421 citations as recorded by crossref.

1. Near Real-Time Automated Early Mapping of the Perimeter of Large Forest Fires from the Aggregation of VIIRS and MODIS Active Fires in Mexico C. Briones-Herrera et al. https://doi.org/10.3390/rs12122061
2. OCO‐2 Satellite‐Imposed Constraints on Terrestrial Biospheric CO2 Fluxes Over South Asia S. Philip et al. https://doi.org/10.1029/2021JD035035
3. Influence of agricultural activities, forest fires and agro-industries on air quality in Thailand W. Phairuang et al. https://doi.org/10.1016/j.jes.2016.02.007
4. Net biome production of the Amazon Basin in the 21st century B. POULTER et al. https://doi.org/10.1111/j.1365-2486.2009.02064.x
5. Fire Regime Analysis in Lebanon (2001–2020): Combining Remote Sensing Data in a Scarcely Documented Area G. Majdalani et al. https://doi.org/10.3390/fire5050141
6. Global Pyrogeography: the Current and Future Distribution of Wildfire M. Krawchuk et al. https://doi.org/10.1371/journal.pone.0005102
7. Detection of vegetation fires and burnt areas by remote sensing in insular Southeast Asian conditions: current status of knowledge and future challenges J. Miettinen et al. https://doi.org/10.1080/01431161.2013.777489
8. Tools based on proprietary and free/open source geospatial software for CO emission maps analysis and comparison F. Migliaccio et al. https://doi.org/10.1007/s12518-011-0075-8
9. Spatial and temporal variability in the ratio of trace gases emitted from biomass burning T. van Leeuwen & G. van der Werf https://doi.org/10.5194/acp-11-3611-2011
10. Performance of heat spots obtained from satellite datasets to represent burned areas in Andean ecosystems of Cusco, Peru R. Zubieta et al. https://doi.org/10.1016/j.rsase.2023.101020
11. Modeling study of biomass burning plumes and their impact on urban air quality; a case study of Santiago de Chile G. Cuchiara et al. https://doi.org/10.1016/j.atmosenv.2017.07.002
12. Fire Eases Imbalances of Nitrogen and Phosphorus in Woody Plants F. Dijkstra & M. Adams https://doi.org/10.1007/s10021-015-9861-1
13. Detection rates of the MODIS active fire product in the United States T. Hawbaker et al. https://doi.org/10.1016/j.rse.2007.12.008
14. An operational system for the assimilation of the satellite information on wild-land fires for the needs of air quality modelling and forecasting M. Sofiev et al. https://doi.org/10.5194/acp-9-6833-2009
15. Defining a fire year for reporting and analysis of global interannual fire variability L. Boschetti & D. Roy https://doi.org/10.1029/2008JG000686
16. Biomass-burning smoke heights over the Amazon observed from space L. Gonzalez-Alonso et al. https://doi.org/10.5194/acp-19-1685-2019
17. Atmospheric impacts of the 2010 Russian wildfires: integrating modelling and measurements of an extreme air pollution episode in the Moscow region I. Konovalov et al. https://doi.org/10.5194/acp-11-10031-2011
18. The Value of Satellite-Based Active Fire Data for Monitoring, Reporting and Verification of REDD+ in the Lao PDR D. Müller et al. https://doi.org/10.1007/s10745-013-9565-0
19. Space‐Based Observations for Understanding Changes in the Arctic‐Boreal Zone B. Duncan et al. https://doi.org/10.1029/2019RG000652
20. GIS-Based Forest Fire Risk Model: A Case Study in Laoshan National Forest Park, Nanjing P. Zhao et al. https://doi.org/10.3390/rs13183704
21. Enhancing seasonal fire predictions with hybrid dynamical and random forest models M. Torres-Vázquez et al. https://doi.org/10.1038/s44304-025-00069-4
22. Identifying the density of grassland fire points with kernel density estimation based on spatial distribution characteristics Z. Shuo et al. https://doi.org/10.1515/geo-2020-0265
23. Variations of concentration of aerosol particles (≤10 μm) in Vilnius D. Šopauskienė & D. Jasinevičienė https://doi.org/10.3952/lithjphys.49303
24. Large-scale weather types, forest fire danger, and wildfire occurrence in the Alps C. Wastl et al. https://doi.org/10.1016/j.agrformet.2012.08.011
25. Estimating Asian terrestrial carbon fluxes from CONTRAIL aircraft and surface CO2 observations for the period 2006–2010 H. Zhang et al. https://doi.org/10.5194/acp-14-5807-2014
26. Pola Distribusi Spasial-Temporal Hotspot dan Variasi Standardized Precipitation Index pada Lahan Gambut Tropis di Kepulauan Meranti, Riau M. Riyadi et al. https://doi.org/10.14710/jil.20.3.457-464
27. Estimation of Biomass Burning Emissions in South and Southeast Asia Based on FY-4A Satellite Observations Y. Wang et al. https://doi.org/10.3390/atmos16050582
28. Remote Sensing and GIS Based Forest Fire Vulnerability Assessment in Dachigam National Park, North Western Himalaya M. Rather et al. https://doi.org/10.3923/ajaps.2018.98.114
29. Spatial analysis of hotspot data for tracing the source of annual peat fires in South Sumatera, Indonesia A. Hamzah et al. https://doi.org/10.1088/1755-1315/393/1/012068
30. Evaluating the performance of pyrogenic and biogenic emission inventories against one decade of space-based formaldehyde columns T. Stavrakou et al. https://doi.org/10.5194/acp-9-1037-2009
31. CO emissions from biomass burning in South-east Asia in the 2006 El Niño year: shipboard and AIRS satellite observations H. Nara et al. https://doi.org/10.1071/EN10113
32. Comparison of global inventories of CO2 emissions from biomass burning during 2002–2011 derived from multiple satellite products Y. Shi et al. https://doi.org/10.1016/j.envpol.2015.08.009
33. Relationship between MODIS fire hot spot count and burned area in a degraded tropical peat swamp forest in Central Kalimantan, Indonesia K. Tansey et al. https://doi.org/10.1029/2008JD010717
34. Human‐mediated trophic mismatch between fire, plants and herbivores M. Lashley et al. https://doi.org/10.1111/ecog.06045
35. Wildfire probability assessment and analysis based on multi-source data in Guangxi Province, China K. Xu et al. https://doi.org/10.1016/j.ecolind.2025.114148
36. Initial Estimates of Mercury Emissions to the Atmosphere from Global Biomass Burning H. Friedli et al. https://doi.org/10.1021/es802703g
37. Quantifying burned area of wildfires in the western United States from polar-orbiting and geostationary satellite active-fire detections M. Berman et al. https://doi.org/10.1071/WF22022
38. Using continental observations in global atmospheric inversions of CO₂: North American carbon sources and sinks M. Butler et al. https://doi.org/10.1111/j.1600-0889.2010.00501.x
39. Ethane, ethyne and carbon monoxide concentrations in the upper troposphere and lower stratosphere from ACE and GEOS-Chem: a comparison study G. González Abad et al. https://doi.org/10.5194/acp-11-9927-2011
40. Development of a Sentinel-2 burned area algorithm: Generation of a small fire database for sub-Saharan Africa E. Roteta et al. https://doi.org/10.1016/j.rse.2018.12.011
41. Quantifying regional, time-varying effects of cropland and pasture on vegetation fire S. Rabin et al. https://doi.org/10.5194/bg-12-6591-2015
42. A VIIRS direct broadcast algorithm for rapid response mapping of wildfire burned area in the western United States S. Urbanski et al. https://doi.org/10.1016/j.rse.2018.10.007
43. Evolution of the representation of global vegetation by vegetation continuous fields C. DiMiceli et al. https://doi.org/10.1016/j.rse.2020.112271
44. Smoke emissions from the extreme wildfire events in central Portugal in October 2017 A. Fernandes et al. https://doi.org/10.1071/WF21097
45. Utility of daily 3 m Planet Fusion Surface Reflectance data for tillage practice mapping with deep learning D. Luo et al. https://doi.org/10.1016/j.srs.2023.100085
46. Fire Response to Local Climate Variability: Huascarán National Park, Peru J. All et al. https://doi.org/10.4996/fireecology.130288764
47. Predictive fire occurrence modelling to improve burned area estimation at a regional scale: A case study in East Caprivi, Namibia M. Siljander https://doi.org/10.1016/j.jag.2009.06.004
48. Regional-Scale Assessment of Burn Scar Mapping in Southwestern Amazonia Using Burned Area Products and CBERS/WFI Data Cubes P. Ferro et al. https://doi.org/10.3390/fire7030067
49. Characterizing boreal forest wildfire with multi-temporal Landsat and LIDAR data M. Wulder et al. https://doi.org/10.1016/j.rse.2009.03.004
50. Characterising fire spatial pattern interactions with climate and vegetation in Colombia D. Armenteras-Pascual et al. https://doi.org/10.1016/j.agrformet.2010.11.002
51. Net ecosystem fluxes of isoprene over tropical South America inferred from Global Ozone Monitoring Experiment (GOME) observations of HCHO columns M. Barkley et al. https://doi.org/10.1029/2008JD009863
52. Global upper-tropospheric formaldehyde: seasonal cycles observed by the ACE-FTS satellite instrument G. Dufour et al. https://doi.org/10.5194/acp-9-3893-2009
