Articles | Volume 17, issue 2
https://doi.org/10.5194/hess-17-651-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-17-651-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Automated global water mapping based on wide-swath orbital synthetic-aperture radar
R. S. Westerhoff
Deltares, Utrecht, The Netherlands
M. P. H. Kleuskens
Deltares, Utrecht, The Netherlands
now at: Alten PTS, Eindhoven, The Netherlands
H. C. Winsemius
Deltares, Utrecht, The Netherlands
H. J. Huizinga
HKV Consultants, Lelystad, The Netherlands
G. R. Brakenridge
University of Colorado, Boulder, Colorado, USA
C. Bishop
Fugro NPA Limited, Edenbridge, UK
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118 citations as recorded by crossref.
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- Dense Time Series Generation of Surface Water Extents through Optical–SAR Sensor Fusion and Gap Filling K. Markert et al. 10.3390/rs16071262
- A Novel Fully Automated Mapping of the Flood Extent on SAR Images Using a Supervised Classifier A. Benoudjit & R. Guida 10.3390/rs11070779
- Development and evaluation of a framework for global flood hazard mapping F. Dottori et al. 10.1016/j.advwatres.2016.05.002
- 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
- Operational Flood Detection Using Sentinel-1 SAR Data over Large Areas H. Cao et al. 10.3390/w11040786
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- Seasonal cycles of lakes on the Tibetan Plateau detected by Sentinel-1 SAR data Y. Zhang et al. 10.1016/j.scitotenv.2019.135563
- Flood Monitoring by Integrating Normalized Difference Flood Index and Probability Distribution of Water Bodies F. Xue et al. 10.1109/JSTARS.2022.3176388
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- A fully automated TerraSAR-X based flood service S. Martinis et al. 10.1016/j.isprsjprs.2014.07.014
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- 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
- 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
- A Pathway to the Automated Global Assessment of Water Level in Reservoirs with Synthetic Aperture Radar (SAR) E. Park et al. 10.3390/rs12081353
- 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
- Object-Based Flood Analysis Using a Graph-Based Representation B. Debusscher & F. Van Coillie 10.3390/rs11161883
- Deriving exclusion maps from C-band SAR time-series in support of floodwater mapping J. Zhao et al. 10.1016/j.rse.2021.112668
- Exploiting the proliferation of current and future satellite observations of rivers G. Schumann & A. Domeneghetti 10.1002/hyp.10825
- 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
- An Intercomparison of Sentinel-1 Based Change Detection Algorithms for Flood Mapping M. Tupas et al. 10.3390/rs15051200
- River Delineation from Remotely Sensed Imagery Using a Multi-Scale Classification Approach K. Yang et al. 10.1109/JSTARS.2014.2309707
- 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
- The Pakistan Flood of August 2022: Causes and Implications J. Nanditha et al. 10.1029/2022EF003230
- Unlocking the full potential of Earth observation during the 2015 Texas flood disaster G. Schumann et al. 10.1002/2015WR018428
- Repeated Hurricanes Reveal Risks and Opportunities for Social-Ecological Resilience to Flooding and Water Quality Problems D. Schaffer-Smith et al. 10.1021/acs.est.9b07815
- Sentinel-1-Imagery-Based High-Resolution Water Cover Detection on Wetlands, Aided by Google Earth Engine A. Gulácsi & F. Kovács 10.3390/rs12101614
- Flood risk assessment in the Kosi megafan using multi-criteria decision analysis: A hydro-geomorphic approach K. Mishra & R. Sinha 10.1016/j.geomorph.2019.106861
- Potential of Two SAR-Based Flood Mapping Approaches in Supporting an Integrated 1D/2D HEC-RAS Model I. Zotou et al. 10.3390/w14244020
- 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
- Improving Sentinel-1 Flood Maps Using a Topographic Index as Prior in Bayesian Inference M. Tupas et al. 10.3390/w15234034
- Surface water maps de-noising and missing-data filling using determinist spatial filters based on several a priori information F. Aires 10.1016/j.rse.2019.111481
- Automatic Features Detection in a Fluvial Environment through Machine Learning Techniques Based on UAVs Multispectral Data E. Pontoglio et al. 10.3390/rs13193983
- A Comparison of Terrain Indices toward Their Ability in Assisting Surface Water Mapping from Sentinel-1 Data C. Huang et al. 10.3390/ijgi6050140
- Inundation Assessment of the 2019 Typhoon Hagibis in Japan Using Multi-Temporal Sentinel-1 Intensity Images W. Liu et al. 10.3390/rs13040639
- Pakistan's 2022 floods: Spatial distribution, causes and future trends from Sentinel-1 SAR observations F. Chen et al. 10.1016/j.rse.2024.114055
- GloFAS – global ensemble streamflow forecasting and flood early warning L. Alfieri et al. 10.5194/hess-17-1161-2013
- Probabilistic Flood Mapping Using Synthetic Aperture Radar Data L. Giustarini et al. 10.1109/TGRS.2016.2592951
- A Decadal Historical Satellite Data and Rainfall Trend Analysis (2001–2016) for Flood Hazard Mapping in Sri Lanka N. Alahacoon et al. 10.3390/rs10030448
- 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
- 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
- Utilising Sentinel-1’s orbital stability for efficient pre-processing of sigma nought backscatter C. Navacchi et al. 10.1016/j.isprsjprs.2022.07.023
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