1982–2018) G. Otón et al. 10.3390/fire4040074
55. Remote Sensing of Forest Burnt Area, Burn Severity, and Post-Fire Recovery: A Review E. Kurbanov et al. 10.3390/rs14194714
56. Lightning-induced fire regime in Portugal based on satellite-derived and in situ data L. Menezes et al. 10.1016/j.agrformet.2024.110108
57. Influence of atmospheric teleconnections on interannual variability of Arctic-boreal fires Z. Zhao et al. 10.1016/j.scitotenv.2022.156550
58. Description and evaluation of the JULES-ES set-up for ISIMIP2b C. Mathison et al. 10.5194/gmd-16-4249-2023
59. Fire, flammability and functional traits at the forefront of global change ecology R. Mitchell & A. Martin 10.1111/1365-2435.14432
60. Recent global and regional trends in burned area and their compensating environmental controls M. Forkel et al. 10.1088/2515-7620/ab25d2
61. Evaluating accuracy of four MODIS-derived burned area products for tropical peatland and non-peatland fires Y. Vetrita et al. 10.1088/1748-9326/abd3d1
62. A new lightning scheme in the Canadian Atmospheric Model (CanAM5.1): implementation, evaluation, and projections of lightning and fire in future climates C. Whaley et al. 10.5194/gmd-17-7141-2024
63. Landsat and Sentinel-2 Based Burned Area Mapping Tools in Google Earth Engine E. Roteta et al. 10.3390/rs13040816
64. Estimating the Carbon Emissions of Remotely Sensed Energy-Intensive Industries Using VIIRS Thermal Anomaly-Derived Industrial Heat Sources and Auxiliary Data X. Kong et al. 10.3390/rs14122901
65. Assessment and characterization of sources of error impacting the accuracy of global burned area products M. Franquesa et al. 10.1016/j.rse.2022.113214
66. Satellite Remote Sensing Contributions to Wildland Fire Science and Management E. Chuvieco et al. 10.1007/s40725-020-00116-5
67. Assessing the accuracy of remotely sensed fire datasets across the southwestern Mediterranean Basin L. Galizia et al. 10.5194/nhess-21-73-2021
68. Anticipating Future Risks of Climate-Driven Wildfires in Boreal Forests S. Corning et al. 10.3390/fire7040144
69. Extreme Events Contributing to Tipping Elements and Tipping Points A. Romanou et al. 10.1007/s10712-024-09863-7
70. Enhancing burned area monitoring with VIIRS dataset: A case study in Sub-Saharan Africa B. Ouattara et al. 10.1016/j.srs.2024.100165
71. Understanding wildfire occurrence and size in Jalisco, Mexico: A spatio-temporal analysis C. Toledo-Jaime et al. 10.1016/j.foreco.2024.122349
72. Global ecosystems and fire: Multi‐model assessment of fire‐induced tree‐cover and carbon storage reduction G. Lasslop et al. 10.1111/gcb.15160
73. Analysis of Spectral Separability for Detecting Burned Areas Using Landsat-8 OLI/TIRS Images under Different Biomes in Brazil and Portugal A. Pacheco et al. 10.3390/f14040663
74. Reassessment of carbon emissions from fires and a new estimate of net carbon uptake in Russian forests in 2001–2021 A. Romanov et al. 10.1016/j.scitotenv.2022.157322
75. Validation of MCD64A1 and FireCCI51 cropland burned area mapping in Ukraine J. Hall et al. 10.1016/j.jag.2021.102443
76. The smokescreen of Russian protected areas R. Cazzolla Gatti et al. 10.1016/j.scitotenv.2021.147372
77. Towards an ensemble-based evaluation of land surface models in light of uncertain forcings and observations V. Arora et al. 10.5194/bg-20-1313-2023
78. Progress and Limitations in the Satellite-Based Estimate of Burnt Areas G. Laneve et al. 10.3390/rs16010042
79. The Temporal-Based Forest Disturbance Monitoring Analysis: A Case Study of Nature Reserves of Hainan Island of China From 1987 to 2020 H. Xiao et al. 10.3389/fenvs.2022.891752
80. Development of a consistent global long-term burned area product (1982–2018) based on AVHRR-LTDR data G. Otón et al. 10.1016/j.jag.2021.102473
81. Assessing wildfire activity and forest loss in protected areas of the Amazon basin E. Da Ponte et al. 10.1016/j.apgeog.2023.102970
82. Google Earth Engine ile Türkiye'de Yanmış Alanların MODIS ve FireCCI51 Küresel Yanmış Alan Uydu Gözlem Verileriyle Karşılaştırmalı Değerlendirilmesi H. TONBUL 10.48123/rsgis.1410382
83. “Forest fire emissions: A contribution to global climate change” S. Singh 10.3389/ffgc.2022.925480
84. A Global Bottom‐Up Approach to Estimate Fuel Consumed by Fires Using Above Ground Biomass Observations F. Di Giuseppe et al. 10.1029/2021GL095452
85. Emergent relationships with respect to burned area in global satellite observations and fire-enabled vegetation models M. Forkel et al. 10.5194/bg-16-57-2019