53. Estimating carbon emissions from African wildfires V. Lehsten et al. https://doi.org/10.5194/bg-6-349-2009
54. Co-variability of smoke and fire in the Amazon basin A. Mishra et al. https://doi.org/10.1016/j.atmosenv.2015.03.007
55. Ammonia emissions from biomass burning in the continental United States C. Bray et al. https://doi.org/10.1016/j.atmosenv.2018.05.052
56. Global modeling of secondary organic aerosol formation from aromatic hydrocarbons: high- vs. low-yield pathways D. Henze et al. https://doi.org/10.5194/acp-8-2405-2008
57. Climate change feedbacks to microbial decomposition in boreal soils S. Allison & K. Treseder https://doi.org/10.1016/j.funeco.2011.01.003
58. Departing from the Colonial Path: A Critical Approach to Studying Fire Regime Changes in West Africa S. Caillault et al. https://doi.org/10.1177/27539687261417715
59. The Impact of Accounting for Future Wood Production in Global Vertebrate Biodiversity Assessments K. Schulze et al. https://doi.org/10.1007/s00267-020-01322-4
60. Progress and Challenges in Quantifying Wildfire Smoke Emissions, Their Properties, Transport, and Atmospheric Impacts I. Sokolik et al. https://doi.org/10.1029/2018JD029878
61. Self-Adjusting Thresholding for Burnt Area Detection Based on Optical Images E. Woźniak & S. Aleksandrowicz https://doi.org/10.3390/rs11222669
62. Fire decreases gross mineralization rate but does not alter gross nitrification rate in boreal forest soils W. Su et al. https://doi.org/10.1016/j.soilbio.2022.108838
63. An Algorithm for Burned Area Detection in the Brazilian Cerrado Using 4 µm MODIS Imagery R. Libonati et al. https://doi.org/10.3390/rs71115782
64. Spatial distribution of grassland fires at the regional scale based on the MODIS active fire products Z. Zhang et al. https://doi.org/10.1071/WF16026
65. Fire parameterization on a global scale O. Pechony & D. Shindell https://doi.org/10.1029/2009JD011927
66. Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997–2009) G. van der Werf et al. https://doi.org/10.5194/acp-10-11707-2010
67. Global impacts of aerosols from particular source regions and sectors D. Koch et al. https://doi.org/10.1029/2005JD007024
68. Assessment of gaseous emissions and radiative forcing in Indian forest fires N. Manojkumar & B. Srimuruganandam https://doi.org/10.1080/00207233.2019.1596387
69. Temporal and spatial dynamics in emission of water-soluble ions in fine particulate matter during forest fires in Southwest China X. Zhan et al. https://doi.org/10.3389/ffgc.2023.1250038
70. An Unsupervised Machine Learning-Based Approach for Combining Sentinel 1 and 2 to Assess the Severity of Fires over Large Areas Using a Google Earth Engine C. Riccardi et al. https://doi.org/10.3390/rs18060956
71. Defining fire spread event days for fire-growth modelling J. Podur & B. Wotton https://doi.org/10.1071/WF09001
72. The Chemistry CATT-BRAMS model (CCATT-BRAMS 4.5): a regional atmospheric model system for integrated air quality and weather forecasting and research K. Longo et al. https://doi.org/10.5194/gmd-6-1389-2013
73. The European carbon balance. Part 2: croplands P. CIAIS et al. https://doi.org/10.1111/j.1365-2486.2009.02055.x
74. Remote Sensing for Wildfire Mapping: A Comprehensive Review of Advances, Platforms, and Algorithms R. Guiop-Servan et al. https://doi.org/10.3390/fire8080316
75. Polycyclic aromatic hydrocarbons in Ethiopian soils: Distribution, sources, and implication from energy consumption structures X. Shan et al. https://doi.org/10.1016/j.emcon.2024.100461
76. A new, global, multi‐annual (2000–2007) burnt area product at 1 km resolution K. Tansey et al. https://doi.org/10.1029/2007GL031567
77. Recent acceleration of biomass burning and carbon losses in Alaskan forests and peatlands M. Turetsky et al. https://doi.org/10.1038/ngeo1027
78. The Collection 6 MODIS burned area mapping algorithm and product L. Giglio et al. https://doi.org/10.1016/j.rse.2018.08.005
79. Spatiotemporal analysis of wildfires and their relationship with climate and land use in the Gran Chaco and Pantanal ecoregions C. Vidal-Riveros et al. https://doi.org/10.1016/j.scitotenv.2024.176823
80. Mercury from wildfires: Global emission inventories and sensitivity to 2000–2050 global change A. Kumar et al. https://doi.org/10.1016/j.atmosenv.2017.10.061
81. Estimating smoke emissions over the US Southern Great Plains using MODIS fire radiative power and aerosol observations N. Jordan et al. https://doi.org/10.1016/j.atmosenv.2007.12.023
82. An Unsupervised Burned Area Mapping Approach Using Sentinel-2 Images M. Sismanis et al. https://doi.org/10.3390/land12020379
83. The covariation of Northern Hemisphere summertime CO2 with surface temperature in boreal regions D. Wunch et al. https://doi.org/10.5194/acp-13-9447-2013
84. Fire occurrence on Mount Kenya and patterns of burning T. Downing et al. https://doi.org/10.1016/j.grj.2016.12.003
85. Long-term study of spatial and temporal variations in biomass burning over the Indian region using MODIS products S. POTDAR et al. https://doi.org/10.1007/s12040-024-02351-x
86. Fire dynamics during the 20th century simulated by the Community Land Model S. Kloster et al. https://doi.org/10.5194/bg-7-1877-2010
87. The Spatial–Temporal Emission of Air Pollutants from Biomass Burning during Haze Episodes in Northern Thailand P. Paluang et al. https://doi.org/10.3390/fire7040122
88. Machine Learning for Estimating Leaf Dust Retention Based on Hyperspectral Measurements W. Jing et al. https://doi.org/10.1155/2018/6026259
89. Large wildfire driven increases in nighttime fire activity observed across CONUS from 2003–2020 P. Freeborn et al. https://doi.org/10.1016/j.rse.2021.112777
90. Tropospheric Ozone Assessment Report: Assessment of global-scale model performance for global and regional ozone distributions, variability, and trends P. Young et al. https://doi.org/10.1525/elementa.265
91. Seasonality of vegetation fires as modified by human action: observing the deviation from eco‐climatic fire regimes Y. Le Page et al. https://doi.org/10.1111/j.1466-8238.2010.00525.x
92. Satellite-borne identification and quantification of wildfire smoke emissions in North America via a novel UV-based index Z. Suo et al. https://doi.org/10.1016/j.atmosenv.2025.121069
93. Reconstructed global monthly burned area maps from 1901 to 2020 Z. Guo et al. https://doi.org/10.5194/essd-17-3599-2025
94. Determinants and predictability of global wildfire emissions W. Knorr et al. https://doi.org/10.5194/acp-12-6845-2012
95. Nonlinear rainfall effects on savanna fire activity across the African Humid Period A. Karp et al. https://doi.org/10.1016/j.quascirev.2023.107994
96. Nutrient content and stoichiometry of pelagic Sargassum reflects increasing nitrogen availability in the Atlantic Basin B. Lapointe et al. https://doi.org/10.1038/s41467-021-23135-7
97. Nitrogen deposition in tropical forests from savanna and deforestation fires Y. CHEN et al. https://doi.org/10.1111/j.1365-2486.2009.02156.x
98. Inventory of boreal fire emissions for North America in 2004: Importance of peat burning and pyroconvective injection S. Turquety et al. https://doi.org/10.1029/2006JD007281
99. Increasing synchronicity of global extreme fire weather C. Yin et al. https://doi.org/10.1126/sciadv.adx8813
100. Spectral–Spatial Adaptive Area-to-Point Regression Kriging for MODIS Image Downscaling Y. Zhang et al. https://doi.org/10.1109/JSTARS.2017.2650260
101. Remote sensing estimates of stand-replacement fires in Russia, 2002–2011 A. Krylov et al. https://doi.org/10.1088/1748-9326/9/10/105007
102. Estimating Lightning from Microwave Remote Sensing Data B. Magi et al. https://doi.org/10.1175/JAMC-D-15-0306.1
103. Integrated use of Sentinel-1 and Sentinel-2 data and open-source machine learning algorithms for burnt and unburnt scars A. Tariq et al. https://doi.org/10.1080/19475705.2023.2190856
104. A MODIS-based spatiotemporal assessment of agricultural residue burning in Madhya Pradesh, India S. Verma et al. https://doi.org/10.1016/j.ecolind.2018.04.042
105. Impacts of different biomass burning emission inventories: Simulations of atmospheric CO2 concentrations based on GEOS-Chem M. Su et al. https://doi.org/10.1016/j.scitotenv.2023.162825
106. Forest Fire Risk Zone Mapping of Aalital Rural Municipality, Dadeldhura District, Nepal P. Subedi et al. https://doi.org/10.47352/jmans.2774-3047.115
107. Biofuels: Effects on Land and Fire K. Kline & V. Dale https://doi.org/10.1126/science.321.5886.199
108. Determination of enhancement ratios of HCOOH relative to CO in biomass burning plumes by the Infrared Atmospheric Sounding Interferometer (IASI) M. Pommier et al. https://doi.org/10.5194/acp-17-11089-2017
