Flooding Extent Mapping for Synthetic Aperture Radar Time Series Using River Gauge Observations

The flooding extent area in a river valley is related to river gauge observations such as discharge and water elevations. The higher the water elevations, or discharge, the larger the flooding area. Flooding extent maps are often derived from synthetic aperture radar (SAR) images using thresholding methods. The thresholding methods vary in complexity and number of required parameters. We proposed a simple thresholding method that takes advantage of the correlation between the river gauge and the flooding area. To show the applicability of the method, we used a 2014–2018 time series of 161 Sentinel 1 SAR images acquired over a wetland floodplain located in Northeast Poland. We validated the method by extracting local water line elevations from a high-resolution digital elevation model for three river gauges, which resulted in a root-mean-square error of 0.16 m, a bias of 0.07 m, and a correlation of 0.86 for the best scenario. The scenario analysis showed that the most important factor affecting the method's accuracy was a proper delineation of the zone in which the flooding extent area was calculated. This was because other water sources, uncorrelated with river flow, were present in the floodplain as open water. Additionally, higher accuracy was obtained for the VV than VH polarization. The discharge can be used instead of water elevations as a river gauge variable, but this results in more bias in the water extent estimates.

[1]  Giorgio Boni,et al.  Combined use of multi-temporal COSMO-SkyMed data and a hydrodynamic model to monitor flood dynamics , 2014, 2014 IEEE Geoscience and Remote Sensing Symposium.

[2]  S. A. Long,et al.  Flood extent mapping for Namibia using change detection and thresholding with SAR , 2014 .

[3]  Philip Marzahn,et al.  Detection of Temporary Flooded Vegetation Using Sentinel-1 Time Series Data , 2018, Remote. Sens..

[4]  Marco Chini,et al.  Monitoring of Inundation Dynamics in the North-American Prairie Pothole Region using Sentinel-1 Time Series , 2018, IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium.

[5]  D. Roque,et al.  OBIA Flood Delimitation Assisted by Threshold Determination with Principal Component Analysis , 2014 .

[6]  Laurence C. Smith,et al.  Estimation of discharge from braided glacial rivers using ERS 1 synthetic aperture radar: first results , 1995 .

[7]  Hahn Chul Jung,et al.  Mapping spatio-temporal water level variations over the central Congo River using PALSAR ScanSAR and Envisat altimetry data , 2017 .

[8]  F. M. Henderson,et al.  Environmental factors and the detection of open surface water areas with X-band radar imagery , 1995 .

[9]  L. Smith,et al.  Estimation of Discharge From Three Braided Rivers Using Synthetic Aperture Radar Satellite Imagery: Potential Application to Ungaged Basins , 1996 .

[10]  A. Cazenave,et al.  Floodplain water storage in the Negro River basin estimated from microwave remote sensing of inundation area and water levels , 2005 .

[11]  I. J. Davenport,et al.  A near real-time algorithm for flood detection in urban and rural areas using high resolution Synthetic Aperture Radar images , 2011, 2011 2nd International Conference on Space Technology.

[12]  Raffaele Albano,et al.  Multitemporal SAR Data and 2D Hydrodynamic Model Flood Scenario Dynamics Assessment , 2018, ISPRS Int. J. Geo Inf..

[13]  J. V. Soares,et al.  HAND, a new terrain descriptor using SRTM-DEM: Mapping terra-firme rainforest environments in Amazonia , 2008 .

[14]  J. Chormański,et al.  Eco-Hydrological Functioning of the Biebrza Wetlands: Lessons for the Conservation and Restoration of Deteriorated Wetlands , 2006 .

[15]  Bo Zhang,et al.  Operational Flood Detection Using Sentinel-1 SAR Data over Large Areas , 2019, Water.

[16]  N. Otsu.  A threshold selection method from gray level histograms , 1979 .

[17]  Albert J. Kettner,et al.  Near-real-time non-obstructed flood inundation mapping using synthetic aperture radar , 2019, Remote Sensing of Environment.

[18]  Dih Barr,et al.  DIRECT SOLUTIONS FOR NORMAL DEPTH USING THE MANNING EQUATION. , 1986 .