86. The Landsat Burned Area algorithm and products for the conterminous United States T. Hawbaker et al. 10.1016/j.rse.2020.111801
87. FIRED (Fire Events Delineation): An Open, Flexible Algorithm and Database of US Fire Events Derived from the MODIS Burned Area Product (2001–2019) J. Balch et al. 10.3390/rs12213498
88. Annual and Seasonal Patterns of Burned Area Products in Arctic-Boreal North America and Russia for 2001–2020 A. Clelland et al. 10.3390/rs16173306
89. Sources of Uncertainty in Regional and Global Terrestrial CO2 Exchange Estimates A. Bastos et al. 10.1029/2019GB006393
90. Mechanisms for Data Acquisition to Train Artificial Intelligence Models for Detecting Increased Susceptibility to Fire Situations by Using Internet of Things Devices and Satellite Systems . Dawid Jurczyński & . Paweł Buchwald 10.12845/sft.63.1.2024.3
91. A Comparison of Burned Area Time Series in the Alaskan Boreal Forests from Different Remote Sensing Products J. Moreno-Ruiz et al. 10.3390/f10050363
92. Detection and impacts of tiling artifacts in MODIS burned area classification T. Liu & M. Crowley 10.1088/2633-1357/abd8e2
93. Microscopic charcoals in ocean sediments off Africa track past fire intensity from the continent A. Haliuc et al. 10.1038/s43247-023-00800-x
94. Global and Regional Trends and Drivers of Fire Under Climate Change M. Jones et al. 10.1029/2020RG000726
95. Constraining modelled global vegetation dynamics and carbon turnover using multiple satellite observations M. Forkel et al. 10.1038/s41598-019-55187-7
96. Sharing Multiple Perspectives on Burning: Towards a Participatory and Intercultural Fire Management Policy in Venezuela, Brazil, and Guyana B. Bilbao et al. 10.3390/fire2030039
97. Interactions between hot and dry fuel conditions and vegetation dynamics in the 2017 fire season in Portugal T. Ermitão et al. 10.1088/1748-9326/ac8be4
98. Wildfire Burnt Area Severity Classification from UAV-Based RGB and Multispectral Imagery T. Simes et al. 10.3390/rs16010030
99. Country-level fire perimeter datasets (2001–2021) A. Mahood et al. 10.1038/s41597-022-01572-3
100. A Synergetic Approach to Burned Area Mapping Using Maximum Entropy Modeling Trained with Hyperspectral Data and VIIRS Hotspots A. Fernández-Manso & C. Quintano 10.3390/rs12050858
101. Missing Burns in the High Northern Latitudes: The Case for Regionally Focused Burned Area Products D. Chen et al. 10.3390/rs13204145
102. Quantification of organic carbon and black carbon emissions, distribution, and carbon variation in diverse vegetative ecosystems across India V. Karthik et al. 10.1016/j.envpol.2022.119790
103. Çok Bantlı Uydu Görüntüleriyle Orman Yangınlarında Hasar Tespiti N. POLAT & Y. KAYA 10.24011/barofd.837507
104. Burned Area Classification Based on Extreme Learning Machine and Sentinel-2 Images J. Gajardo et al. 10.3390/app12010009
105. Regional-scale fire severity mapping of Eucalyptus forests with the Landsat archive D. Dixon et al. 10.1016/j.rse.2021.112863
106. Long term post-fire recovery of woody plants in savannas of central Brazil W. Machida et al. 10.1016/j.foreco.2021.119255
107. MOSEV: a global burn severity database from MODIS (2000–2020) E. Alonso-González & V. Fernández-García 10.5194/essd-13-1925-2021
108. Sentinel-2 Reference Fire Perimeters for the Assessment of Burned Area Products over Latin America and the Caribbean for the Year 2019 J. Gonzalez-Ibarzabal et al. 10.3390/rs16071166
109. Influence of Fire on the Carbon Cycle and Climate G. Lasslop et al. 10.1007/s40641-019-00128-9
110. Evaluation of Four Satellite-Derived Fire Products in the Fire-Prone, Cloudy, and Mountainous Area Over Subtropical China M. Jiao et al. 10.1109/LGRS.2022.3188259
111. Satellite-Derived Variation in Burned Area in China from 2001 to 2018 and Its Response to Climatic Factors X. Wang et al. 10.3390/rs13071287
112. Development of a standard database of reference sites for validating global burned area products M. Franquesa et al. 10.5194/essd-12-3229-2020
113. Global climate change below 2 °C avoids large end century increases in burned area in Canada S. Curasi et al. 10.1038/s41612-024-00781-4
114. Fire Monitoring Algorithm and Its Application on the Geo-Kompsat-2A Geostationary Meteorological Satellite J. Chen et al. 10.3390/rs14112655
115. Remote Sensing Applications for Mapping Large Wildfires Based on Machine Learning and Time Series in Northwestern Portugal S. dos Santos et al. 10.3390/fire6020043
