Skip to main content

Advertisement

SpringerLink
Log in

Timely Low Resolution SAR Imagery To Support Floodplain Modelling: a Case Study Review

  • Published:
Surveys in Geophysics Aims and scope Submit manuscript

Abstract

It is widely recognised that remote sensing can support flood monitoring, modelling and management. In particular, satellites carrying Synthetic Aperture Radar (SAR) sensors are valuable as radar wavelengths can penetrate cloud cover and are insensitive to daylight. However, given the strong inverse relationship between spatial resolution and revisit time, monitoring floods from space in near real time is currently only possible through low resolution (about 100 m pixel size) SAR imagery. For instance, ENVISAT-ASAR (Advanced Synthetic Aperture Radar) in WSM (wide swath mode) revisit times are of the order of 3 days and the data can be obtained within 24 h at no (or low) cost. Hence, this type of space-borne data can be used for monitoring major floods on medium-to-large rivers. This paper aims to discuss the potential for, and uncertainties of, coarse resolution SAR imagery to monitor floods and support hydraulic modelling. The paper first describes the potential of globally and freely available space-borne data to support flood inundation modelling in near real time. Then, the uncertainty of SAR-derived flood extent maps is discussed and the need to move from deterministic binary maps (wet/dry) of flood extent to uncertain flood inundation maps is highlighted.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  • Abbott MB (1999) Introducing Hydroinformatics. J Hydroinformat 1:3–19

    Google Scholar 

  • Alsdorf DE, Smith LC, Melack JM (2001) Amazon floodplain water level changes measured with interferometric SIR-C radar. IEEE Trans on Geosci Remote Sensing 39(2):423–431

    Article  Google Scholar 

  • Alsdorf DE, Bates PD, Melack J, Wilson MD, Dunne T (2007) The spatial and temporal complexity of the Amazon flood measured from space. Geophys Res Lett 34:L08402

    Article  Google Scholar 

  • Apel H, Aronica GT, Kreibich H, Thieken AH (2009) Flood risk analyses—how detailed do we need to be? Nat Hazards 49(1):79–98

    Article  Google Scholar 

  • Aplin P, Atkinson PM, Tatnall AR, Cutler ME, Sargent I (1999) SAR imagery for flood monitoring and assessment. In Proceedings RSS99 Remote Sensing Society Earth Observation from Data to Information, Cardiff, 557–563

  • Aronica G, Hankin BG, Beven KJ (1998) Uncertainty and equifinality in calibrating distributed roughness coefficients in a flood propagation model with limited data. Adv Water Resour 22(4):349–365

    Article  Google Scholar 

  • Aronica G, Bates PD, Horritt MS (2002) Assessing the uncertainty in distributed model predictions using observed binary pattern information within GLUE. Hydrol Process 16(10):2001–2016

    Article  Google Scholar 

  • Bates PD (2004) Remote sensing and flood inundation modelling. Hydrol Process 18:2593–2597

    Article  Google Scholar 

  • Bates PD, De Roo APJ (2000) A simple raster based model for flood inundation simulation. J Hydrol 236:54–77

    Article  Google Scholar 

  • Bates PD, Horritt MS, Aronica G, Beven KJ (2004) Bayesian updating of flood inundation likelihoods conditioned on flood extent data. Hydrol Process 18:3347–3370

    Article  Google Scholar 

  • Bates PD, Wilson MD, Horritt MS, Mason D, Holden N, Currie C (2006) Reach scale floodplain inundation dynamics observed using airborne synthetic aperture radar imagery: data analysis and modelling. J Hydrol 328:306–318

    Article  Google Scholar 

  • Blyth K (1997) FLOODNET: a telenetwork for acquisition, processing, and dissemination of earth observation data for monitoring and emergency management of floods. Hydrol Process 11:1359–1375

    Article  Google Scholar 

  • Bonnet MP, Barroux G, Martinez JM, Seyler F, Moreira-Turcq P, Cochonneau G, Melack J-M, Boaventura G, Maurice-Bourgoin L, León JG, Roux E, Calmant S, Kosuth P, Guyot JL, Seyler P (2008) Floodplain hydrology in an Amazon floodplain lake (Lago Grande de Curuaí). J Hydrol 349(1–2):18–30

    Article  Google Scholar 

  • Brakenridge GR, Tracy BT, Knox JC (1998) Orbital SAR remote sensing of a river flood wave. Int J Remote Sens 19(7):1439–1445

