268 citations as recorded by crossref.

1. Flood Detection with SAR: A Review of Techniques and Datasets D. Amitrano et al. 10.3390/rs16040656
2. Drone-Based Water Level Detection in Flood Disasters H. Rizk et al. 10.3390/ijerph19010237
3. Surface Water Mapping from SAR Images Using Optimal Threshold Selection Method and Reference Water Mask O. Kavats et al. 10.3390/w14244030
4. Sentinel-1-based flood mapping: a fully automated processing chain A. Twele et al. 10.1080/01431161.2016.1192304
5. Near-real-time non-obstructed flood inundation mapping using synthetic aperture radar X. Shen et al. 10.1016/j.rse.2018.11.008
6. Application of Gated Recurrent Unit Neural Network for Flood Extraction from Synthetic Aperture Radar Time Series M. Zhang et al. 10.3390/w15213779
7. A review of low‐cost space‐borne data for flood modelling: topography, flood extent and water level K. Yan et al. 10.1002/hyp.10449
8. Mapping and assessing spatial extent of floods from multitemporal synthetic aperture radar images: a case study on Brahmaputra River in Assam State, India S. Surampudi & K. Yarrakula 10.1007/s11356-019-06849-6
9. A methodology for mapping annual flood extent using multi-temporal Sentinel-1 imagery T. McCormack et al. 10.1016/j.rse.2022.113273
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
13. Automatic procedures analyzing remote sensing data to minimize flood response time: a step towards National flood mapping service V. Sharma et al. 10.1007/s41324-017-0132-4
14. Monitoring Flood Evolution in Vegetated Areas Using COSMO-SkyMed Data: The Tuscany 2009 Case Study L. Pulvirenti et al. 10.1109/JSTARS.2012.2219509
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. The potential of Sentinel-1 imagery for flood event detection: A satellite vs. hydraulic model comparison J. Breznik et al. 10.1016/j.jhydrol.2024.132587
21. Flood mapping under vegetation using single SAR acquisitions S. Grimaldi et al. 10.1016/j.rse.2019.111582
22. Towards developing comparable optical and SAR remote sensing inundation mapping with hydrodynamic modelling C. Ticehurst & F. Karim 10.1080/01431161.2023.2211714
23. 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
24. Flood period estimation using multi-sensor satellite data: Case study on Punjab floods 2023 Y. Bhageerath et al. 10.1007/s12040-024-02499-6
25. 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
26. The International Charter ‘Space and Major Disasters’: DLR’s Contributions to Emergency Response Worldwide S. Martinis et al. 10.1007/s41064-017-0032-1
27. Automatic Open Water Flood Detection from Sentinel-1 Multi-Temporal Imagery I. Hlaváčová et al. 10.3390/w13233392
28. 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
29. Deep Learning-Based Flood Area Extraction for Fully Automated and Persistent Flood Monitoring Using Cloud Computing J. Kim et al. 10.3390/rs14246373
30. Microwave remote sensing of flood inundation G. Schumann & D. Moller 10.1016/j.pce.2015.05.002
31. Enhancing precision of flood estimation in EOS-04 SAR imagery: a statistical approach Y. Bhageerath et al. 10.1080/19475705.2024.2413910
32. 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
33. 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
34. A Method for Automatic and Rapid Mapping of Water Surfaces from Sentinel-1 Imagery F. Bioresita et al. 10.3390/rs10020217
35. Urban Flood Mapping Using SAR Intensity and Interferometric Coherence via Bayesian Network Fusion Y. Li et al. 10.3390/rs11192231
36. Flood Inundation Distribution In Lamongan Regency Using Sentinel-1 SAR Data And Automatic Water-S1 Method L. Azizah et al. 10.1088/1755-1315/1418/1/012052
37. The use of remote sensing to characterise hydromorphological properties of European rivers S. Bizzi et al. 10.1007/s00027-015-0430-7
38. An automatic method for mapping inland surface waterbodies with Radarsat-2 imagery J. Li & S. Wang 10.1080/01431161.2015.1009653
39. 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
40. A fully automated TerraSAR-X based flood service S. Martinis et al. 10.1016/j.isprsjprs.2014.07.014
41. Multi-Index Image Differencing Method (MINDED) for Flood Extent Estimations E. Oliveira et al. 10.3390/rs11111305
42. Use of Sentinel-1 GRD SAR Images to Delineate Flood Extent in Pakistan M. Zhang et al. 10.3390/su12145784
43. On the Exploitation of Remote Sensing Technologies for the Monitoring of Coastal and River Delta Regions Q. Zhao et al. 10.3390/rs14102384