116. MODIS Sensor Capability to Burned Area Mapping—Assessment of Performance and Improvements Provided by the Latest Standard Products in Boreal Regions J. Moreno-Ruiz et al. 10.3390/s20185423
117. Global burned area mapping from Sentinel-3 Synergy and VIIRS active fires J. Lizundia-Loiola et al. 10.1016/j.rse.2022.113298
118. Estimation of post-fire vegetation recovery in boreal forests using solar-induced chlorophyll fluorescence (SIF) data M. Guo et al. 10.1071/WF20162
119. Intercomparison of Burned Area Products and Its Implication for Carbon Emission Estimations in the Amazon A. Pessôa et al. 10.3390/rs12233864
120. Burned Area Detection Using Multi-Sensor SAR, Optical, and Thermal Data in Mediterranean Pine Forest S. Abdikan et al. 10.3390/f13020347
121. Remote sensing assessment of wildfire using high-resolution PlanetScope satellite observations: A case study on Co Tien Mountain, Nha Trang City, Vietnam B. Pham-Duc & H. Nguyen 10.15243/jdmlm.2024.121.6491
122. Spectral signature analysis of false positive burned area detection from agricultural harvests using Sentinel-2 data D. van Dijk et al. 10.1016/j.jag.2021.102296
123. The impacts of modelling prescribed vs. dynamic land cover in a high-CO2 future scenario – greening of the Arctic and Amazonian dieback S. Kou-Giesbrecht et al. 10.5194/bg-21-3339-2024
124. Monitoring Landsat Based Burned Area as an Indicator of Sustainable Development Goals M. Wei et al. 10.1029/2020EF001960
125. Heatwaves and wildfires suffocate our healthy start to life: time to assess impact and take action A. Bansal et al. 10.1016/S2542-5196(23)00134-1
126. Fire regime of peatlands in the Angolan Highlands M. Lourenco et al. 10.1007/s10661-022-10704-6
127. The Impact of Climate Forcing Biases and the Nitrogen Cycle on Land Carbon Balance Projections C. Seiler et al. 10.1029/2023MS003749
128. A System for Burned Area Detection on Multispectral Imagery M. Zanetti et al. 10.1109/TGRS.2021.3110280
129. Deep-learning-based burned area mapping using the synergy of Sentinel-1&2 data Q. Zhang et al. 10.1016/j.rse.2021.112575
130. Increased burned area in the Pantanal over the past two decades D. Correa et al. 10.1016/j.scitotenv.2022.155386
131. 30 m Resolution Global Annual Burned Area Mapping Based on Landsat Images and Google Earth Engine T. Long et al. 10.3390/rs11050489
132. New Inventories of Global Carbon Dioxide Emissions through Biomass Burning in 2001–2020 T. Shiraishi et al. 10.3390/rs13101914
133. Winter North Atlantic SST as a Precursor of Spring Eurasian Wildfire M. Meng & D. Gong 10.1029/2022GL099920
134. On the use of Earth Observation to support estimates of national greenhouse gas emissions and sinks for the Global stocktake process: lessons learned from ESA-CCI RECCAP2 A. Bastos et al. 10.1186/s13021-022-00214-w
135. Comparing machine learning algorithms to predict vegetation fire detections in Pakistan F. Shahzad et al. 10.1186/s42408-024-00289-5
136. Comparable biophysical and biogeochemical feedbacks on warming from tropical moist forest degradation L. Zhu et al. 10.1038/s41561-023-01137-y
137. A comprehensive characterization of MODIS daily burned area mapping accuracy across fire sizes in tropical savannas M. Campagnolo et al. 10.1016/j.rse.2020.112115
138. Monitoring trends in global vegetation fire hot spots using MODIS data C. Reddy & N. Sarika 10.1007/s41324-022-00457-2
139. Evaluating recovery metrics derived from optical time series over tropical forest ecosystems W. De Keersmaecker et al. 10.1016/j.rse.2022.112991
140. Fire regime in Goiás - Brazil and Mozambique between 2010 and 2019: frequency, recurrence, and most affected cover classes S. Santos et al. 10.5327/Z2176-94781303
141. Current Forest–Savanna Transition in Northern South America Departs from Typical Climatic Thresholds S. Valencia et al. 10.1007/s10021-023-00872-y
142. Monthly mapping of Indonesia’s burned areas: implementation, history, techniques, and future directions Y. Vetrita et al. 10.1080/01431161.2024.2421942
143. 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
144. Climate influence on the 2019 fires in Amazonia X. Dong et al. 10.1016/j.scitotenv.2021.148718
145. Using long temporal reference units to assess the spatial accuracy of global satellite-derived burned area products M. Franquesa et al. 10.1016/j.rse.2021.112823
