55 citations as recorded by crossref.

1. Generation and analysis of a new global burned area product based on MODIS 250 m reflectance bands and thermal anomalies E. Chuvieco et al. 10.5194/essd-10-2015-2018
2. Spatiotemporal Variations of Microwave Land Surface Emissivity (MLSE) over China Derived from Four-Year Recalibrated Fengyun 3B MWRI Data R. Li et al. 10.1007/s00376-022-1314-0
3. Comparative analysis of CORINE and climate change initiative land cover maps in Europe: Implications for wildfire occurrence estimation at regional and local scales L. Vilar et al. 10.1016/j.jag.2019.01.019
4. Spatiotemporal Variation of the Burned Area and Its Relationship with Climatic Factors in Central Kazakhstan Y. Xu et al. 10.3390/rs13020313
5. Satellite Retrieval of Microwave Land Surface Emissivity under Clear and Cloudy Skies in China Using Observations from AMSR-E and MODIS J. Hu et al. 10.3390/rs13193980
6. Quantifying the drivers and predictability of seasonal changes in African fire Y. Yu et al. 10.1038/s41467-020-16692-w
7. A Deep Learning-Based Approach to Predict Large-Scale Dynamics of Normalized Difference Vegetation Index for the Monitoring of Vegetation Activities and Stresses Using Meteorological Data Y. Sun et al. 10.3390/su15086632
8. Land-Cover Dependent Relationships between Fire and Soil Moisture A. Schaefer & B. Magi 10.3390/fire2040055
9. Definitions and methods to estimate regional land carbon fluxes for the second phase of the REgional Carbon Cycle Assessment and Processes Project (RECCAP-2) P. Ciais et al. 10.5194/gmd-15-1289-2022
10. Global fire modelling and control attributions based on the ensemble machine learning and satellite observations Y. Zhang et al. 10.1016/j.srs.2023.100088
11. Improving the LPJmL4-SPITFIRE vegetation–fire model for South America using satellite data M. Drüke et al. 10.5194/gmd-12-5029-2019
12. Recent global and regional trends in burned area and their compensating environmental controls M. Forkel et al. 10.1088/2515-7620/ab25d2
13. DeepPhenoMem V1.0: deep learning modelling of canopy greenness dynamics accounting for multi-variate meteorological memory effects on vegetation phenology G. Liu et al. 10.5194/gmd-17-6683-2024
14. Technical note: Low meteorological influence found in 2019 Amazonia fires D. Kelley et al. 10.5194/bg-18-787-2021
15. Modelling Human-Fire Interactions: Combining Alternative Perspectives and Approaches A. Ford et al. 10.3389/fenvs.2021.649835
16. Spatial variability in Arctic–boreal fire regimes influenced by environmental and human factors R. Scholten et al. 10.1038/s41561-024-01505-2
17. How contemporary bioclimatic and human controls change global fire regimes D. Kelley et al. 10.1038/s41558-019-0540-7
18. Fire hazard modulation by long-term dynamics in land cover and dominant forest type in eastern and central Europe A. Feurdean et al. 10.5194/bg-17-1213-2020
19. Multi-Temporal Analysis of Forest Fire Probability Using Socio-Economic and Environmental Variables S. Kim et al. 10.3390/rs11010086
20. The interactive global fire module pyrE (v1.0) K. Mezuman et al. 10.5194/gmd-13-3091-2020
21. The global long-term microwave Vegetation Optical Depth Climate Archive (VODCA) L. Moesinger et al. 10.5194/essd-12-177-2020
22. A roadmap for high-resolution satellite soil moisture applications – confronting product characteristics with user requirements J. Peng et al. 10.1016/j.rse.2020.112162
23. VODCA v2: multi-sensor, multi-frequency vegetation optical depth data for long-term canopy dynamics and biomass monitoring R. Zotta et al. 10.5194/essd-16-4573-2024
24. Estimating leaf moisture content at global scale from passive microwave satellite observations of vegetation optical depth M. Forkel et al. 10.5194/hess-27-39-2023