44. Detecting Flooded Areas Using Sentinel-1 SAR Imagery F. Alonso-Sarria et al. 10.3390/rs17081368
45. Mapping and Characterization of Hydrological Dynamics in a Coastal Marsh Using High Temporal Resolution Sentinel-1A Images C. Cazals et al. 10.3390/rs8070570
46. Operational Surface Water Detection and Monitoring Using Radarsat 2 S. Bolanos et al. 10.3390/rs8040285
47. 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
48. A Framework to Assess Remote Sensing Algorithms for Satellite-Based Flood Index Insurance M. Thomas et al. 10.1109/JSTARS.2023.3244098
49. 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
50. 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
51. Flood Forecasting in Large River Basins Using FOSS Tool and HPC U. Dutta et al. 10.3390/w13243484
52. Automatic Extraction of Water Inundation Areas Using Sentinel-1 Data for Large Plain Areas S. Hu et al. 10.3390/rs12020243
53. Snow Avalanche Debris Analysis Using Time Series of Dual-Polarimetric Synthetic Aperture Radar Data S. Schlaffer & M. Schlögl 10.1109/JSTARS.2024.3423403
54. Probabilistic mapping of flood-induced backscatter changes in SAR time series S. Schlaffer et al. 10.1016/j.jag.2016.12.003
55. 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
56. 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
57. Flood Extent Mapping in the Caprivi Floodplain Using Sentinel-1 Time Series T. Bangira et al. 10.1109/JSTARS.2021.3083517
58. A local thresholding approach to flood water delineation using Sentinel-1 SAR imagery J. Liang & D. Liu 10.1016/j.isprsjprs.2019.10.017
59. Where is my attention? An explainable AI exploration in water detection from SAR imagery L. Chen et al. 10.1016/j.jag.2024.103878
60. Flood Mapping With TerraSAR-X in Forested Regions in Estonia K. Voormansik et al. 10.1109/JSTARS.2013.2283340
61. Brief communication: Key papers of 20 years in Natural Hazards and Earth System Sciences A. Gain et al. 10.5194/nhess-22-985-2022
62. 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
63. Flood Monitoring by Integrating Normalized Difference Flood Index and Probability Distribution of Water Bodies F. Xue et al. 10.1109/JSTARS.2022.3176388
64. 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
65. 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
66. Flood Extent Mapping from Time-Series SAR Images Based on Texture Analysis and Data Fusion M. Ouled Sghaier et al. 10.3390/rs10020237
67. 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
68. 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
69. Flood Hazard Mapping Combining Hydrodynamic Modeling and Multi Annual Remote Sensing data L. Giustarini et al. 10.3390/rs71014200
70. 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
71. Operational Flood Detection Using Sentinel-1 SAR Data over Large Areas H. Cao et al. 10.3390/w11040786
72. Inundation Extent Mapping by Synthetic Aperture Radar: A Review X. Shen et al. 10.3390/rs11070879
73. A review of remote sensing applications for water security: Quantity, quality, and extremes I. Chawla et al. 10.1016/j.jhydrol.2020.124826
74. 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
75. Sentetik Açıklıklı Radar verilerinin Taşkın Çalışmalarında Kullanılması: Berdan Ovası Taşkını M. AKGÜL 10.29128/geomatik.378123
76. Inland Surface Waters Quantity Monitored from Remote Sensing J. Cretaux et al. 10.1007/s10712-023-09803-x
77. Progress in operational flood mapping using satellite synthetic aperture radar (SAR) and airborne light detection and ranging (LiDAR) data K. Brown et al. 10.1177/0309133316633570
78. Near-Real-Time Flood Mapping Using Off-the-Shelf Models with SAR Imagery and Deep Learning V. Katiyar et al. 10.3390/rs13122334
79. 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
80. Towards Operational Flood Monitoring in Flanders Using Sentinel-1 L. Landuyt et al. 10.1109/JSTARS.2021.3121992
81. 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
82. A Novel Fully Automated Mapping of the Flood Extent on SAR Images Using a Supervised Classifier A. Benoudjit & R. Guida 10.3390/rs11070779
83. 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
84. Flood monitoring using multi-temporal COSMO-SkyMed data: Image segmentation and signature interpretation L. Pulvirenti et al. 10.1016/j.rse.2010.12.002
85. Observing floods from space: Experience gained from COSMO-SkyMed observations N. Pierdicca et al. 10.1016/j.actaastro.2012.10.034
