90 citations as recorded by crossref.

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38. Phenology Patterns Indicate Recovery Trajectories of Ponderosa Pine Forests After High-Severity Fires J. Walker & C. Soulard https://doi.org/10.3390/rs11232782
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41. A remote sensing assessment of oak forest recovery after postfire restoration L. Lopes et al. https://doi.org/10.1007/s10342-024-01667-z
42. Examining post-fire vegetation recovery with Landsat time series analysis in three western North American forest types B. Bright et al. https://doi.org/10.1186/s42408-018-0021-9
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44. Statistical challenges in spatial analysis of plant ecology data A. Gelfand https://doi.org/10.1016/j.spasta.2020.100418
45. Postfire Vegetation Recovery Assessment Through Time Series Reconstruction of Vegetation Index G. Lee & S. Park https://doi.org/10.1109/JSTARS.2026.3687234
46. Recovery of Forest Vegetation in a Burnt Area in the Republic of Korea: A Perspective Based on Sentinel-2 Data Y. Kim et al. https://doi.org/10.3390/app11062570
47. The Signature of Climate in Annual Burned Area in Portugal C. DaCamara https://doi.org/10.3390/cli12090143
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51. A Review of the Applications of Remote Sensing in Fire Ecology D. Szpakowski & J. Jensen https://doi.org/10.3390/rs11222638
52. Long-Term Satellite Detection of Post-Fire Vegetation Trends in Boreal Forests of China K. Yi et al. https://doi.org/10.3390/rs5126938
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54. Burned vegetation recovery trajectory and its driving factors using satellite remote-sensing datasets in the Great Xing’An forest region of Inner Mongolia Q. Zhang et al. https://doi.org/10.1071/WF21167
55. Relationship Between Post-Fire Vegetation Recovery and Soil Temperature in the Mediterranean Forest G. Calderisi et al. https://doi.org/10.3390/fire8030091
56. Resilience to Forest Fires: An Indicator-Based Study in a Tropical Forest of Uttarakhand, India M. Aryalakshmi et al. https://doi.org/10.1109/LGRS.2025.3531961
57. Short-term temporal and spatial analysis for post-fire vegetation regrowth characterization and mapping in a Mediterranean ecosystem using optical and SAR image time-series G. De Luca et al. https://doi.org/10.1080/10106049.2022.2097482
58. Assessing tree crown fire damage integrating linear spectral mixture analysis and supervised machine learning on Sentinel-2 imagery G. De Luca et al. https://doi.org/10.1080/17538947.2023.2243900
59. Automated Extraction of Forest Burn Severity Based on Light and Small UAV Visible Remote Sensing Images J. Ye et al. https://doi.org/10.3390/f13101665
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68. Remote Sensing, natural hazards and the contribution of ESA Sentinels missions D. Poursanidis & N. Chrysoulakis https://doi.org/10.1016/j.rsase.2017.02.001
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