[19]  Jakub Osowicki,et al.  Floodplain inundation Mapping using SAR Scattering Coefficient Thresholding and Observed Discharge Data , 2019, IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium.

[20]  J. Chormański,et al.  Spatiotemporal Dynamics of the Active Perirheic Zone in a Natural Wetland Floodplain , 2019, Water Resources Research.

[21]  Bernard De Baets,et al.  Impact of the timing of a SAR image acquisition on the calibration of a flood inundation model , 2017 .

[22]  J. Chormański,et al.  Skill of remote sensing snow products for distributed runoff prediction , 2015 .

[23]  Philip A. Townsend,et al.  Mapping Seasonal Flooding in Forested Wetlands Using Multi-Temporal Radarsat SAR , 2001 .

[24]  M. Menenti,et al.  Earth observation for water resource management in Africa , 2015 .

[25]  Wetlands in flux: looking for the drivers in a central European case , 2018, Wetlands Ecology and Management.

[26]  P. Manjusree,et al.  Optimization of threshold ranges for rapid flood inundation mapping by evaluating backscatter profiles of high incidence angle SAR images , 2012, International Journal of Disaster Risk Science.

[27]  Simon Plank,et al.  Sentinel-1-based flood mapping: a fully automated processing chain , 2016 .

[28]  Chenghu Zhou,et al.  Flood monitoring using multi-temporal AVHRR and RADARSAT imagery , 2000 .

[29]  Sandro Martinis.  Improving flood mapping in arid areas using SENTINEL-1 time series data , 2017, 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).

[30]  C. Brekke,et al.  X-, C-, and L-band SAR signatures of newly formed sea ice in Arctic leads during winter and spring , 2018 .

[31]  C. Kilsby,et al.  Multi‐temporal synthetic aperture radar flood mapping using change detection , 2018 .

[32]  J. Chormański,et al.  A new look at the Flood Pulse Concept: The (ir)relevance of the moving littoral in temperate zone rivers , 2014 .

[33]  Franz J. Meyer,et al.  Operational Flood Mapping Using Multi-Temporal Sentinel-1 SAR Images: A Case Study from Bangladesh , 2019, Remote. Sens..

[34]  H. You,et al.  Automatic extraction of flood inundation areas from SAR images: a case study of Jilin, China during the 2017 flood disaster , 2019, International Journal of Remote Sensing.

[35]  Waqas Ahmad,et al.  Estimation of flow in various sizes of streams using the Sentinel-1 Synthetic Aperture Radar (SAR) data in Han River Basin, Korea , 2019, Int. J. Appl. Earth Obs. Geoinformation.

[36]  M. N. Sumaiya,et al.  Unsupervised Change Detection of Flood affected areas in SAR images using Rayleigh based Bayesian Thresholding , 2018 .

[37]  K. Rebel,et al.  Flood mapping with remote sensing and hydrochemistry: A new method to distinguish the origin of flood water during floods , 2011 .

[38]  S. Martinis,et al.  Flood Monitoring in Vegetated Areas Using Multitemporal Sentinel-1 Data: Impact of Time Series Features , 2019, Water.

[39]  L. Mertes,et al.  Documentation and significance of the perirheic zone on inundated floodplains , 1997 .

[40]  W. Wagner,et al.  Investigating Radar Time Series for Hydrological Characterisation in the Lower Mekong Basin , 2015 .

[41]  Valentijn R. N. Pauwels,et al.  Remote Sensing-Derived Water Extent and Level to Constrain Hydraulic Flood Forecasting Models: Opportunities and Challenges , 2016, Surveys in Geophysics.

[42]  Paul D. Bates,et al.  Automatic near real-time selection of flood water levels from high resolution Synthetic Aperture Radar images for assimilation into hydraulic models: A case study , 2012 .

[43]  Henrik Madsen,et al.  Simultaneous calibration of multiple hydrodynamic model parameters using satellite altimetry observations of water surface elevation in the Songhua River , 2019, Remote Sensing of Environment.

[44]  Steven M. De Jong,et al.  Locating flood embankments using SAR time series: A proof of concept , 2018, Int. J. Appl. Earth Obs. Geoinformation.