86. Flood depth estimation by means of high-resolution SAR images and lidar data F. Cian et al. 10.5194/nhess-18-3063-2018
87. 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
88. 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
89. 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
90. RadWet: An Improved and Transferable Mapping of Open Water and Inundated Vegetation Using Sentinel-1 G. Oakes et al. 10.3390/rs15061705
91. 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
92. Fully Convolutional Neural Network for Rapid Flood Segmentation in Synthetic Aperture Radar Imagery E. Nemni et al. 10.3390/rs12162532
93. Flooding Water Depth Estimation With High-Resolution SAR P. Iervolino et al. 10.1109/TGRS.2014.2358501
94. 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
95. Extraction and Classification of Flood-Affected Areas Based on MRF and Deep Learning J. Wang et al. 10.3390/w15071288
96. 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
97. Automatic flood detection using sentinel-1 images on the google earth engine M. Moharrami et al. 10.1007/s10661-021-09037-7
98. Robust algorithm for detecting floodwater in urban areas using synthetic aperture radar images D. Mason et al. 10.1117/1.JRS.12.045011
99. 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
100. 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
101. 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
102. Assimilating SAR-derived water level data into a hydraulic model: a case study L. Giustarini et al. 10.5194/hess-15-2349-2011
103. L-Band Passive Microwave Data from SMOS for River Gauging Observations in Tropical Climates Z. Kugler et al. 10.3390/rs11070835
104. Satellite Imagery-Based Identification of High-Risk Areas of Schistosome Intermediate Snail Hosts Spread after Flood J. Qiu et al. 10.3390/rs14153707
105. Recognition of small water bodies under complex terrain based on SAR and optical image fusion algorithm S. Yang et al. 10.1016/j.scitotenv.2024.174329
106. Mapping Flooded Vegetation Using COSMO-SkyMed: Comparison With Polarimetric and Optical Data Over Rice Fields N. Pierdicca et al. 10.1109/JSTARS.2017.2711960
107. An Automatic Processing Chain for Near Real-Time Mapping of Burned Forest Areas Using Sentinel-2 Data L. Pulvirenti et al. 10.3390/rs12040674
108. Flood Damage Assessment Through Multitemporal COSMO-SkyMed Data and Hydrodynamic Models: The Albania 2010 Case Study L. Pulvirenti et al. 10.1109/JSTARS.2014.2328012
109. A Bayesian Network for Flood Detection Combining SAR Imagery and Ancillary Data A. D'Addabbo et al. 10.1109/TGRS.2016.2520487
110. The accuracy of sequential aerial photography and SAR data for observing urban flood dynamics, a case study of the UK summer 2007 floods G. Schumann et al. 10.1016/j.rse.2011.04.039
111. Deep Learning Ensemble for Flood Probability Analysis F. Sseguya & K. Jun 10.3390/w16213092
112. A Hierarchical Split-Based Approach for Parametric Thresholding of SAR Images: Flood Inundation as a Test Case M. Chini et al. 10.1109/TGRS.2017.2737664
113. River flood mapping in urban areas combining Radarsat-2 data and flood return period data M. Tanguy et al. 10.1016/j.rse.2017.06.042
114. RadWet-L: A Novel Approach for Mapping of Inundation Dynamics of Forested Wetlands Using ALOS-2 PALSAR-2 L-Band Radar Imagery G. Oakes et al. 10.3390/rs16122078
115. The Use of C-Band and X-Band SAR with Machine Learning for Detecting Small-Scale Mining G. Janse van Rensburg & J. Kemp 10.3390/rs14040977
116. Resilience to unusual flooding after 2021 tropical storms in part of mainland Southeast Asia P. Wattanachareekul et al. 10.3389/fevo.2022.1072993
117. Towards high resolution flood monitoring: An integrated methodology using passive microwave brightness temperatures and Sentinel synthetic aperture radar imagery Z. Zeng et al. 10.1016/j.jhydrol.2019.124377
118. Improving Urban Flood Mapping by Merging Synthetic Aperture Radar-Derived Flood Footprints with Flood Hazard Maps D. Mason et al. 10.3390/w13111577
119. Automatic boosted flood mapping from satellite data B. Coltin et al. 10.1080/01431161.2016.1145366
120. Adaptive water delineation algorithms for L- and C-band SAR imagery: a comparative analysis A. Gujrati et al. 10.1007/s12145-024-01417-0
121. Flood inundation modelling: A review of methods, recent advances and uncertainty analysis J. Teng et al. 10.1016/j.envsoft.2017.01.006
122. Unsupervised Rapid Flood Mapping Using Sentinel-1 GRD SAR Images D. Amitrano et al. 10.1109/TGRS.2018.2797536