    Article  Google Scholar 

  • Brandimarte L, Brath A, Castellarin A, Di Baldassarre G (2009) Isla Hispaniola: a trans-boundary flood risk mitigation plan. Phys Chem Earth, Special Issue on Integrated water resources assessment, with special focus on developing countries 34:209–218

  • Castellarin A, Di Baldassarre G, Bates PD, Brath A (2009) Optimal cross-section spacing in Preissmann scheme 1D hydrodynamic models. ASCE J Hydraul Engineer 135(2):96–105

    Article  Google Scholar 

  • Cobby DM, Mason DC, Davenport IJ (2001) Image processing of airborne scanning laser altimetry data for improved river flood modeling. ISPRS J Photogramm Remote Sensing 56(2):121–138

    Article  Google Scholar 

  • Deshmukh KS, Shinde GN (2005) An adaptive color image segmentation. Elect Lett Comp Vision Image Anal 5(4):12–23

    Google Scholar 

  • Di Baldassarre G, Schumann G, Bates PD (2009a) Near real time satellite imagery to support and verify timely flood modelling. Hydrol Process 23:799–803

    Article  Google Scholar 

  • Di Baldassarre G, Schumann G, Bates PD (2009b) A technique for the calibration of hydraulic models using uncertain satellite observations of flood extent. J Hydrol 367:276–282

    Article  Google Scholar 

  • Di Baldassarre G, Montanari A, Lins H, Koutsoyiannis D, Brandimarte L, Blöschl G (2010) Flood fatalities in Africa: from diagnosis to mitigation. Geophys Res Lett 37:L22402. doi:10.1029/2010GL045467

    Article  Google Scholar 

  • Gubbels T, Brakenridge R (2004) Flood disaster hits Hispaniola. Nasa Earth Observatory. http://earthobservatory.nasa.gov/Study/Haiti2004

  • Gupta RP, Banerji S (1985) Monitoring of reservoir volume using LANDSAT data. J Hydrol 77:159–170

    Article  Google Scholar 

  • Henry JB, Chastanet P, Fellah K, Desnos JL Envisat multi-polarized ASAR data for flood mapping, International Journal of Remote Sensing 27(10):1921–1929

  • Horritt MS (2006) A methodology for the validation of uncertain flood inundation models. J Hydrol 326:153–165

    Article  Google Scholar 

  • Horritt MS, Bates PD (2001) Effects of spatial resolution on a raster based model of flood flow. J Hydrol 253:239–249

    Article  Google Scholar 

  • Horritt MS, Bates PD (2002) Evaluation of 1-D and 2-D models for predicting river flood inundation. J Hydrol 268:87–99

    Article  Google Scholar 

  • Horritt MS, Mason D, Luckman AJ (2001) Flood boundary delineation from synthetic aperture radar imagery using a statistical active contour model. Int J Remote Sens 22:2489–2507

    Google Scholar 

  • Horritt MS, Mason DC, Cobby DM, Davenport IJ, Bates PD (2003) Waterline mapping in flooded vegetation from airborne SAR imagery. Remote Sensing of Environ 85(3):271–281

    Article  Google Scholar 

  • Horritt MS, Di Baldassarre G, Bates PD, Brath A (2007) Comparing the performance of 2-D finite element and finite volume models of floodplain inundation using airborne SAR imagery. Hydrol Process 21:2745–2759

    Article  Google Scholar 

  • Hostache R, Matgen P, Schumann G, Puech C, Hoffmann L, Pfister L (2009) Water level estimation and reduction of hydraulic model calibration uncertainties using satellite SAR images of floods. IEEE Trans Geosci Remote Sensing 47:431–441

    Article  Google Scholar 

  • Hunter NM, Bates PD, Horritt MS et al (2007) Simple spatially-distributed models for predicting flood inundation: a review. Geomorphology 90:208–225

    Article  Google Scholar 

  • Irons JR, Petersen GW (1981) Texture transforms of remote sensing data. Remote Sensing Environ 11:359–370

    Article  Google Scholar 

  • Jonkman SN, Vrijling JK (2008) Loss of life due to floods. J Flood Risk Manag 1(1):43–56

    Article  Google Scholar 

  • Kokare M, Chatterji BN, Biswas PK (2003) Comparison of similarity metrics for texture image retrieval. In: Proceedings of the IEEE 10th Conference on Convergent Technologies for Asia-Pacific Region, October 2003, vol. 2. IEEE, Bangalore, India, pp 571–575