109. Identifying industrial heat sources using time-series of the VIIRS Nightfire product with an object-oriented approach Y. Liu et al. https://doi.org/10.1016/j.rse.2017.10.019
110. Spatiotemporal variation in nonagricultural open fire emissions in China from 2000 to 2007 Y. Song et al. https://doi.org/10.1029/2008GB003344
111. The Spatiotemporal Changing Dynamics of Miombo Deforestation and Illegal Human Activities for Forest Fire in Kundelungu National Park, Democratic Republic of the Congo Y. Sikuzani et al. https://doi.org/10.3390/fire6050174
112. Can We Go Beyond Burned Area in the Assessment of Global Remote Sensing Products with Fire Patch Metrics? J. Nogueira et al. https://doi.org/10.3390/rs9010007
113. The Coupled Aerosol and Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CATT-BRAMS) – Part 2: Model sensitivity to the biomass burning inventories K. Longo et al. https://doi.org/10.5194/acp-10-5785-2010
114. GLOBAL BURNED-LAND ESTIMATION IN LATIN AMERICA USING MODIS COMPOSITE DATA E. Chuvieco et al. https://doi.org/10.1890/06-2148.1
115. Defining pyromes and global syndromes of fire regimes S. Archibald et al. https://doi.org/10.1073/pnas.1211466110
116. Improved biomass burning emissions from 1750 to 2010 using ice core records and inverse modeling B. Zhang et al. https://doi.org/10.1038/s41467-024-47864-7
117. Regional ecosystem structure and function: ecological insights from remote sensing of tropical forests J. Chambers et al. https://doi.org/10.1016/j.tree.2007.05.001
118. Evaluating MODIS-vegetation continuous field products to assess tree cover change and forest fragmentation in India – A multi-scale satellite remote sensing approach G. Amarnath et al. https://doi.org/10.1016/j.ejrs.2017.05.004
119. Application of Remote Sensing Technology in Wildfire Research: Bibliometric Perspective X. Li et al. https://doi.org/10.1007/s10694-023-01531-3
120. Nationwide summer peaks of OC/EC ratios in the contiguous United States T. Zeng & Y. Wang https://doi.org/10.1016/j.atmosenv.2010.10.038
121. RELAÇÃO ENTRE O ÂNGULO DE VISADA E A ESTIMATIVA DA POTÊNCIA RADIATIVA DO FOGO G. Mataveli et al. https://doi.org/10.1590/S1982-21702015000200021
122. Evaluating the efficiency of the Dong model in determining fire vulnerability in Iran’s Zagros forests S. Baqer Rasooli & A. Bonyad https://doi.org/10.1007/s11676-018-0765-8
123. Comparison of forest burned areas in mainland China derived from MCD45A1 and data recorded in yearbooks from 2001 to 2011 J. Li et al. https://doi.org/10.1071/WF14031
124. Modelling biomass burning emissions and the effect of spatial resolution: a case study for Africa based on the Global Fire Emissions Database (GFED) D. van Wees & G. van der Werf https://doi.org/10.5194/gmd-12-4681-2019
125. Improvement of human-induced wildfire occurrence modeling from a spatial variation of anthropogenic ignition factor in the CLM5 L. Cai et al. https://doi.org/10.1088/1748-9326/acf1b6
126. Biomass burning fuel consumption dynamics in the tropics and subtropics assessed from satellite N. Andela et al. https://doi.org/10.5194/bg-13-3717-2016
127. How do forest fires affect soil greenhouse gas emissions in upland boreal forests? A review C. Ribeiro-Kumara et al. https://doi.org/10.1016/j.envres.2020.109328
128. The sensitivity of CO and aerosol transport to the temporal and vertical distribution of North American boreal fire emissions Y. Chen et al. https://doi.org/10.5194/acp-9-6559-2009
129. Population pressure and global markets drive a decade of forest cover change in Africa's Albertine Rift S. Ryan et al. https://doi.org/10.1016/j.apgeog.2017.02.009
130. The effect of fire on microbial biomass: a meta-analysis of field studies S. Dooley & K. Treseder https://doi.org/10.1007/s10533-011-9633-8
131. A patch-based algorithm for global and daily burned area mapping M. Campagnolo et al. https://doi.org/10.1016/j.rse.2019.111288
132. Climate regulation of fire emissions and deforestation in equatorial Asia G. van der Werf et al. https://doi.org/10.1073/pnas.0803375105
133. Estimates of CO2 from fires in the United States: implications for carbon management C. Wiedinmyer & J. Neff https://doi.org/10.1186/1750-0680-2-10
134. Terrestrial Vegetation in the Coupled Human-Earth System: Contributions of Remote Sensing R. DeFries https://doi.org/10.1146/annurev.environ.33.020107.113339
135. Historical Forest fire Occurrence Analysis in Jambi Province During the Period of 2000 – 2015: Its Distribution & Land Cover Trajectories L. Prasetyo et al. https://doi.org/10.1016/j.proenv.2016.03.096
136. Integrating remotely sensed fires for predicting deforestation for REDD+ D. Armenteras et al. https://doi.org/10.1002/eap.1522
137. Amazon fires in the 21st century: The year of 2020 in evidence M. Silveira et al. https://doi.org/10.1111/geb.13577
138. MODIS–Landsat fusion for large area 30 m burned area mapping L. Boschetti et al. https://doi.org/10.1016/j.rse.2015.01.022
139. Estimates of carbon monoxide emissions from wildfires in northern Eurasia for airquality assessment and climate modeling A. Vivchar et al. https://doi.org/10.1134/S0001433810030023
140. Source contributions to carbonaceous aerosol concentrations in Korea J. Jeong et al. https://doi.org/10.1016/j.atmosenv.2010.11.031
141. GEM-AQ/EC, an on-line global multi-scale chemical weather modelling system: model development and evaluation of global aerosol climatology S. Gong et al. https://doi.org/10.5194/acp-12-8237-2012
142. Combining POLDER-3 satellite observations and WRF-Chem numerical simulations to derive biomass burning aerosol properties over the southeast Atlantic region A. Siméon et al. https://doi.org/10.5194/acp-21-17775-2021
143. Impacts of Russian biomass burning on UK air quality C. Witham & A. Manning https://doi.org/10.1016/j.atmosenv.2007.06.058
144. Hydroclimate variability was the main control on fire activity in northern Africa over the last 50,000 years H. Moore et al. https://doi.org/10.1016/j.quascirev.2022.107578
145. Inferring energy incident on sensors in low-intensity surface fires from remotely sensed radiation and using it to predict tree stem injury M. Dickinson et al. https://doi.org/10.1071/WF18164
146. Ecosystem services and forest fires in India — Context and policy implications from a case study in Andhra Pradesh J. Schmerbeck et al. https://doi.org/10.1016/j.forpol.2014.09.012
147. Orbital‐scale Climate Dynamics may Impact Gzhelian Peatland Wildfire Activity in the Ordos Basin W. DU et al. https://doi.org/10.1111/1755-6724.15327
148. Estimating burn severity and carbon emissions from a historic megafire in boreal forests of China W. Xu et al. https://doi.org/10.1016/j.scitotenv.2020.136534
149. Contribution of ‘human induced fires’ to forest and savanna land conversion dynamics in the Luki Biosphere Reserve landscape, western Democratic Republic of Congo N. Cirezi et al. https://doi.org/10.1080/01431161.2022.2138622
150. Comparing multiple model-derived aerosol optical properties to spatially collocated ground-based and satellite measurements I. Ocko & P. Ginoux https://doi.org/10.5194/acp-17-4451-2017
151. Nitrogen oxides and PAN in plumes from boreal fires during ARCTAS-B and their impact on ozone: an integrated analysis of aircraft and satellite observations M. Alvarado et al. https://doi.org/10.5194/acp-10-9739-2010
152. Systematic assessment of terrestrial biogeochemistry in coupled climate–carbon models J. RANDERSON et al. https://doi.org/10.1111/j.1365-2486.2009.01912.x
153. The impact of North American anthropogenic emissions and lightning on long-range transport of trace gases and their export from the continent during summers 2002 and 2004 M. Martini et al. https://doi.org/10.1029/2010JD014305
154. Assessing Fire Regimes in the Paraguayan Chaco: Implications for Ecological and Fire Management C. Vidal-Riveros et al. https://doi.org/10.3390/fire7100347
155. Analysis and Assessment of the Spatial and Temporal Distribution of Burned Areas in the Amazon Forest F. Cardozo et al. https://doi.org/10.3390/rs6098002
156. Climate controls on the variability of fires in the tropics and subtropics G. van der Werf et al. https://doi.org/10.1029/2007GB003122
157. Meteorological modes of variability for fine particulate matter (PM2.5) air quality in the United States: implications for PM2.5 sensitivity to climate change A. Tai et al. https://doi.org/10.5194/acp-12-3131-2012
158. Biomass burning contribution to black carbon in the Western United States Mountain Ranges Y. Mao et al. https://doi.org/10.5194/acp-11-11253-2011
159. Forest edge burning in the Brazilian Amazon promoted by escaping fires from managed pastures A. Cano‐Crespo et al. https://doi.org/10.1002/2015JG002914