25. A comparison of remotely-sensed and inventory datasets for burned area in Mediterranean Europe M. Turco et al. 10.1016/j.jag.2019.05.020
26. Using soil moisture information to better understand and predict wildfire danger: a review of recent developments and outstanding questions E. Krueger et al. 10.1071/WF22056
27. A carbon sink-driven approach to estimate gross primary production from microwave satellite observations I. Teubner et al. 10.1016/j.rse.2019.04.022
28. A data-driven model for Fennoscandian wildfire danger S. Bakke et al. 10.5194/nhess-23-65-2023
29. Fires prime terrestrial organic carbon for riverine export to the global oceans M. Jones et al. 10.1038/s41467-020-16576-z
30. Reimagine fire science for the anthropocene J. Shuman et al. 10.1093/pnasnexus/pgac115
31. Linking fire and the United Nations Sustainable Development Goals D. Martin 10.1016/j.scitotenv.2018.12.393
32. Dynamic prediction of global monthly burned area with hybrid deep neural networks G. Zhang et al. 10.1002/eap.2610
33. Global environmental controls on wildfire burnt area, size, and intensity O. Haas et al. 10.1088/1748-9326/ac6a69
34. Tropical climate–vegetation–fire relationships: multivariate evaluation of the land surface model JSBACH G. Lasslop et al. 10.5194/bg-15-5969-2018
35. Effect of Socioeconomic Variables in Predicting Global Fire Ignition Occurrence T. Mukunga et al. 10.3390/fire6050197
36. 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
37. A spatio-temporal active-fire clustering approach for global burned area mapping at 250 m from MODIS data J. Lizundia-Loiola et al. 10.1016/j.rse.2019.111493
38. Past Variance and Future Projections of the Environmental Conditions Driving Western U.S. Summertime Wildfire Burn Area S. Brey et al. 10.1029/2020EF001645
39. The global drivers of wildfire O. Haas et al. 10.3389/fenvs.2024.1438262
40. The importance of antecedent vegetation and drought conditions as global drivers of burnt area A. Kuhn-Régnier et al. 10.5194/bg-18-3861-2021
41. A Preliminary Global Automatic Burned-Area Algorithm at Medium Resolution in Google Earth Engine E. Roteta et al. 10.3390/rs13214298
42. Wildfire Danger Prediction and Understanding With Deep Learning S. Kondylatos et al. 10.1029/2022GL099368
43. The Reading Palaeofire Database: an expanded global resource to document changes in fire regimes from sedimentary charcoal records S. Harrison et al. 10.5194/essd-14-1109-2022
44. 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
45. Wildfire Risk Assessment and Zoning by Integrating Maxent and GIS in Hunan Province, China X. Yang et al. 10.3390/f12101299
46. 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
47. Tailoring Seasonal Rainfall Forecasts for Farmer's Communities in the Upper Blue Nile River Basin M. Haider et al. 10.2139/ssrn.4173667
48. Why woody plant modularity through time and space must be integrated in fire research? M. Chiminazzo et al. 10.1093/aobpla/plad029
49. Global rise in forest fire emissions linked to climate change in the extratropics M. Jones et al. 10.1126/science.adl5889
50. Monitoring post-fire recovery of various vegetation biomes using multi-wavelength satellite remote sensing E. Bousquet et al. 10.5194/bg-19-3317-2022
51. 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
52. Thresholds of fire response to moisture and fuel load differ between tropical savannas and grasslands across continents S. Alvarado et al. 10.1111/geb.13034
53. Global and Regional Trends and Drivers of Fire Under Climate Change M. Jones et al. 10.1029/2020RG000726
54. ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions W. Dorigo et al. 10.1016/j.rse.2017.07.001
55. Interacting Effects of Leaf Water Potential and Biomass on Vegetation Optical Depth M. Momen et al. 10.1002/2017JG004145