123. The agricultural impact of the 2015–2016 floods in Ireland as mapped through Sentinel 1 satellite imagery R. O’Hara et al. 10.2478/ijafr-2019-0006
124. Optimized Rule-Based Flood Mapping Technique Using Multitemporal RADARSAT-2 Images in the Tropical Region B. Pradhan et al. 10.1109/JSTARS.2017.2676343
125. Near Real-Time Flood Detection in Urban and Rural Areas Using High-Resolution Synthetic Aperture Radar Images D. Mason et al. 10.1109/TGRS.2011.2178030
126. Evaluation of the Threshold for an Improved Surface Water Extraction Index Using Optical Remote Sensing Data F. Yulianto et al. 10.1155/2022/4894929
127. MMFlood: A Multimodal Dataset for Flood Delineation From Satellite Imagery F. Montello et al. 10.1109/ACCESS.2022.3205419
128. Taşkın Modelleme Yöntemlerinin Gözden Geçirilmesi ve Karşılaştırılması V. DEMİR et al. 10.31590/ejosat.1010220
129. Use of SAR Data for Detecting Floodwater in Urban and Agricultural Areas: The Role of the Interferometric Coherence L. Pulvirenti et al. 10.1109/TGRS.2015.2482001
130. Evaluation of a new 18-year MODIS-derived surface water fraction dataset for constructing Mediterranean wetland open surface water dynamics L. Li et al. 10.1016/j.jhydrol.2020.124956
131. Development of an Automated Tool for Delineation of Flood Footprints from SAR Imagery for Rapid Disaster Response: A Case Study S. Kuntla & P. Manjusree 10.1007/s12524-020-01125-4
132. Extrapolating Satellite-Based Flood Masks by One-Class Classification—A Test Case in Houston F. Brill et al. 10.3390/rs13112042
133. Sentinel-1 InSAR Coherence to Detect Floodwater in Urban Areas: Houston and Hurricane Harvey as A Test Case M. Chini et al. 10.3390/rs11020107
134. A Multi-Sensor Exportable Approach for Automatic Flooded Areas Detection and Monitoring by a Composite Satellite Constellation M. Faruolo et al. 10.1109/TGRS.2012.2236336
135. Location-Aware, Context-Driven QoS for IoT Applications E. Ahmad et al. 10.1109/JSYST.2019.2893913
136. The Use of Sentinel-1 Time-Series Data to Improve Flood Monitoring in Arid Areas S. Martinis et al. 10.3390/rs10040583
137. Breaking Limits of Remote Sensing by Deep Learning From Simulated Data for Flood and Debris-Flow Mapping N. Yokoya et al. 10.1109/TGRS.2020.3035469
138. TanDEM-X Water Indication Mask: Generation and First Evaluation Results A. Wendleder et al. 10.1109/JSTARS.2012.2210999
139. An approach for flood monitoring by the combined use of Landsat 8 optical imagery and COSMO-SkyMed radar imagery X. Tong et al. 10.1016/j.isprsjprs.2017.11.006
140. Flood extent mapping for Namibia using change detection and thresholding with SAR S. Long et al. 10.1088/1748-9326/9/3/035002
141. Automated Extraction of Inundated Areas from Multi-Temporal Dual-Polarization RADARSAT-2 Images of the 2011 Central Thailand Flood P. Nakmuenwai et al. 10.3390/rs9010078
142. Evaluation of Sentinel-1 data for flood mapping in the upstream of Sidi Salem dam (Northern Tunisia) A. Ezzine et al. 10.1007/s12517-018-3505-7
143. Inundation Assessment of the 2019 Typhoon Hagibis in Japan Using Multi-Temporal Sentinel-1 Intensity Images W. Liu et al. 10.3390/rs13040639
144. Multi-Method Tracking of Monsoon Floods Using Sentinel-1 Imagery G. Ruzza et al. 10.3390/w11112289
145. Flood hazard assessment of August 20, 2016 floods in Satna District, Madhya Pradesh, India R. Kumar et al. 10.1016/j.rsase.2018.06.001
146. Utilization of Satellite-based Digital Elevation Model (DEM) for Hydrologic Applications: A Review S. Zaidi et al. 10.1007/s12594-018-1016-5
147. Estimating Ensemble Likelihoods for the Sentinel-1-Based Global Flood Monitoring Product of the Copernicus Emergency Management Service C. Krullikowski et al. 10.1109/JSTARS.2023.3292350
148. Integrated Flood Impact and Vulnerability Assessment Using a Multi-Sensor Earth Observation Mission with the Perspective of an Operational Service in Lombardy, Italy M. Righini et al. 10.3390/land13020140
149. Information Extraction From Remote Sensing Images for Flood Monitoring and Damage Evaluation S. Serpico et al. 10.1109/JPROC.2012.2198030
150. 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. 10.3390/rs12193218
151. Extending general compact querieable representations to GIS applications N. Brisaboa et al. 10.1016/j.ins.2019.08.007
152. Rapid and robust monitoring of flood events using Sentinel-1 and Landsat data on the Google Earth Engine B. DeVries et al. 10.1016/j.rse.2020.111664