160. Intercomparison of MODIS AQUA and VIIRS I-Band Fires and Emissions in an Agricultural Landscape—Implications for Air Pollution Research K. Vadrevu & K. Lasko https://doi.org/10.3390/rs10070978
161. Satellite versus ground-based estimates of burned area: A comparison between MODIS based burned area and fire agency reports over North America in 2007 S. Mangeon et al. https://doi.org/10.1177/2053019615588790
162. Remote Sensing of Environmental Drivers Influencing the Movement Ecology of Sympatric Wild and Domestic Ungulates in Semi-Arid Savannas, a Review F. Rumiano et al. https://doi.org/10.3390/rs12193218
163. Model‐data comparison of MCI field campaign atmospheric CO2 mole fractions L. Díaz Isaac et al. https://doi.org/10.1002/2014JD021593
164. Competition between plant functional types in the Canadian Terrestrial Ecosystem Model (CTEM) v. 2.0 J. Melton & V. Arora https://doi.org/10.5194/gmd-9-323-2016
165. Effects of landscape pattern and vegetation type on the fire regime of a mesic savanna in Mali P. Laris et al. https://doi.org/10.1016/j.jenvman.2018.08.091
166. Contribution of ocean, fossil fuel, land biosphere, and biomass burning carbon fluxes to seasonal and interannual variability in atmospheric CO2 C. Nevison et al. https://doi.org/10.1029/2007JG000408
167. The newly developed Multi-ensemble Biomass-burning Emissions Inventory (MBEI): characterizing and unraveling spatiotemporal uncertainty in global biomass burning emissions X. Liu et al. https://doi.org/10.5194/essd-18-1203-2026
168. Climate drivers of global wildfire burned area M. Grillakis et al. https://doi.org/10.1088/1748-9326/ac5fa1
169. Assessment of VIIRS 375m active fire detection product for direct burned area mapping P. Oliva & W. Schroeder https://doi.org/10.1016/j.rse.2015.01.010
170. Seasonal Characteristics of Model Uncertainties From Biogenic Fluxes, Transport, and Large‐Scale Boundary Inflow in Atmospheric CO2 Simulations Over North America S. Feng et al. https://doi.org/10.1029/2019JD031165
171. Multi-decadal trends and variability in burned area from the fifth version of the Global Fire Emissions Database (GFED5) Y. Chen et al. https://doi.org/10.5194/essd-15-5227-2023
172. BA_EnCaps: Dense Capsule Architecture for Thermal Scrutiny Q. Safder et al. https://doi.org/10.1109/TGRS.2022.3166352
173. The empirical relationship between satellite-derived tropospheric NO2 and fire radiative power and possible implications for fire emission rates of NOx S. Schreier et al. https://doi.org/10.5194/acp-14-2447-2014
174. Multi-year black carbon emissions from cropland burning in the Russian Federation J. McCarty et al. https://doi.org/10.1016/j.atmosenv.2012.08.053
175. Global atmospheric emission inventory of polycyclic aromatic hydrocarbons (PAHs) for 2004 Y. Zhang & S. Tao https://doi.org/10.1016/j.atmosenv.2008.10.050
176. Utilizing the Available Open-Source Remotely Sensed Data in Assessing the Wildfire Ignition and Spread Capacities of Vegetated Surfaces in Romania A. Hysa et al. https://doi.org/10.3390/rs13142737
177. Decadal trend and interannual variation of outflow of aerosols from East Asia: Roles of variations in meteorological parameters and emissions Y. Yang et al. https://doi.org/10.1016/j.atmosenv.2014.11.004
178. Hierarchical space-time models for fire ignition and percentage of land burned by wildfires M. Amaral-Turkman et al. https://doi.org/10.1007/s10651-010-0153-9
179. Characterization of pollutants emitted during burning of eight main tree species in subtropical China X. Yang et al. https://doi.org/10.1016/j.atmosenv.2019.116899
180. MODIS-Derived Fire Characteristics and Greenhouse Gas Emissions from Cropland Residue Burning in Central India T. Ray et al. https://doi.org/10.3390/su142416612
181. The short-term effectiveness of surfactant seed coating and mulching treatment in reducing post-fire runoff and erosion M. Hosseini et al. https://doi.org/10.1016/j.geoderma.2017.08.008
182. Pyrogenic HONO seen from space: insights from global IASI observations B. Franco et al. https://doi.org/10.5194/acp-24-4973-2024
183. Vegetation fire emissions and their impact on air pollution and climate B. Langmann et al. https://doi.org/10.1016/j.atmosenv.2008.09.047
184. IASI-derived NH3 enhancement ratios relative to CO for the tropical biomass burning regions S. Whitburn et al. https://doi.org/10.5194/acp-17-12239-2017
185. Nitrogen alters carbon dynamics during early succession in boreal forest S. Allison et al. https://doi.org/10.1016/j.soilbio.2010.03.026
186. Long-term trends and interannual variability of forest, savanna and agricultural fires in South America Y. Chen et al. https://doi.org/10.4155/cmt.13.61
187. Constraining black carbon aerosol over Asia using OMI aerosol absorption optical depth and the adjoint of GEOS-Chem L. Zhang et al. https://doi.org/10.5194/acp-15-10281-2015
188. Fire risk assessment, spatiotemporal clustering and hotspot analysis in the Luki biosphere reserve region, western DR Congo N. Cizungu et al. https://doi.org/10.1016/j.tfp.2021.100104
189. Radiative effects of absorbing aerosols over northeastern India: Observations and model simulations M. Gogoi et al. https://doi.org/10.1002/2016JD025592
190. Do biomass burning aerosols intensify drought in equatorial Asia during El Niño? M. Tosca et al. https://doi.org/10.5194/acp-10-3515-2010
191. Semi-automated mapping of burned areas in semi-arid ecosystems using MODIS time-series imagery L. Hardtke et al. https://doi.org/10.1016/j.jag.2014.11.011
192. Temporal comparison of global inventories of CO2 emissions from biomass burning during 2002–2011 derived from remotely sensed data Y. Shi & T. Matsunaga https://doi.org/10.1007/s11356-017-9141-z
193. Wildfire particulate matter in Europe during summer 2003: meso-scale modeling of smoke emissions, transport and radiative effects A. Hodzic et al. https://doi.org/10.5194/acp-7-4043-2007
194. Major advances in geostationary fire radiative power (FRP) retrieval over Asia and Australia stemming from use of Himarawi-8 AHI W. Xu et al. https://doi.org/10.1016/j.rse.2017.02.024
195. Carbon Emissions during Wildland Fire on a North American Temperate Peatland R. Mickler et al. https://doi.org/10.4996/fireecology.1301034
196. MODIS derived fire characteristics and aerosol optical depth variations during the agricultural residue burning season, north India K. Vadrevu et al. https://doi.org/10.1016/j.envpol.2011.03.001
197. Assessment of fire emission inventories during the South American Biomass Burning Analysis (SAMBBA) experiment G. Pereira et al. https://doi.org/10.5194/acp-16-6961-2016
198. Impact of Soil Reflectance Variation Correction on Woody Cover Estimation in Kruger National Park Using MODIS Data S. Ibrahim et al. https://doi.org/10.3390/rs11080898
199. Evaluation of black carbon estimations in global aerosol models D. Koch et al. https://doi.org/10.5194/acp-9-9001-2009
200. How Well Does the ‘Small Fire Boost’ Methodology Used within the GFED4.1s Fire Emissions Database Represent the Timing, Location and Magnitude of Agricultural Burning? T. Zhang et al. https://doi.org/10.3390/rs10060823
201. Forest fire estimation and risk prediction using multispectral satellite images: Case study N. Talukdar et al. https://doi.org/10.1016/j.nhres.2024.01.007
202. Managing the human component of fire regimes: lessons from Africa S. Archibald https://doi.org/10.1098/rstb.2015.0346
203. Influence of Droughts on Mid-Tropospheric CO2 X. Jiang et al. https://doi.org/10.3390/rs9080852
204. Building a machine learning surrogate model for wildfire activities within a global Earth system model Q. Zhu et al. https://doi.org/10.5194/gmd-15-1899-2022
205. The Global Forest Fire Emissions Prediction System version 1.0 K. Anderson et al. https://doi.org/10.5194/gmd-17-7713-2024
206. Reconciling the disagreement between observed and simulated temperature responses to deforestation L. Chen & P. Dirmeyer https://doi.org/10.1038/s41467-019-14017-0
207. Fires of differing intensities rapidly select distinct soil fungal communities in a Northwest US ponderosa pine forest ecosystem C. Reazin et al. https://doi.org/10.1016/j.foreco.2016.07.002
208. Interactions among bioenergy feedstock choices, landscape dynamics, and land use V. Dale et al. https://doi.org/10.1890/09-0501.1
209. Unusual late-fall wildfire in a pre-Alpine Fagus sylvatica forest reduced fine roots in the shallower soil layer and shifted very fine-root growth to deeper soil depth A. Montagnoli et al. https://doi.org/10.1038/s41598-023-33580-7
210. Effects of Siberian forest fires on air quality in East Asia during May 2003 and its climate implication J. Jeong et al. https://doi.org/10.1016/j.atmosenv.2008.08.037