146. Combining European Earth Observation products with Dynamic Global Vegetation Models for estimating Essential Biodiversity Variables M. Dantas de Paula et al. 10.1080/17538947.2019.1597187
147. CLASSIC v1.0: the open-source community successor to the Canadian Land Surface Scheme (CLASS) and the Canadian Terrestrial Ecosystem Model (CTEM) – Part 2: Global benchmarking C. Seiler et al. 10.5194/gmd-14-2371-2021
148. A Practical Method for High-Resolution Burned Area Monitoring Using Sentinel-2 and VIIRS M. Pinto et al. 10.3390/rs13091608
149. Spatio-temporal characterization of landscape fire in relation to anthropogenic activity and climatic variability over the Western Himalaya, India S. Bar et al. 10.1080/15481603.2021.1879495
150. Mapping South America’s Drylands through Remote Sensing—A Review of the Methodological Trends and Current Challenges K. Ganem et al. 10.3390/rs14030736
151. Improving the south America wildfires smoke estimates: Integration of polar-orbiting and geostationary satellite fire products in the Brazilian biomass burning emission model (3BEM) G. Pereira et al. 10.1016/j.atmosenv.2022.118954
152. Determining fire frequency and its relationship with rangeland aboveground grass biomass using MODIS and Landsat imagery C. Munyati & T. Mashego 10.1080/01431161.2023.2221801
153. 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
154. Global patterns and influencing factors of post-fire land cover change S. Wu et al. 10.1016/j.gloplacha.2023.104076
155. Evaluating the Performance of the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) Tailored to the Pan‐Canadian Domain S. Curasi et al. 10.1029/2022MS003480
156. Fire Responses to the 2010 and 2015/2016 Amazonian Droughts C. Silva Junior et al. 10.3389/feart.2019.00097
157. Spatial Pattern Analysis of Global Burned Area in 2005 Based on Landsat Satellite Images Z. Zhang et al. 10.1088/1755-1315/428/1/012078
158. Self-Adjusting Thresholding for Burnt Area Detection Based on Optical Images E. Woźniak & S. Aleksandrowicz 10.3390/rs11222669
159. A deep learning approach for mapping and dating burned areas using temporal sequences of satellite images M. Pinto et al. 10.1016/j.isprsjprs.2019.12.014
160. A novel data source for human-caused wildfires in China: extracting information from judgment documents J. Xue et al. 10.1080/19475705.2024.2361132
161. A review of freely accessible global datasets for the study of floods, droughts and their interactions with human societies S. Lindersson et al. 10.1002/wat2.1424
162. Assessing the Shape Accuracy of Coarse Resolution Burned Area Identifications M. Humber et al. 10.1109/TGRS.2019.2943901
163. Estimating the multi-decadal carbon deficit of burned Amazonian forests C. Silva et al. 10.1088/1748-9326/abb62c
164. Rapid and automatic burned area detection using sentinel-2 time-series images in google earth engine cloud platform: a case study over the Andika and Behbahan Regions, Iran H. Farhadi et al. 10.1007/s10661-022-10045-4
165. Global intercomparison of functional pyrodiversity from two satellite sensors M. Moreno et al. 10.1080/01431161.2021.1999529
166. Historical and future global burned area with changing climate and human demography C. Wu et al. 10.1016/j.oneear.2021.03.002
167. About Validation-Comparison of Burned Area Products G. Valencia et al. 10.3390/rs12233972
168. African burned area and fire carbon emissions are strongly impacted by small fires undetected by coarse resolution satellite data R. Ramo et al. 10.1073/pnas.2011160118
169. Development of an emission estimation method with satellite observations for significant forest fires and comparison with global fire emission inventories: Application to catastrophic fires of summer 2021 over the Eastern Mediterranean E. Bilgiç et al. 10.1016/j.atmosenv.2023.119871
170. Regional-Scale Assessment of Burn Scar Mapping in Southwestern Amazonia Using Burned Area Products and CBERS/WFI Data Cubes P. Ferro et al. 10.3390/fire7030067
171. Deep learning-based burned forest areas mapping via Sentinel-2 imagery: a comparative study Ü. Atasever & E. Tercan 10.1007/s11356-023-31575-5
172. Variability and predictability of bush fire in Guinea on inter-annual and multi-year timescales based on NDVI-MODIS datasets analysis B. M. et al. 10.5897/AJEST2018.2562
173. Historical background and current developments for mapping burned area from satellite Earth observation E. Chuvieco et al. 10.1016/j.rse.2019.02.013