153. Probabilistic Flood Mapping Using Synthetic Aperture Radar Data L. Giustarini et al. 10.1109/TGRS.2016.2592951
154. XFIMNet: an Explainable deep learning architecture for versatile flood inundation mapping with synthetic aperture radar and multi-spectral optical images J. Sanderson et al. 10.1080/01431161.2023.2288945
155. A Multi-Scale Flood Monitoring System Based on Fully Automatic MODIS and TerraSAR-X Processing Chains S. Martinis et al. 10.3390/rs5115598
156. Radar and optical mapping of surge persistence and marsh dieback along the New Jersey Mid-Atlantic coast after Hurricane Sandy A. Rangoonwala et al. 10.1080/01431161.2016.1163748
157. Implications of boreal forest stand characteristics for X-band SAR flood mapping accuracy J. Cohen et al. 10.1016/j.rse.2016.08.016
158. Mapping and monitoring of spatio-temporal land use and land cover changes and relationship with normalized satellite indices and driving factors S. Wahla et al. 10.1080/24749508.2023.2187567
159. Level set model for water region segmentation in synthetic aperture radar images W. Lyu et al. 10.1117/1.JRS.13.026510
160. Multi-Temporal Sentinel-1 SAR and Sentinel-2 MSI Data for Flood Mapping and Damage Assessment in Mozambique M. Nhangumbe et al. 10.3390/ijgi12020053
161. Unsupervised Extraction of Flood-Induced Backscatter Changes in SAR Data Using Markov Image Modeling on Irregular Graphs S. Martinis et al. 10.1109/TGRS.2010.2052816
162. A Prototype System for Flood Monitoring Based on Flood Forecast Combined With COSMO-SkyMed and Sentinel-1 Data G. Boni et al. 10.1109/JSTARS.2016.2514402
163. Hydrological/Hydraulic Modeling-Based Thresholding of Multi SAR Remote Sensing Data for Flood Monitoring in Regions of the Vietnamese Lower Mekong River Basin N. Hong Quang et al. 10.3390/w12010071
164. A Collection of SAR Methodologies for Monitoring Wetlands L. White et al. 10.3390/rs70607615
165. The soil moisture data bank: The ground-based, model-based, and satellite-based soil moisture data A. Tavakol et al. 10.1016/j.rsase.2021.100649
166. Estimating the impact of satellite observations on the predictability of large-scale hydraulic models K. Andreadis & G. Schumann 10.1016/j.advwatres.2014.06.006
167. Technical Note: Advances in flash flood monitoring using unmanned aerial vehicles (UAVs) M. Perks et al. 10.5194/hess-20-4005-2016
168. Remote Sensing-Derived Water Extent and Level to Constrain Hydraulic Flood Forecasting Models: Opportunities and Challenges S. Grimaldi et al. 10.1007/s10712-016-9378-y
169. Automatic Detection of Open and Vegetated Water Bodies Using Sentinel 1 to Map African Malaria Vector Mosquito Breeding Habitats A. Hardy et al. 10.3390/rs11050593
170. Automatic near real-time flood detection using Suomi-NPP/VIIRS data S. Li et al. 10.1016/j.rse.2017.09.032
171. Flood Mapping Using Multi-temporal Sentinel-1 SAR Images: A Case Study—Inaouene Watershed from Northeast of Morocco B. Benzougagh et al. 10.1007/s40996-021-00683-y
172. HydroSAR: A Cloud-Based Service for the Monitoring of Inundation Events in the Hindu Kush Himalaya F. Meyer et al. 10.3390/rs16173244
173. Flood Index-Enhanced deep learning model for coastal inundation mapping in SAR imagery W. Chen et al. 10.1016/j.jag.2025.104550
174. Automatic Surface Water Mapping Using Polarimetric SAR Data for Long-Term Change Detection W. Zhang et al. 10.3390/w12030872
175. Flood Mapping and Flood Dynamics of the Mekong Delta: ENVISAT-ASAR-WSM Based Time Series Analyses C. Kuenzer et al. 10.3390/rs5020687
176. Detecting, mapping and analysing of flood water propagation using synthetic aperture radar (SAR) satellite data and GIS: A case study from the Kendrapara District of Orissa State of India M. Rahman & P. Thakur 10.1016/j.ejrs.2017.10.002
177. Automatic near real-time selection of flood water levels from high resolution Synthetic Aperture Radar images for assimilation into hydraulic models: A case study D. Mason et al. 10.1016/j.rse.2012.06.017
178. A New Short-Wave Infrared (SWIR) Method for Quantitative Water Fraction Derivation and Evaluation With EOS/MODIS and Landsat/TM Data S. Li et al. 10.1109/TGRS.2012.2208466
179. A multitemporal index for the automatic identification of winter wheat based on Sentinel-2 imagery time series Y. Xie et al. 10.1080/15481603.2023.2262833
180. Mapping African wetlands for 2020 using multiple spectral, geo-ecological features and Google Earth Engine A. Li et al. 10.1016/j.isprsjprs.2022.09.009