211. Sensitivity of biomass burning emissions estimates to land surface information M. Saito et al. https://doi.org/10.5194/bg-19-2059-2022
212. Is global burned area declining due to cropland expansion? How much do we know based on remotely sensed data? M. Zubkova et al. https://doi.org/10.1080/01431161.2023.2174389
213. Analysis of CO in the tropical troposphere using Aura satellite data and the GEOS-Chem model: insights into transport characteristics of the GEOS meteorological products J. Logan et al. https://doi.org/10.5194/acp-10-12207-2010
214. What the past can say about the present and future of fire J. Marlon https://doi.org/10.1017/qua.2020.48
215. Spatiotemporal PAH patterns in size-fractionated particles (PM_>10-PM_0.1) from Northern Thailand biomass burning via Sentinel-2 P. Paluang et al. https://doi.org/10.20517/jeea.2025.88
216. Theoretical uncertainties for global satellite-derived burned area estimates J. Brennan et al. https://doi.org/10.5194/bg-16-3147-2019
217. Tree Diversity Drives Forest Stand Resistance to Natural Disturbances H. Jactel et al. https://doi.org/10.1007/s40725-017-0064-1
218. A new transport mechanism of biomass burning from Indochina as identified by modeling studies C. Lin et al. https://doi.org/10.5194/acp-9-7901-2009
219. Sources and implications of bias and uncertainty in a century of US wildfire activity data K. Short https://doi.org/10.1071/WF14190
220. Forest fire risk mapping using GIS and remote sensing in two major landscapes of Nepal A. Parajuli et al. https://doi.org/10.1080/19475705.2020.1853251
221. The Impact of Uncertainties in African Biomass Burning Emission Estimates on Modeling Global Air Quality, Long Range Transport and Tropospheric Chemical Lifetimes J. Williams et al. https://doi.org/10.3390/atmos3010132
222. Characterization of Saharan dust, marine aerosols and mixtures of biomass-burning aerosols and dust by means of multi-wavelength depolarization and Raman lidar measurements during SAMUM 2 S. Groß et al. https://doi.org/10.1111/j.1600-0889.2011.00556.x
223. Preliminary analysis of the development of the Carbon Tracker system in Latin America and the Caribbean Y. Woon Jang et al. https://doi.org/10.1016/S0187-6236(14)71101-4
224. Detection and mapping of burnt areas from time series of MODIS-derived NDVI data in a Mediterranean region M. García et al. https://doi.org/10.2478/s13533-012-0167-y
225. Black carbon dynamics over the Northern Indian Ocean: Variability, emission sources, transport and future projections S. Singh & S. Tiwari https://doi.org/10.1016/j.gsf.2026.102263
226. Agricultural intensification increases deforestation fire activity in Amazonia D. MORTON et al. https://doi.org/10.1111/j.1365-2486.2008.01652.x
227. Tropical biomass burning smoke plume size, shape, reflectance, and age based on 2001–2009 MISR imagery of Borneo C. Zender et al. https://doi.org/10.5194/acp-12-3437-2012
228. Mapping Forest Fire Risk—A Case Study in Galicia (Spain) A. Novo et al. https://doi.org/10.3390/rs12223705
229. Research Progress on the Effects of Logging and Burning on Forest Soil Microorganisms 宏. 高 https://doi.org/10.12677/IJE.2021.104053
230. Automated classification of heat sources detected using SWIR remote sensing S. Kato et al. https://doi.org/10.1016/j.jag.2021.102491
231. Pattern validation for MODIS image mining of burned area objects C. Quintano et al. https://doi.org/10.1080/01431160903154358
232. Spatial and Temporal Distribution of Biomass Open Burning Emissions in the Greater Mekong Subregion A. Junpen et al. https://doi.org/10.3390/cli8080090
233. Atmospheric deposition—Another source of nutrients enhancing primary productivity in the eastern tropical Indian Ocean during positive Indian Ocean Dipole phases E. Siswanto https://doi.org/10.1002/2015GL064188
234. Changes in Soil Fungal Communities, Extracellular Enzyme Activities, and Litter Decomposition Across a Fire Chronosequence in Alaskan Boreal Forests S. Holden et al. https://doi.org/10.1007/s10021-012-9594-3
235. Strong winds drive grassland fires in China Z. Wang et al. https://doi.org/10.1088/1748-9326/aca921
236. Emission factors for open and domestic biomass burning for use in atmospheric models S. Akagi et al. https://doi.org/10.5194/acp-11-4039-2011
237. Wildland fire emissions, carbon, and climate: Wildland fire detection and burned area in the United States W. Hao & N. Larkin https://doi.org/10.1016/j.foreco.2013.09.029
238. Burning issues: statistical analyses of global fire data to inform assessments of environmental change M. Krawchuk & M. Moritz https://doi.org/10.1002/env.2287
239. Contributions of wildland fire to terrestrial ecosystem carbon dynamics in North America from 1990 to 2012 G. Chen et al. https://doi.org/10.1002/2016GB005548
240. Strengths and weaknesses of MODIS hotspots to characterize global fire occurrence S. Hantson et al. https://doi.org/10.1016/j.rse.2012.12.004
241. Annual and Seasonal Patterns of Burned Area Products in Arctic-Boreal North America and Russia for 2001–2020 A. Clelland et al. https://doi.org/10.3390/rs16173306
242. The occurrence and levels of polycyclic aromatic hydrocarbons (PAHs) in African environments—a systematic review S. Ofori et al. https://doi.org/10.1007/s11356-020-09428-2
243. Mapping the research history, collaborations and trends of remote sensing in fire ecology M. de Santana et al. https://doi.org/10.1007/s11192-020-03805-x
244. Modeling Litter Stocks in Planted Forests of Northern Mexico F. Rodríguez-Flores et al. https://doi.org/10.3390/f13071049
245. Improved estimation of fire particulate emissions using a combination of VIIRS and AHI data for Indonesia during 2015–2020 X. Lu et al. https://doi.org/10.1016/j.rse.2022.113238
246. Effects of biomass burning on climate, accounting for heat and moisture fluxes, black and brown carbon, and cloud absorption effects M. Jacobson https://doi.org/10.1002/2014JD021861
247. Fuel-Specific Aggregation of Active Fire Detections for Rapid Mapping of Forest Fire Perimeters in Mexico C. Briones-Herrera et al. https://doi.org/10.3390/f13010124
248. Seasonal and interannual variations in CO and BC emissions from open biomass burning in Southern Africa during 1998–2005 A. Ito et al. https://doi.org/10.1029/2006GB002848
249. Multi-year MODIS active fire type classification over the Brazilian Tropical Moist Forest Biome D. Roy & S. Kumar https://doi.org/10.1080/17538947.2016.1208686
250. Sensitivity of the air–sea CO2 exchange in the Baltic Sea and Danish inner waters to atmospheric short-term variability A. Lansø et al. https://doi.org/10.5194/bg-12-2753-2015
251. Disturbance and the carbon balance of US forests: A quantitative review of impacts from harvests, fires, insects, and droughts C. Williams et al. https://doi.org/10.1016/j.gloplacha.2016.06.002
252. Fire regimes of China: inference from statistical comparison with the United States M. Krawchuk & M. Moritz https://doi.org/10.1111/j.1466-8238.2009.00472.x
253. The collection 5 MODIS burned area product — Global evaluation by comparison with the MODIS active fire product D. Roy et al. https://doi.org/10.1016/j.rse.2008.05.013
254. Variability and recent trends in the African terrestrial carbon balance P. Ciais et al. https://doi.org/10.5194/bg-6-1935-2009
255. Estimates of black carbon emissions in the western United States using the GEOS-Chem adjoint model Y. Mao et al. https://doi.org/10.5194/acp-15-7685-2015
256. Optimization of Multi-Ecosystem Model Ensembles to Simulate Vegetation Growth at the Global Scale L. Tang et al. https://doi.org/10.1109/TGRS.2020.2993641
257. Satellite-based automated burned area detection: A performance assessment of the MODIS MCD45A1 in the Brazilian savanna F. Araújo & L. Ferreira https://doi.org/10.1016/j.jag.2014.10.009
258. Emissions from biomass burning in the Yucatan R. Yokelson et al. https://doi.org/10.5194/acp-9-5785-2009
259. CO2 annual and semiannual cycles from multiple satellite retrievals and models X. Jiang et al. https://doi.org/10.1002/2014EA000045
260. Serotiny in the South African shrub Protea repens is associated with gradients of precipitation, temperature, and fire intensity R. de Gouvenain et al. https://doi.org/10.1007/s11258-018-00905-w
261. Assessing VIIRS capabilities to improve burned area mapping over the Brazilian Cerrado F. Santos et al. https://doi.org/10.1080/01431161.2020.1771791
262. Deep cognitive imaging systems enable estimation of continental-scale fire incidence from climate data R. Dutta et al. https://doi.org/10.1038/srep03188
263. Resilience, remoteness and war shape the land cover dynamics in one of the world's largest miombo woodlands C. Andrews et al. https://doi.org/10.1016/j.tfp.2024.100623