    Google Scholar 

  • Kussul N, Shelestov A, Skakun S (2008) Grid system for flood extent extraction from satellite images. Earth Sci Inf 1(3):105–117

    Article  Google Scholar 

  • Lane SN, James TD, Pritchard H, Saunders M (2003) Photogrammetric and laser altimetric reconstruction of water levels for extreme flood event analysis. Photogramm Record 18(104):293–307

    Article  Google Scholar 

  • Mason DC, Davenport IJ, Flather RA, Gurney C, Robinson GJ, Smith JA (2001) A sensitivity analysis of the waterline method of constructing a digital elevation model for intertidal areas in ERS SAR scene of Eastern England. Estuar Coast Shelf Sci 53:759–778

    Article  Google Scholar 

  • Mason DC, Cobby DM, Horritt MS, Bates PD (2003) Floodplain friction parameterization in two-dimensional river flood models using vegetation heights derived from airborne scanning laser altimetry. Hydrol Process 17:1711–1732

    Article  Google Scholar 

  • Mason DC, Bates PD, Dall’Amico JT (2009) Calibration of uncertain flood inundation models using remotely sensed water levels. J Hydrol 368:224–236

    Article  Google Scholar 

  • Mason DC, Speck R, Devereux B, Schumann G, Neal J, Bates PD (2010) Flood detection in urban areas using TerraSAR-X, IEEE. Trans. Geosci Rem. Sens 48(2):882–894

    Article  Google Scholar 

  • Matgen P, Schumann G, Pappenberger F, Pfister L (2007a) Sequential assimilation of remotely sensed water stages in flood inundation models. Remote Sensing for Environmental Monitoring and Change Detection, Proceedings of Symposium HS3007 at IUGG2007, Perugia, July 2007. IAHS Publ 316:78–88

    Google Scholar 

  • Matgen P, Schumann G, Henry JB, Hoffmann L, Pfister L (2007b) Integration of SAR-derived inundation areas, high precision topographic data and a river flow model toward real-time flood management. Int J Appl Earth Observ Geoinformat 9(3):247–263

    Article  Google Scholar 

  • Montanari A, Brath A (2004) A stochastic approach for assessing the uncertainty of rainfall-runoff simulations. Water Resour Res 40:W01106

    Article  Google Scholar 

  • Montanari A, Grossi G, (2008) Estimating the uncertainty of hydrological forecasts: A statistical approach, Water Resources Research 44:W00B08

    Google Scholar 

  • Moussa R, Bocquillon C (1996) Criteria for the choice of flood-routing methods in natural channels. J Hydrol 186:1–30

    Article  Google Scholar 

  • Neal J, Schumann G, Bates PD, Buytaert W, Matgen P, Pappenberger F (2009) A data assimilation approach to discharge from space. Hydrol Processes 23:3641–3649

    Article  Google Scholar 

  • Oberstadler R, Hnsch H, Huth D (1997) Assessment of the mapping capabilities of ERS-1 SAR data for flood mapping: a case study in Germany. Hydrol Process 10:1415–1425

    Article  Google Scholar 

  • Ohl C, Tapsell S (2000) Flooding and human health: the dangers posed are not always obvious. B Med J 321(7270):1167–1168

    Article  Google Scholar 

  • Otsu N (1979) A threshold selection method from gray-level histograms. IEEE trans syst man Cybern 9:62–66

    Article  Google Scholar 

  • Pappenberger F, Matgen P, Beven KJ, Henry JB, Pfister L, de Fraipont P (2006) Influence of uncertain boundary conditions and model structure on flood inundation predictions. Adv Water Resour 29:1430–1449

    Article  Google Scholar 

  • Pappenberger F, Frodsham K, Beven KJ, Romanovicz R, Matgen P (2007) Fuzzy set approach to calibrating distributed flood inundation models using remote sensing observations. Hydrol Earth Syst Sci 11(2):739–752

    Article  Google Scholar 

  • Prestininzi P, Di Baldassarre G, Schumann G, Bates PD (2010) Selecting the appropriate hydraulic model structure using low-resolution satellite imagery. Advances in Water Resources, doi:10.1016/j.advwatres.2010.09.016

  • Raclot D (2006) Remote sensing of water levels on floodplains: a spatial approach guided by hydraulic functioning. Int J Remote Sens 27(12):2553–2574