181. Flood detection from multi-temporal SAR data using harmonic analysis and change detection S. Schlaffer et al. 10.1016/j.jag.2014.12.001
182. Towards an automated SAR-based flood monitoring system: Lessons learned from two case studies P. Matgen et al. 10.1016/j.pce.2010.12.009
183. DEM and SAR image based flood feature extraction techniques to map the deep and shallow flood inundated regions of known as well as remote disaster regions . Manavalan & . Rao 10.1080/10106049.2013.838310
184. Change detection in floodable areas of the Danube delta using radar images S. Niculescu et al. 10.1007/s11069-015-1809-4
185. Surface Water Dynamics from Space: A Round Robin Intercomparison of Using Optical and SAR High-Resolution Satellite Observations for Regional Surface Water Detection C. Tottrup et al. 10.3390/rs14102410
186. Detection of Flooded Areas Caused by Typhoon Hagibis by Applying a Learning-Based Method Using Sentinel-1 Data T. Igarashi & H. Wakabayashi 10.1109/JSTARS.2024.3400282
187. Flood Inundation Extraction and its Impact on Ground Subsidence Using Sentinel-1 Data: A Case Study of the “7.20” Rainstorm Event in Henan Province, China Q. Lan et al. 10.1109/JSTARS.2023.3348845
188. Multi-sensoral and automated derivation of inundated areas using TerraSAR-X and ENVISAT ASAR data V. Gstaiger et al. 10.1080/01431161.2012.700421
189. Semi-Automated Monitoring of a Mega-Scale Beach Nourishment Using High-Resolution TerraSAR-X Satellite Data E. Vandebroek et al. 10.3390/rs9070653
190. Assessment of time-series-derived no-flood references for sar-based Bayesian flood mapping M. Tupas et al. 10.1080/15481603.2024.2427304
191. Fast and Automatic Data-Driven Thresholding for Inundation Mapping with Sentinel-2 Data G. Kordelas et al. 10.3390/rs10060910
192. Extraction of Information on the Flooding Extent of Agricultural Land in Henan Province Based on Multi-Source Remote Sensing Images and Google Earth Engine J. Cui et al. 10.3390/agronomy13020355
193. Locating flood embankments using SAR time series: A proof of concept M. Wood et al. 10.1016/j.jag.2018.04.003
194. SAR image analysis techniques for flood area mapping - literature survey R. Manavalan 10.1007/s12145-016-0274-2
195. Performance Study of Landslide Detection Using Multi-Temporal SAR Images Y. Lin et al. 10.3390/rs14102444
196. Automated Processing for Flood Area Detection Using ALOS-2 and Hydrodynamic Simulation Data M. Ohki et al. 10.3390/rs12172709
197. A MODIS-based automated flood monitoring system for southeast asia A. Ahamed & J. Bolten 10.1016/j.jag.2017.05.006
198. Computerized Seed and Range Selection Method for Flood Extent Extraction in SAR Image Using Iterative Region Growing A. Chakraborty & D. Chakraborty 10.1007/s12524-018-0906-8
199. Spatial Evaluation of a Natural Flood Management Project Using SAR Change Detection S. Jarrett & D. Hölbling 10.3390/w15122182
200. Automated Extraction of Surface Water Extent from Sentinel-1 Data W. Huang et al. 10.3390/rs10050797
201. Assessing Single-Polarization and Dual-Polarization TerraSAR-X Data for Surface Water Monitoring K. Irwin et al. 10.3390/rs10060949
202. Mapping of flooded vegetation by means of polarimetric Sentinel-1 and ALOS-2/PALSAR-2 imagery S. Plank et al. 10.1080/01431161.2017.1306143
203. Extraction of Inundation Areas Due to the July 2018 Western Japan Torrential Rain Event Using Multi-Temporal ALOS-2 Images W. Liu et al. 10.20965/jdr.2019.p0445
204. A Hierarchical Spatio-Temporal Markov Model for Improved Flood Mapping Using Multi-Temporal X-Band SAR Data S. Martinis & A. Twele 10.3390/rs2092240
205. Prediction of flash flood susceptibility using integrating analytic hierarchy process (AHP) and frequency ratio (FR) algorithms M. Majeed et al. 10.3389/fenvs.2022.1037547
206. Examining Community Vulnerabilities through multi-scale geospatial analysis of social media activity during Hurricane Irma A. Forati & R. Ghose 10.1016/j.ijdrr.2021.102701
207. GEE4FLOOD: rapid mapping of flood areas using temporal Sentinel-1 SAR images with Google Earth Engine cloud platform V. Vanama et al. 10.1117/1.JRS.14.034505
208. Flood Extent Mapping During Hurricane Florence With Repeat‐Pass L‐Band UAVSAR Images C. Wang et al. 10.1029/2021WR030606
209. Backscatter Analysis Using Multi-Temporal and Multi-Frequency SAR Data in the Context of Flood Mapping at River Saale, Germany S. Martinis & C. Rieke 10.3390/rs70607732