264. A deep learning approach for mapping and dating burned areas using temporal sequences of satellite images M. Pinto et al. https://doi.org/10.1016/j.isprsjprs.2019.12.014
265. A spatio-temporal active-fire clustering approach for global burned area mapping at 250 m from MODIS data J. Lizundia-Loiola et al. https://doi.org/10.1016/j.rse.2019.111493
266. Evaluation of satellite-derived burned area products for the fynbos, a Mediterranean shrubland H. de Klerk et al. https://doi.org/10.1071/WF11002
267. Regime de queima em Goiás, Brasil, e em Moçambique entre 2010 e 2019: frequência, recorrência e classes de cobertura mais afetadas S. Santos et al. https://doi.org/10.5327/Z2176-94781303
268. Estimated Global Mortality Attributable to Smoke from Landscape Fires F. Johnston et al. https://doi.org/10.1289/ehp.1104422
269. Satellite contributions to the quantitative characterization of biomass burning for climate modeling C. Ichoku et al. https://doi.org/10.1016/j.atmosres.2012.03.007
270. Integration of remote sensing data and surface observations to estimate the impact of the Russian wildfires over Europe and Asia during August 2010 L. Mei et al. https://doi.org/10.5194/bg-8-3771-2011
271. Late Quaternary variations in tree cover at the northern forest-tundra ecotone J. Williams et al. https://doi.org/10.1029/2010JG001458
272. WRF-Chem model estimates of equatorial Atlantic Ocean tropospheric ozone increases via June 2006 African biomass burning ozone precursor transport J. Smith et al. https://doi.org/10.1007/s10874-014-9293-x
273. Comparison of L3JRC and MODIS global burned area products from 2000 to 2007 D. Chang & Y. Song https://doi.org/10.1029/2008JD011361
274. Mapping burn severity and burning efficiency in California using simulation models and Landsat imagery A. De Santis et al. https://doi.org/10.1016/j.rse.2010.02.008
275. The impact of monthly variation of the Pacific–North America (PNA) teleconnection pattern on wintertime surface-layer aerosol concentrations in the United States J. Feng et al. https://doi.org/10.5194/acp-16-4927-2016
276. CarbonTracker-CH4: an assimilation system for estimating emissions of atmospheric methane L. Bruhwiler et al. https://doi.org/10.5194/acp-14-8269-2014
277. A stratified random sampling design in space and time for regional to global scale burned area product validation L. Boschetti et al. https://doi.org/10.1016/j.rse.2016.09.016
278. Fire carbon emissions over Equatorial Asia reduced by shortened dry seasons S. Wang et al. https://doi.org/10.1038/s41612-023-00455-7
279. Remote‐sensing constraints on South America fire traits by Bayesian fusion of atmospheric and surface data A. Bloom et al. https://doi.org/10.1002/2014GL062584
280. Trans-Pacific transport and evolution of aerosols: spatiotemporal characteristics and source contributions Z. Hu et al. https://doi.org/10.5194/acp-19-12709-2019
281. Analysis fire patterns and drivers with a global SEVER-FIRE v1.0 model incorporated into dynamic global vegetation model and satellite and on-ground observations S. Venevsky et al. https://doi.org/10.5194/gmd-12-89-2019
282. Fire alters soil bacterial and fungal communities and intensifies seasonal variation in subtropical forest ecosystem Z. Shi et al. https://doi.org/10.1016/j.ejsobi.2024.103677
283. Division of the tropical savanna fire season into early and late dry season burning using MODIS active fires T. Eames et al. https://doi.org/10.1016/j.jag.2023.103575
284. An attribution of the low single-scattering albedo of biomass burning aerosol over the southeastern Atlantic A. Dobracki et al. https://doi.org/10.5194/acp-23-4775-2023
285. Global characterization of biomass-burning patterns using satellite measurements of fire radiative energy C. Ichoku et al. https://doi.org/10.1016/j.rse.2008.02.009
286. Global forest area disturbance from fire, insect pests, diseases and severe weather events P. van Lierop et al. https://doi.org/10.1016/j.foreco.2015.06.010
287. A Revised Historical Fire Regime Analysis in Tunisia (1985–2010) from a Critical Analysis of the National Fire Database and Remote Sensing C. Belhadj-Khedher et al. https://doi.org/10.3390/f9020059
288. How much global burned area can be forecast on seasonal time scales using sea surface temperatures? Y. Chen et al. https://doi.org/10.1088/1748-9326/11/4/045001
289. Detection of Fire Smoke Plumes Based on Aerosol Scattering Using VIIRS Data over Global Fire-Prone Regions X. Lu et al. https://doi.org/10.3390/rs13020196
290. The European carbon balance. Part 3: forests S. LUYSSAERT et al. https://doi.org/10.1111/j.1365-2486.2009.02056.x
291. Wildfires in Russia in 2000–2008: estimates of burnt areas using the satellite MODIS MCD45 data A. Vivchar https://doi.org/10.1080/01431161.2010.499138
292. Down to Earth: Contextualizing the Anthropocene F. Biermann et al. https://doi.org/10.1016/j.gloenvcha.2015.11.004
293. Geographic and seasonal distributions of CO transport pathways and their roles in determining CO centers in the upper troposphere L. Huang et al. https://doi.org/10.5194/acp-12-4683-2012
294. Análisis de la frecuencia de focos de calor en el noroeste de la provincia del Chaco entre 2001-2021 J. Insaurralde et al. https://doi.org/10.15446/rcdg.v34n2.101639
295. New GOES imager algorithms for cloud and active fire detection and fire radiative power assessment across North, South and Central America W. Xu et al. https://doi.org/10.1016/j.rse.2010.03.012
296. Combustion Completeness and Sample Location Determine Wildfire Ash Leachate Chemistry M. Campbell et al. https://doi.org/10.1029/2024GC011470
297. An active-fire based burned area mapping algorithm for the MODIS sensor L. Giglio et al. https://doi.org/10.1016/j.rse.2008.10.006
298. Disentangling the contribution of multiple land covers to fire‐mediated carbon emissions in Amazonia during the 2010 drought L. Anderson et al. https://doi.org/10.1002/2014GB005008
299. Environmental controls on the distribution of wildfire at multiple spatial scales M. Parisien & M. Moritz https://doi.org/10.1890/07-1289.1
300. Global burned area mapping from ENVISAT-MERIS and MODIS active fire data I. Alonso-Canas & E. Chuvieco https://doi.org/10.1016/j.rse.2015.03.011
301. Upscaling terrestrial carbon dioxide fluxes in Alaska with satellite remote sensing and support vector regression M. Ueyama et al. https://doi.org/10.1002/jgrg.20095
302. The Disaster Risk, Global Change, and Sustainability Nexus P. Peduzzi https://doi.org/10.3390/su11040957
303. Separating agricultural and non-agricultural fire seasonality at regional scales B. Magi et al. https://doi.org/10.5194/bg-9-3003-2012
304. Forest fragmentation and edge influence on fire occurrence and intensity under different management types in Amazon forests D. Armenteras et al. https://doi.org/10.1016/j.biocon.2012.10.026
305. A burned area mapping method for the FY-3D MERSI based on the single-temporal L1 data and multi-temporal daily active fire products T. Shan et al. https://doi.org/10.1080/01431161.2020.1826064
306. Resistance of microbial and soil properties to warming treatment seven years after boreal fire S. Allison et al. https://doi.org/10.1016/j.soilbio.2010.07.011
307. Temporal and spatial variability in biomass burned areas across the USA derived from the GOES fire product X. Zhang & S. Kondragunta https://doi.org/10.1016/j.rse.2008.02.006
308. Influence of future anthropogenic emissions on climate, natural emissions, and air quality M. Jacobson & D. Streets https://doi.org/10.1029/2008JD011476
309. Conservation Threats Due to Human‐Caused Increases in Fire Frequency in Mediterranean‐Climate Ecosystems A. SYPHARD et al. https://doi.org/10.1111/j.1523-1739.2009.01223.x
310. A tropospheric ozone maximum over the equatorial Southern Indian Ocean L. Zhang et al. https://doi.org/10.5194/acp-12-4279-2012
311. Evaluation of tropical and extratropical Southern Hemisphere African aerosol properties simulated by a climate model B. Magi et al. https://doi.org/10.1029/2008JD011128
312. Trends in the sources and sinks of carbon dioxide C. Le Quéré et al. https://doi.org/10.1038/ngeo689
313. Extreme air pollution events in Hokkaido, Japan, traced back to early snowmelt and large-scale wildfires over East Eurasia: Case studies T. Yasunari et al. https://doi.org/10.1038/s41598-018-24335-w
314. Global ammonia emission inversion in 2022 via assimilating IASI observations M. Chen et al. https://doi.org/10.1038/s44407-026-00072-7
315. Evaluation of CMIP6 model performances in simulating fire weather spatiotemporal variability on global and regional scales C. Gallo et al. https://doi.org/10.5194/gmd-16-3103-2023
