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10. Estimation of Flood Inundation and Depth During Hurricane Florence Using Sentinel-1 and UAVSAR Data S. Kundu et al. 10.1109/LGRS.2022.3165444
11. Assessing Burned Areas in Wildfires and Prescribed Fires with Spectral Indices and SAR Images in the Margalla Hills of Pakistan A. Tariq et al. 10.3390/f12101371
12. OBIA Flood Delimitation Assisted by Threshold Determination with Principal Component Analysis D. Roque et al. 10.14358/PERS.80.6.551-557
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15. Evaluating the impact of flood inundation with the cloud computing platform over vegetation cover of Ganga Basin during COVID-19 S. Ghosh et al. 10.1007/s41324-022-00430-z
16. Flood inundation mapping- Kerala 2018; Harnessing the power of SAR, automatic threshold detection method and Google Earth Engine V. Tiwari et al. 10.1371/journal.pone.0237324
17. Earth observation data based rapid flood-extent modelling for tsunami-devastated coastal areas S. Hese & T. Heyer 10.1016/j.jag.2015.11.005
18. Brief communication: Hurricane Dorian: automated near-real-time mapping of the “unprecedented” flooding in the Bahamas using synthetic aperture radar D. Cerrai et al. 10.5194/nhess-20-1463-2020
19. The last two decades of computer vision technologies in water resource management: A bibliometric analysis U. Iqbal et al. 10.1111/wej.12845
20. Flood mapping under vegetation using single SAR acquisitions S. Grimaldi et al. 10.1016/j.rse.2019.111582
21. Towards developing comparable optical and SAR remote sensing inundation mapping with hydrodynamic modelling C. Ticehurst & F. Karim 10.1080/01431161.2023.2211714
22. A Review of the Internet of Floods: Near Real-Time Detection of a Flood Event and Its Impact S. Van Ackere et al. 10.3390/w11112275
23. A new multi-source remote sensing image sample dataset with high resolution for flood area extraction: GF-FloodNet Y. Zhang et al. 10.1080/17538947.2023.2230978
24. The International Charter ‘Space and Major Disasters’: DLR’s Contributions to Emergency Response Worldwide S. Martinis et al. 10.1007/s41064-017-0032-1
25. Automatic Open Water Flood Detection from Sentinel-1 Multi-Temporal Imagery I. Hlaváčová et al. 10.3390/w13233392
26. Estimation of flood inundation in river basins of Uttar Pradesh using Sentinel 1A-SAR data on Sentinel Application Platform (SNAP) P. Gautam et al. 10.1007/s12517-024-11910-x
27. Deep Learning-Based Flood Area Extraction for Fully Automated and Persistent Flood Monitoring Using Cloud Computing J. Kim et al. 10.3390/rs14246373
28. Microwave remote sensing of flood inundation G. Schumann & D. Moller 10.1016/j.pce.2015.05.002
29. Enhancing precision of flood estimation in EOS-04 SAR imagery: a statistical approach Y. Bhageerath et al. 10.1080/19475705.2024.2413910
30. Flood Monitoring Based on the Study of Sentinel-1 SAR Images: The Ebro River Case Study F. Carreño Conde & M. De Mata Muñoz 10.3390/w11122454
31. Automatic extraction of flood inundation areas from SAR images: a case study of Jilin, China during the 2017 flood disaster L. Wan et al. 10.1080/01431161.2019.1577999
32. A Method for Automatic and Rapid Mapping of Water Surfaces from Sentinel-1 Imagery F. Bioresita et al. 10.3390/rs10020217
33. Urban Flood Mapping Using SAR Intensity and Interferometric Coherence via Bayesian Network Fusion Y. Li et al. 10.3390/rs11192231
34. The use of remote sensing to characterise hydromorphological properties of European rivers S. Bizzi et al. 10.1007/s00027-015-0430-7
35. An automatic method for mapping inland surface waterbodies with Radarsat-2 imagery J. Li & S. Wang 10.1080/01431161.2015.1009653
36. A large-scale 2005–2012 flood map record derived from ENVISAT-ASAR data: United Kingdom as a test case J. Zhao et al. 10.1016/j.rse.2021.112338
37. A fully automated TerraSAR-X based flood service S. Martinis et al. 10.1016/j.isprsjprs.2014.07.014
38. Multi-Index Image Differencing Method (MINDED) for Flood Extent Estimations E. Oliveira et al. 10.3390/rs11111305
39. Use of Sentinel-1 GRD SAR Images to Delineate Flood Extent in Pakistan M. Zhang et al. 10.3390/su12145784
40. On the Exploitation of Remote Sensing Technologies for the Monitoring of Coastal and River Delta Regions Q. Zhao et al. 10.3390/rs14102384
41. Mapping and Characterization of Hydrological Dynamics in a Coastal Marsh Using High Temporal Resolution Sentinel-1A Images C. Cazals et al. 10.3390/rs8070570