210. Analysis of Environmental and Atmospheric Influences in the Use of SAR and Optical Imagery from Sentinel-1, Landsat-8, and Sentinel-2 in the Operational Monitoring of Reservoir Water Level W. Souza et al. 10.3390/rs14092218
211. A highly automated algorithm for wetland detection using multi-temporal optical satellite data C. Ludwig et al. 10.1016/j.rse.2019.01.017
212. Urban Flood Detection Using TerraSAR-X and SAR Simulated Reflectivity Maps S. Baghermanesh et al. 10.3390/rs14236154
213. Detection and Refinement of Water Bodies Using a Local Thresholding Approach with Feature Extraction from Radar Satellite Images (Case study: Zaribar and Chitgar Lakes) F. Naeimi Asl & M. Akhoondzadeh 10.61186/jgst.14.2.33
214. Mapping Damage-Affected Areas after Natural Hazard Events Using Sentinel-1 Coherence Time Series S. Olen & B. Bookhagen 10.3390/rs10081272
215. “The 20 July 2021 Major Flood Event” in Greater Zhengzhou, China: A Case Study of Flooding Severity and Landscape Characteristics Y. Duan et al. 10.3390/land11111921
216. Mapping the 2021 October Flood Event in the Subsiding Taiyuan Basin by Multitemporal SAR Data H. Feng et al. 10.1109/JSTARS.2022.3204277
217. Object-Based Flood Analysis Using a Graph-Based Representation B. Debusscher & F. Van Coillie 10.3390/rs11161883
218. DEM Extraction in Urban Areas Using High-Resolution TerraSAR-X Imagery U. Sefercik et al. 10.1007/s12524-013-0317-9
219. Fusion of Sentinel-1 data with Sentinel-2 products to overcome non-favourable atmospheric conditions for the delineation of inundation maps I. Manakos et al. 10.1080/22797254.2019.1596757
220. Flood Mapping Based on Synthetic Aperture Radar: An Assessment of Established Approaches L. Landuyt et al. 10.1109/TGRS.2018.2860054
221. Flooded Rice Paddy Detection Using Sentinel-1 and PlanetScope Data: A Case Study of the 2018 Spring Flood in West Java, Indonesia H. Wakabayashi et al. 10.1109/JSTARS.2021.3083610
222. Surface Water Extent Extraction in Prairie Environments Using Sentinel-1 Image-Pair Coherence P. Chen & G. Gunn 10.3390/glacies2020006
223. Water extraction from SAR images based on improved geodesic active contour J. Wan et al. 10.1007/s10661-022-10366-4
224. Monitoring of “7-20” Rainstorm Damage in the Zhengzhou Road Network Using Heterogeneous SAR Images S. Li et al. 10.3390/app13021103
225. Detection of Water Bodies from Kompsat-5 SAR Data S. Park 10.7780/kjrs.2016.32.5.11
226. Weakly Supervised Deep Soft Clustering for Flood Identification in SAR Images F. Ma et al. 10.1109/LGRS.2022.3150778
227. Machine Learning Based Method for Detecting Tsunami Devastated Area Using TerraSAR-X Data H. GOKON et al. 10.2208/kaigan.69.I_1441
228. An active monitoring method for flood events Z. Chen et al. 10.1016/j.cageo.2018.04.009
229. A Change Detection Approach to Flood Mapping in Urban Areas Using TerraSAR-X L. Giustarini et al. 10.1109/TGRS.2012.2210901
230. Flooding extent cartography with Landsat TM imagery and regularized kernel Fisher's discriminant analysis M. Volpi et al. 10.1016/j.cageo.2013.03.009
231. Detection of urban flood inundation using RISAT-1 SAR images: a case study of Srinagar, Jammu and Kashmir (North India) floods of September 2014 C. Bhatt et al. 10.1007/s40808-019-00690-z
232. Towards a global seasonal and permanent reference water product from Sentinel-1/2 data for improved flood mapping S. Martinis et al. 10.1016/j.rse.2022.113077
233. Techniques of Remote Sensing and GIS as Tools for Visualizing Impact of Climate Change-Induced Flood in the Southern African Region Y. Twumasi et al. 10.4236/ajcc.2017.62016
234. Learning from the 2018 Western Japan Heavy Rains to Detect Floods during the 2019 Hagibis Typhoon L. Moya et al. 10.3390/rs12142244
235. Improved integrated framework for flooded crop damage and recovery assessment: A multi-source earth observation and participatory mapping in Hadejia, Nigeria L. Lateef et al. 10.1016/j.jenvman.2025.125542
236. SAR and InSAR for Flood Monitoring: Examples With COSMO-SkyMed Data A. Refice et al. 10.1109/JSTARS.2014.2305165
237. Effectiveness of Sentinel-1 and Sentinel-2 for flood detection assessment in Europe A. Tarpanelli et al. 10.5194/nhess-22-2473-2022
238. Sentinel-1-Based Water and Flood Mapping: Benchmarking Convolutional Neural Networks Against an Operational Rule-Based Processing Chain M. Bereczky et al. 10.1109/JSTARS.2022.3152127
239. Automatic Flood Duration Estimation Based on Multi-Sensor Satellite Data M. Rättich et al. 10.3390/rs12040643