316. New perspectives on African biomass burning dynamics G. Roberts & M. Wooster https://doi.org/10.1029/2007EO380001
317. Emission factors of some common grass species in West Africa K. Abdulraheem et al. https://doi.org/10.1007/s10661-020-08725-0
318. Algorithms for Detecting Sub‐Pixel Elevated Temperature Features for the NASA Surface Biology and Geology (SBG) Designated Observable A. Shreevastava et al. https://doi.org/10.1029/2022JG007370
319. Terrestrial Vegetation in the Coupled Human-Earth System: Contributions of Remote Sensing R. DeFries https://doi.org/10.1146/annurev.environ.33.020107.113339
320. Global emissions of non-methane hydrocarbons deduced from SCIAMACHY formaldehyde columns through 2003–2006 T. Stavrakou et al. https://doi.org/10.5194/acp-9-3663-2009
321. Experimentally determined traits shape bacterial community composition one and five years following wildfire D. Johnson et al. https://doi.org/10.1038/s41559-023-02135-4
322. Assessing boreal forest fire smoke aerosol impacts on U.S. air quality: A case study using multiple data sets D. Miller et al. https://doi.org/10.1029/2011JD016170
323. Spatiotemporal Characteristics and Attribution of Global Wildfire Burned A. Sun et al. https://doi.org/10.3390/rs18020262
324. Spatial and Temporal Trends of Burnt Area in Angola: Implications for Natural Vegetation and Protected Area Management S. Catarino et al. https://doi.org/10.3390/d12080307
325. Evaluation of spatially explicit emission scenario of land-use change and biomass burning using a process-based biogeochemical model E. Kato et al. https://doi.org/10.1080/1747423X.2011.628705
326. Spatial scale invariance of southern Australian forest fires mirrors the scaling behaviour of fire-driving weather events M. Boer et al. https://doi.org/10.1007/s10980-008-9260-5
327. Satellite-based estimates of ground-level fine particulate matter during extreme events: A case study of the Moscow fires in 2010 A. van Donkelaar et al. https://doi.org/10.1016/j.atmosenv.2011.07.068
328. Assessment of the Forest Fire Risk and Its Indicating Significances in Zhaoqing City Based on Landsat Time-Series Images X. Zhou et al. https://doi.org/10.3390/f14020327
329. Big data integration shows Australian bush-fire frequency is increasing significantly R. Dutta et al. https://doi.org/10.1098/rsos.150241
330. State of Wildfires 2024–2025 D. Kelley et al. https://doi.org/10.5194/essd-17-5377-2025
331. Spring fires in Russia: results from participatory burned area mapping with Sentinel-2 imagery I. Glushkov et al. https://doi.org/10.1088/1748-9326/ac3287
332. Satellite evidence of substantial rain-induced soil emissions of ammonia across the Sahel J. Hickman et al. https://doi.org/10.5194/acp-18-16713-2018
333. CTDAS-Lagrange v1.0: a high-resolution data assimilation system for regional carbon dioxide observations W. He et al. https://doi.org/10.5194/gmd-11-3515-2018
334. Detection, Emission Estimation and Risk Prediction of Forest Fires in China Using Satellite Sensors and Simulation Models in the Past Three Decades—An Overview J. Zhang et al. https://doi.org/10.3390/ijerph8083156
335. Mapping spatial and temporal patterns of Mediterranean wildfires from MODIS N. Levin & A. Heimowitz https://doi.org/10.1016/j.rse.2012.08.003
336. Ten years of global burned area products from spaceborne remote sensing—A review: Analysis of user needs and recommendations for future developments F. Mouillot et al. https://doi.org/10.1016/j.jag.2013.05.014
337. The sensitivity of global climate to the episodicity of fire aerosol emissions S. Clark et al. https://doi.org/10.1002/2015JD024068
338. A quantitative link between CO2 emissions from tropical vegetation fires and the daily tropospheric excess (DTE) of CO2 seen by NOAA‐10 (1987–1991) A. Chédin et al. https://doi.org/10.1029/2007JD008576
339. Trend estimates of AERONET-observed and model-simulated AOTs between 1993 and 2013 J. Yoon et al. https://doi.org/10.1016/j.atmosenv.2015.10.058
340. Spatiotemporal pattern of ENSO-induced modulation on landscape fires over Pacific Rim from 2001 to 2020 F. Li et al. https://doi.org/10.1016/j.accre.2024.11.001
341. Contrasting trends of mass and optical properties of aerosols over the Northern Hemisphere from 1992 to 2011 K. Wang et al. https://doi.org/10.5194/acp-12-9387-2012
342. Modeling the transport and optical properties of smoke plumes from South American biomass burning R. Matichuk et al. https://doi.org/10.1029/2007JD009005
343. Fire risk assessment in the Brazilian Amazon using MODIS imagery and change vector analysis E. Maeda et al. https://doi.org/10.1016/j.apgeog.2010.02.004
344. Biomass burning emission analysis based on MODIS aerosol optical depth and AeroCom multi-model simulations: implications for model constraints and emission inventories M. Petrenko et al. https://doi.org/10.5194/acp-25-1545-2025
345. Fire Detection and Fire Characterization Over Africa Using Meteosat SEVIRI G. Roberts & M. Wooster https://doi.org/10.1109/TGRS.2008.915751
346. Comparison of burnt area estimates derived from satellite products and national statistics in Europe L. Loepfe et al. https://doi.org/10.1080/01431161.2011.631950
347. Does the POA–SOA split matter for global CCN formation? W. Trivitayanurak & P. Adams https://doi.org/10.5194/acp-14-995-2014
348. Emissions of air pollutants by Canadian wildfires from 2000 to 2004 D. Lavoué & B. Stocks https://doi.org/10.1071/WF08114
349. Ammonia emissions in tropical biomass burning regions: Comparison between satellite-derived emissions and bottom-up fire inventories S. Whitburn et al. https://doi.org/10.1016/j.atmosenv.2015.03.015
350. Avoidable damage assessment of forest fires in European countries: an efficient frontier approach E. Gutiérrez & S. Lozano https://doi.org/10.1007/s10342-012-0650-5
351. Evaluating MODIS active fire products in subtropical Yucatán forest D. Cheng et al. https://doi.org/10.1080/2150704X.2012.749360
352. Mega fire emissions in Siberia: potential supply of bioavailable iron from forests to the ocean A. Ito https://doi.org/10.5194/bg-8-1679-2011
353. Global fire emissions estimates during 1997–2016 G. van der Werf et al. https://doi.org/10.5194/essd-9-697-2017
354. A Climatological Satellite Assessment of Absorbing Carbonaceous Aerosols on a Global Scale N. Hatzianastassiou et al. https://doi.org/10.3390/atmos10110671
355. A review of particulate pollution over Himalaya region: Characteristics and salient factors contributing ambient PM pollution M. Hassan et al. https://doi.org/10.1016/j.atmosenv.2022.119472
356. Comparison of global inventories of CO emissions from biomass burning derived from remotely sensed data D. Stroppiana et al. https://doi.org/10.5194/acp-10-12173-2010
357. All-cause, cardiovascular, and respiratory mortality and wildfire-related ozone: a multicountry two-stage time series analysis G. Chen et al. https://doi.org/10.1016/S2542-5196(24)00117-7
358. Direct top‐down estimates of biomass burning CO emissions using TES and MOPITT versus bottom‐up GFED inventory O. Pechony et al. https://doi.org/10.1002/jgrd.50624
359. Applicability of MODIS land cover and Enhanced Vegetation Index (EVI) for the assessment of spatial and temporal changes in strength of vegetation in tropical rainforest region of Borneo H. Vijith & D. Dodge-Wan https://doi.org/10.1016/j.rsase.2020.100311
360. Projected fire weather intensification across the Mediterranean: implications for management and restoration C. Gallo et al. https://doi.org/10.1186/s42408-026-00477-5
361. MODIS Reflectance and Active Fire Data for Burn Mapping in Colombia S. Merino-de-Miguel et al. https://doi.org/10.1175/2010EI344.1
362. Atmospheric CO<sub>2</sub> source and sink patterns over the Indian region S. Fadnavis et al. https://doi.org/10.5194/angeo-34-279-2016
363. PREP-CHEM-SRC – 1.0: a preprocessor of trace gas and aerosol emission fields for regional and global atmospheric chemistry models S. Freitas et al. https://doi.org/10.5194/gmd-4-419-2011
364. Impacts of fire emissions and transport pathways on the interannual variation of CO in the tropical upper troposphere L. Huang et al. https://doi.org/10.5194/acp-14-4087-2014
365. Advances in the estimation of high Spatio-temporal resolution pan-African top-down biomass burning emissions made using geostationary fire radiative power (FRP) and MAIAC aerosol optical depth (AOD) data H. Nguyen & M. Wooster https://doi.org/10.1016/j.rse.2020.111971
366. Measurements necessary for assessing the net ecosystem carbon budget of croplands P. Smith et al. https://doi.org/10.1016/j.agee.2010.04.004