42. Operational Surface Water Detection and Monitoring Using Radarsat 2 S. Bolanos et al. 10.3390/rs8040285
43. Tropical Wetland (TropWet) Mapping Tool: The Automatic Detection of Open and Vegetated Waterbodies in Google Earth Engine for Tropical Wetlands A. Hardy et al. 10.3390/rs12071182
44. A Framework to Assess Remote Sensing Algorithms for Satellite-Based Flood Index Insurance M. Thomas et al. 10.1109/JSTARS.2023.3244098
45. Enabling the Use of Earth Observation Data for Integrated Water Resource Management in Africa with the Water Observation and Information System R. Guzinski et al. 10.3390/rs6087819
46. Extracting urban water bodies from high-resolution radar images: Measuring the urban surface morphology to control for radar’s double-bounce effect H. Liao & T. Wen 10.1016/j.jag.2019.102003
47. Flood Forecasting in Large River Basins Using FOSS Tool and HPC U. Dutta et al. 10.3390/w13243484
48. Automatic Extraction of Water Inundation Areas Using Sentinel-1 Data for Large Plain Areas S. Hu et al. 10.3390/rs12020243
49. Snow Avalanche Debris Analysis Using Time Series of Dual-Polarimetric Synthetic Aperture Radar Data S. Schlaffer & M. Schlögl 10.1109/JSTARS.2024.3423403
50. Probabilistic mapping of flood-induced backscatter changes in SAR time series S. Schlaffer et al. 10.1016/j.jag.2016.12.003
51. Extreme rainfall-induced urban flood monitoring and damage assessment in Wuhan (China) and Kumamoto (Japan) cities using Google Earth Engine A. Pandey et al. 10.1007/s10661-022-10076-x
52. Fusion of Sentinel-1 and Sentinel-2 image time series for permanent and temporary surface water mapping F. Bioresita et al. 10.1080/01431161.2019.1624869
53. Flood Extent Mapping in the Caprivi Floodplain Using Sentinel-1 Time Series T. Bangira et al. 10.1109/JSTARS.2021.3083517
54. A local thresholding approach to flood water delineation using Sentinel-1 SAR imagery J. Liang & D. Liu 10.1016/j.isprsjprs.2019.10.017
55. Where is my attention? An explainable AI exploration in water detection from SAR imagery L. Chen et al. 10.1016/j.jag.2024.103878
56. Flood Mapping With TerraSAR-X in Forested Regions in Estonia K. Voormansik et al. 10.1109/JSTARS.2013.2283340
57. Brief communication: Key papers of 20 years in <i>Natural Hazards and Earth System Sciences</i> A. Gain et al. 10.5194/nhess-22-985-2022
58. Integration of SAR and multi-spectral imagery in flood inundation mapping – a case study on Kerala floods 2018 J. Jacinth Jennifer et al. 10.1080/09715010.2020.1791265
59. Flood Monitoring by Integrating Normalized Difference Flood Index and Probability Distribution of Water Bodies F. Xue et al. 10.1109/JSTARS.2022.3176388
60. A novel change detection and threshold-based ensemble of scenarios pyramid for flood extent mapping using Sentinel-1 data E. Pedzisai et al. 10.1016/j.heliyon.2023.e13332
61. A satellite imagery-driven framework for rapid resource allocation in flood scenarios to enhance loss and damage fund effectiveness J. Eudaric et al. 10.1038/s41598-024-69977-1
62. Flood Extent Mapping from Time-Series SAR Images Based on Texture Analysis and Data Fusion M. Ouled Sghaier et al. 10.3390/rs10020237
63. The Synergistic Use of RADARSAT-2 Ascending and Descending Images to Improve Surface Water Detection Accuracy in Alberta, Canada E. DeLancey et al. 10.1080/07038992.2019.1691516
64. Rapid and large-scale mapping of flood inundation via integrating spaceborne synthetic aperture radar imagery with unsupervised deep learning X. Jiang et al. 10.1016/j.isprsjprs.2021.05.019
65. Flood Hazard Mapping Combining Hydrodynamic Modeling and Multi Annual Remote Sensing data L. Giustarini et al. 10.3390/rs71014200
66. Review article: Detection of inundation areas due to the 2015 Kanto and Tohoku torrential rain in Japan based on multi-temporal ALOS-2 imagery W. Liu & F. Yamazaki 10.5194/nhess-18-1905-2018
67. Operational Flood Detection Using Sentinel-1 SAR Data over Large Areas H. Cao et al. 10.3390/w11040786
68. Inundation Extent Mapping by Synthetic Aperture Radar: A Review X. Shen et al. 10.3390/rs11070879
69. A review of remote sensing applications for water security: Quantity, quality, and extremes I. Chawla et al. 10.1016/j.jhydrol.2020.124826
70. Discrimination of Water Surfaces, Heavy Rainfall, and Wet Snow Using COSMO-SkyMed Observations of Severe Weather Events L. Pulvirenti et al. 10.1109/TGRS.2013.2244606