240. Development of algorithms for evaluating performance of flood simulation models with satellite-derived flood T. Surwase et al. 10.2166/h2oj.2020.117
241. An unusually long Rift valley fever inter-epizootic period in Zambia: Evidence for enzootic virus circulation and risk for disease outbreak H. Chambaro et al. 10.1371/journal.pntd.0010420
242. A Physics-Guided Neural Network for Flooding Area Detection Using SAR Imagery and Local River Gauge Observations M. Gierszewska & T. Berezowski 10.1109/JSTARS.2025.3561926
243. Normalized Difference Flood Index for rapid flood mapping: Taking advantage of EO big data F. Cian et al. 10.1016/j.rse.2018.03.006
244. Flood Detection in Gaofen-3 SAR Images via Fully Convolutional Networks W. Kang et al. 10.3390/s18092915
245. An Intercomparison of Sentinel-1 Based Change Detection Algorithms for Flood Mapping M. Tupas et al. 10.3390/rs15051200
246. Identifying floods and flood-affected paddy rice fields in Bangladesh based on Sentinel-1 imagery and Google Earth Engine M. Singha et al. 10.1016/j.isprsjprs.2020.06.011
247. Flood Monitoring Using Satellite-Based RGB Composite Imagery and Refractive Index Retrieval in Visible and Near-Infrared Bands H. Ban et al. 10.3390/rs9040313
248. Enhancement of Detecting Permanent Water and Temporary Water in Flood Disasters by Fusing Sentinel-1 and Sentinel-2 Imagery Using Deep Learning Algorithms: Demonstration of Sen1Floods11 Benchmark Datasets Y. Bai et al. 10.3390/rs13112220
249. Flood Modeling and Prediction Using Earth Observation Data G. Schumann et al. 10.1007/s10712-022-09751-y
250. DAFNE: A Matlab toolbox for Bayesian multi-source remote sensing and ancillary data fusion, with application to flood mapping A. D'Addabbo et al. 10.1016/j.cageo.2017.12.005
251. Comparing four operational SAR-based water and flood detection approaches S. Martinis et al. 10.1080/01431161.2015.1060647
252. Prediction of forest fire susceptibility applying machine and deep learning algorithms for conservation priorities of forest resources S. Saha et al. 10.1016/j.rsase.2022.100917
253. Dataset for Water Body Detection Using Satellite SAR Images S. Lee & H. Oh 10.22761/DJ2021.3.2.002
254. Assessing riverbank erosion in Bangladesh using time series of Sentinel-1 radar imagery in the Google Earth Engine J. Freihardt & O. Frey 10.5194/nhess-23-751-2023
255. Monitoring of an Indonesian Tropical Wetland by Machine Learning-Based Data Fusion of Passive and Active Microwave Sensors H. Mizuochi et al. 10.3390/rs10081235
256. Rapid Assessment of Flood Inundation and Damaged Rice Area in Red River Delta from Sentinel 1A Imagery A. Phan et al. 10.3390/rs11172034
257. A Tool for Pre-Operational Daily Mapping of Floods and Permanent Water Using Sentinel-1 Data L. Pulvirenti et al. 10.3390/rs13071342
258. Time series analysis of automated surface water extraction and thermal pattern variation over the Betwa river, India N. Das et al. 10.1016/j.asr.2021.04.020
259. Increased flooded area and exposure in the White Volta river basin in Western Africa, identified from multi-source remote sensing data C. Li et al. 10.1038/s41598-022-07720-4
260. Leveraging synthetic assimilation of remote sensing with the National Water Model (NWM) to improve above-normal flow prediction in ungauged basins S. Fang et al. 10.1088/1748-9326/ad8808
261. Deep learning methods for flood mapping: a review of existing applications and future research directions R. Bentivoglio et al. 10.5194/hess-26-4345-2022
262. Enhanced flood water depth estimation from Sentinel-1A images A. Nguyen et al. 10.1080/01431161.2023.2268819
263. Potential of Two SAR-Based Flood Mapping Approaches in Supporting an Integrated 1D/2D HEC-RAS Model I. Zotou et al. 10.3390/w14244020
264. Flood Detection in Urban Areas Using TerraSAR-X D. Mason et al. 10.1109/TGRS.2009.2029236
265. A Practical Plateau Lake Extraction Algorithm Combining Novel Statistical Features and Kullback–Leibler Distance Using Synthetic Aperture Radar Imagery X. Zhou et al. 10.1109/JSTARS.2020.3016349
266. Using Sentinel-1A DInSAR interferometry and Landsat 8 data for monitoring water level changes in two lakes in Crete, Greece D. Alexakis et al. 10.1080/10106049.2018.1434685
267. Contributions of Operational Satellites in Monitoring the Catastrophic Floodwaters Due to Hurricane Harvey M. Goldberg et al. 10.3390/rs10081256
268. Infrastructure assessment for disaster management using multi-sensor and multi-temporal remote sensing imagery M. Butenuth et al. 10.1080/01431161.2010.542204