367. Intercomparison of AVHRR PAL and LTDR Version 2 Long-Term Data Sets for Africa From 1982 to 2000 and Its Impact on Mapping Burned Area J. Moreno-Ruiz et al. https://doi.org/10.1109/LGRS.2009.2024436
368. Estimation of Burned Area in the Northeastern Siberian Boreal Forest from a Long-Term Data Record (LTDR) 1982–2015 Time Series J. García-Lázaro et al. https://doi.org/10.3390/rs10060940
369. Regionally adaptable dNBR-based algorithm for burned area mapping from MODIS data T. Loboda et al. https://doi.org/10.1016/j.rse.2007.01.017
370. Global Warming Reshapes European Pyroregions L. Galizia et al. https://doi.org/10.1029/2022EF003182
371. Effect of land-cover change on Africa’s burnt area J. Grégoire et al. https://doi.org/10.1071/WF11142
372. Interannual variability in global biomass burning emissions from 1997 to 2004 G. van der Werf et al. https://doi.org/10.5194/acp-6-3423-2006
373. Global wildfire activity re-visited O. Dube https://doi.org/10.1016/j.gloenvcha.2024.102894
374. A Global Analysis of Wildfire Smoke Injection Heights Derived from Space-Based Multi-Angle Imaging M. Val Martin et al. https://doi.org/10.3390/rs10101609
375. Evaluating Satellite Fire Detection Products and an Ensemble Approach for Estimating Burned Area in the United States A. Marsha & N. Larkin https://doi.org/10.3390/fire5050147
376. Spatiotemporal fire occurrence in Borneo over a period of 10 years A. LANGNER & F. SIEGERT https://doi.org/10.1111/j.1365-2486.2008.01828.x
377. Role of disturbed vegetation in mapping the boreal zone in northern Eurasia A. Hofgaard et al. https://doi.org/10.1111/j.1654-109X.2010.01086.x
378. Annual and diurnal african biomass burning temporal dynamics G. Roberts et al. https://doi.org/10.5194/bg-6-849-2009
379. SCIAMACHY CO over land and oceans: 2003–2007 interannual variability A. Gloudemans et al. https://doi.org/10.5194/acp-9-3799-2009
380. Six global biomass burning emission datasets: intercomparison and application in one global aerosol model X. Pan et al. https://doi.org/10.5194/acp-20-969-2020
381. Dynamics of active fire data and their relationship with fires in the areas of regularized indigenous lands in the Southern Amazon A. Santos et al. https://doi.org/10.1016/j.rsase.2021.100570
382. Optical and Microphysical Properties of the Aerosols during a Rare Event of Biomass-Burning Mixed with Polluted Dust M. Gidarakou et al. https://doi.org/10.3390/atmos15020190
383. Long-term in situ observations of biomass burning aerosol at a high altitude station in Venezuela – sources, impacts and interannual variability T. Hamburger et al. https://doi.org/10.5194/acp-13-9837-2013
384. Top-down estimates of biomass burning emissions of black carbon in the Western United States Y. Mao et al. https://doi.org/10.5194/acp-14-7195-2014
385. Spatiotemporal dynamic of global fires and their effects on land cover and vegetation recovery P. Tian et al. https://doi.org/10.1016/j.gloplacha.2026.105309
386. A satellite‐based assessment of transpacific transport of pollution aerosol H. Yu et al. https://doi.org/10.1029/2007JD009349
387. Simulating smoke transport from wildland fires with a regional-scale air quality model: Sensitivity to spatiotemporal allocation of fire emissions F. Garcia-Menendez et al. https://doi.org/10.1016/j.scitotenv.2014.05.108
388. Validation of active forest fires detected by MSG‐SEVIRI by means of MODIS hot spots and AWiFS images A. Calle et al. https://doi.org/10.1080/01431160701596164
389. The validity and utility of MODIS data for simple estimation of area burned and aerosols emitted by wildfire events S. Henderson et al. https://doi.org/10.1071/WF09027
390. The role of the southern African easterly jet in modifying the southeast Atlantic aerosol and cloud environments A. Adebiyi & P. Zuidema https://doi.org/10.1002/qj.2765
391. Constraints on global fire activity vary across a resource gradient M. Krawchuk & M. Moritz https://doi.org/10.1890/09-1843.1
392. A Review of the Applications of Remote Sensing in Fire Ecology D. Szpakowski & J. Jensen https://doi.org/10.3390/rs11222638
393. Natural Gas Fugitive Emissions Rates Constrained by Global Atmospheric Methane and Ethane S. Schwietzke et al. https://doi.org/10.1021/es501204c
394. Vegetation Fires in the Lubumbashi Charcoal Production Basin (The Democratic Republic of the Congo): Drivers, Extent and Spatiotemporal Dynamics Y. Useni Sikuzani et al. https://doi.org/10.3390/land12122171
395. Spatial and temporal intercomparison of four global burned area products M. Humber et al. https://doi.org/10.1080/17538947.2018.1433727
396. Assessing the performance of MODIS and VIIRS active fire products in the monitoring of wildfires: a case study in Turkey K. Coskuner https://doi.org/10.3832/ifor3754-015
397. Modelling of long-range transport of Southeast Asia biomass-burning aerosols to Taiwan and their radiative forcings over East Asia C. Lin et al. https://doi.org/10.3402/tellusb.v66.23733
398. Assessing variability and long-term trends in burned area by merging multiple satellite fire products L. Giglio et al. https://doi.org/10.5194/bg-7-1171-2010
399. ENSO‐Driven Fires Cause Large Interannual Variability in the Naturally Emitted, Ozone‐Depleting Trace Gas CH3Br M. Nicewonger et al. https://doi.org/10.1029/2021GL094756
400. Modelling burned area in Africa V. Lehsten et al. https://doi.org/10.5194/bg-7-3199-2010
401. Regional fire monitoring and characterization using global NASA MODIS fire products in dry lands of Central Asia T. Loboda et al. https://doi.org/10.1007/s11707-012-0313-3
402. Changes in very fine root respiration and morphology with time since last fire in a boreal forest N. Makita et al. https://doi.org/10.1007/s11104-016-2801-9
403. Where are the ‘bad fires’ in West African savannas? Rethinking burning management through a space–time analysis in Burkina Faso S. Caillault et al. https://doi.org/10.1111/geoj.12074
404. The NASA VIIRS burned area product, global validation, and intercomparison with the NASA MODIS burned area product L. Giglio et al. https://doi.org/10.1016/j.rse.2025.115006
405. Tracking the emission and transport of pollution from wildfires using the IASI CO retrievals: analysis of the summer 2007 Greek fires S. Turquety et al. https://doi.org/10.5194/acp-9-4897-2009
406. Global and Regional Trends and Drivers of Fire Under Climate Change M. Jones et al. https://doi.org/10.1029/2020RG000726
407. Uncertainty-Aware Visualization for Analyzing Heterogeneous Wildfire Detections A. Preston et al. https://doi.org/10.1109/MCG.2019.2918158
408. The early/late fire dichotomy P. Laris et al. https://doi.org/10.1177/0309133316665570
409. Environmental and political implications of underestimated cropland burning in Ukraine J. Hall et al. https://doi.org/10.1088/1748-9326/abfc04
410. Characterizing Vegetation Fire dynamics in Myanmar and South Asian Countries C. Reddy et al. https://doi.org/10.1007/s12524-020-01205-5
411. Estimation of Biomass Burned Areas Using Multiple-Satellite-Observed Active Fires X. Zhang et al. https://doi.org/10.1109/TGRS.2011.2149535
412. Global distribution and seasonality of active fires as observed with the Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) sensors L. Giglio et al. https://doi.org/10.1029/2005JG000142
413. Measurement of inter- and intra-annual variability of landscape fire activity at a continental scale: the Australian case G. Williamson et al. https://doi.org/10.1088/1748-9326/11/3/035003
414. Assessing the impacts of catastrophic 2020 wildfires in the Brazilian Pantanal using MODIS data and Google Earth Engine: A case study in the world’s largest sanctuary for Jaguars L. Parra et al. https://doi.org/10.1007/s12145-023-01080-x
415. Prototyping an artificial neural network for burned area mapping on a regional scale in Mediterranean areas using MODIS images I. Gómez & M. Martín https://doi.org/10.1016/j.jag.2011.05.002
416. An evaluation of empirical and statistically based smoke plume injection height parametrisations used within air quality models J. Wilkins et al. https://doi.org/10.1071/WF20140
417. Regionalizing global climate models A. Pitman et al. https://doi.org/10.1002/joc.2279
418. Mapping Burned Areas in Tropical Forests Using a Novel Machine Learning Framework V. Mithal et al. https://doi.org/10.3390/rs10010069
419. Global fire activity patterns (1996–2006) and climatic influence: an analysis using the World Fire Atlas Y. Le Page et al. https://doi.org/10.5194/acp-8-1911-2008
420. Spaceborne Measurements of Formic and Acetic Acids: A Global View of the Regional Sources B. Franco et al. https://doi.org/10.1029/2019GL086239
421. How emissions uncertainty influences the distribution and radiative impacts of smoke from fires in North America T. Carter et al. https://doi.org/10.5194/acp-20-2073-2020