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72. Inland Surface Waters Quantity Monitored from Remote Sensing J. Cretaux et al. 10.1007/s10712-023-09803-x
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75. A Self-Adaptive Thresholding Approach for Automatic Water Extraction Using Sentinel-1 SAR Imagery Based on OTSU Algorithm and Distance Block J. Tan et al. 10.3390/rs15102690
76. Towards Operational Flood Monitoring in Flanders Using Sentinel-1 L. Landuyt et al. 10.1109/JSTARS.2021.3121992
77. Using Sentinel-1 and Google Earth Engine cloud computing for detecting historical flood hazards in tropical urban regions: a case of Dar es Salaam B. Demissie et al. 10.1080/19475705.2023.2202296
78. A Novel Fully Automated Mapping of the Flood Extent on SAR Images Using a Supervised Classifier A. Benoudjit & R. Guida 10.3390/rs11070779
79. Identifying the effect of monsoon floods on vegetation and land surface temperature by using Google Earth Engine S. Rahaman & N. Shermin 10.1016/j.uclim.2022.101162
80. Flood monitoring using multi-temporal COSMO-SkyMed data: Image segmentation and signature interpretation L. Pulvirenti et al. 10.1016/j.rse.2010.12.002
81. Observing floods from space: Experience gained from COSMO-SkyMed observations N. Pierdicca et al. 10.1016/j.actaastro.2012.10.034
82. Flood depth estimation by means of high-resolution SAR images and lidar data F. Cian et al. 10.5194/nhess-18-3063-2018
83. Flood Area Detection Using PALSAR-2 Amplitude and Coherence Data: The Case of the 2015 Heavy Rainfall in Japan M. Ohki et al. 10.1109/JSTARS.2019.2911596
84. Monitoring River Basin Development and Variation in Water Resources in Transboundary Imjin River in North and South Korea Using Remote Sensing D. Kim et al. 10.3390/rs12010195
85. Monitoring surface water dynamics in the Prairie Pothole Region of North Dakota using dual-polarised Sentinel-1 synthetic aperture radar (SAR) time series S. Schlaffer et al. 10.5194/hess-26-841-2022
86. RadWet: An Improved and Transferable Mapping of Open Water and Inundated Vegetation Using Sentinel-1 G. Oakes et al. 10.3390/rs15061705
87. A synergetic use of satellite imagery from SAR and optical sensors to improve coastal flood mapping in the Gulf of Mexico N. Chaouch et al. 10.1002/hyp.8268
88. Fully Convolutional Neural Network for Rapid Flood Segmentation in Synthetic Aperture Radar Imagery E. Nemni et al. 10.3390/rs12162532
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90. Multiscale framework for rapid change analysis from SAR image time series: Case study of flood monitoring in the central coast regions of Vietnam T. Lê et al. 10.1016/j.rse.2021.112837
91. Extraction and Classification of Flood-Affected Areas Based on MRF and Deep Learning J. Wang et al. 10.3390/w15071288
92. Comparison of NLDAS-2 Simulated and NASMD Observed Daily Soil Moisture. Part I: Comparison and Analysis Y. Xia et al. 10.1175/JHM-D-14-0096.1
93. Automatic flood detection using sentinel-1 images on the google earth engine M. Moharrami et al. 10.1007/s10661-021-09037-7
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95. Flood Inundation Probability Estimation by Integrating Physical and Social Sensing Data: Case Study of 2021 Heavy Rainfall in Henan, China W. Du et al. 10.3390/rs16152734
96. Detecting areas affected by flood using multi-temporal ALOS PALSAR remotely sensed data in Karawang, West Java, Indonesia F. Yulianto et al. 10.1007/s11069-015-1633-x
97. Remote Sensing of River Delta Inundation: Exploiting the Potential of Coarse Spatial Resolution, Temporally-Dense MODIS Time Series C. Kuenzer et al. 10.3390/rs70708516
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100. Satellite Imagery-Based Identification of High-Risk Areas of Schistosome Intermediate Snail Hosts Spread after Flood J. Qiu et al. 10.3390/rs14153707
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102. Mapping Flooded Vegetation Using COSMO-SkyMed: Comparison With Polarimetric and Optical Data Over Rice Fields N. Pierdicca et al. 10.1109/JSTARS.2017.2711960
103. An Automatic Processing Chain for Near Real-Time Mapping of Burned Forest Areas Using Sentinel-2 Data L. Pulvirenti et al. 10.3390/rs12040674
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107. Deep Learning Ensemble for Flood Probability Analysis F. Sseguya & K. Jun 10.3390/w16213092
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