    Article  Google Scholar 

  • Romanowicz R, Beven K (2003) Estimation of flood inundation probabilities as conditioned on event inundation maps. Water Resour Res 39(3):1073–1085

    Article  Google Scholar 

  • Sali E, Wolfson H (1992) Texture classification in aerial photographs and satellite data. Int J Remote Sens 13:3395–3408

    Article  Google Scholar 

  • Schumann G, Di Baldassarre G (2010) The direct use of radar satellites for event-specific flood risk mapping. Int J Remote Sens 1(2):75–84

    Google Scholar 

  • Schumann G, Hostache R, Puech C, Hoffmann L, Matgen P, Pappenberger F, Pfister L (2007) High-resolution 3D flood information from radar imagery for flood hazard management. IEEE Trans Geosci Remote Sensing 45(6):1715–1725

    Article  Google Scholar 

  • Schumann G, Matgen P, Cutler MEJ, Black A, Hoffmann L, Pfister L (2008) Comparison of remotely sensed water stages from LiDAR, topographic contours and SRTM. ISPRS J Photogramm Remote Sensing 63:283–296

    Article  Google Scholar 

  • Schumann G, Di Baldassarre G, Bates PD (2009a) The utility of space-borne radar to render flood inundation maps based on multi-algorithm ensembles. IEEE Trans Geosci Remote Sensing 47(2):2801–2807

    Article  Google Scholar 

  • Schumann G, Bates PD, Horritt MS, Matgen P, Pappenberger F (2009b) Progress in integration of remote sensing–derived flood extent and stage data and hydraulic models. Reviews of Geophysics 47: RG4001

  • Schumann G, Di Baldassarre G, Alsdorf DE, Bates PD (2010) Near real-time flood wave approximation on large rivers from space: application to the River Po, Northern Italy. Water Resour Res 46:W05601

    Article  Google Scholar 

  • Smith LC (1997) Satellite remote sensing of river inundation area, stage and discharge: a review. Hydrol Process 11(10):1427–1439

    Article  Google Scholar 

  • Srinivasa RG, Brinda V, Manju P, Bhanumurthy V (2006) Advantage of multipolarized SAR data for flood extent delineation. Proceedings of the SPIE 6410

  • Todini E (1999) An operational decision support system for flood risk mapping, forecasting and management. Urban Water 1:131–143

    Article  Google Scholar 

  • Uhlenbrook S (2009) Climate and man-made changes and their impacts on catchments. In: Kovar P., Maca P., Redinova J. (eds.): Water Policy 2009, Water as a Vulnerable and Exhaustible Resource. Proceedings of the Joint Conference of APLU and ICA, 23-26 June 2009, Prague, Czech Republic, page 81-87

  • US Agency for International Development (2004) Dominican Republic and Haiti – Floods. USAID/OFDA Fact Sheet #3, June 17

  • Verhoest NEC, De Baets B, Mattia F, Satalino G, Lucau C, Defourny P (2007) A possibilistic approach to soil moisture retrieval from ERS synthetic aperture radar backscattering under soil roughness uncertainty, Water Resources Research, 43(7): W07435

    Google Scholar 

  • Vorogushyn S, Merz B, Lindenschmidt KE, Apel H (2010) A new methodology for flood hazard assessment considering dike breaches, Water Resources Research 10.1029/2009WR008475

  • Wilson MD, Bates PD, Alsdorf DE, Forsberg B, Horritt MS, Melack J, Frappart F, Famiglietti J (2007) Modeling large-scale inundation of Amazonian seasonally flooded wetlands. Geophys Res Lett 34:L15404

    Article  Google Scholar 

  • Wright NG, Asce M, Villanueva I et al (2008) Case study of the use of remotely sensed data for modeling flood inundation on the River Severn, UK. J Hydraul Engineer 134(5):533–540

    Article  Google Scholar 

  • Zwenzner H, Voigt S (2009) Improved estimation of flood parameters by combining space based SAR data with very high resolution digital elevation data. Hydrol Earth Syst Sci 13:567–576

    Article  Google Scholar 

Download references

Acknowledgments

The authors are extremely grateful to the European Space Agency (ESA) for allowing access to the flood images used in this study (Category 1 Project ID: 5739), the Environment Agency of England and Wales for the LiDAR data and the River Po Authority. Guy Schumann is funded by a Great Western Research fellowship.

Author information

Authors and Affiliations

  1. Department of Hydroinformatics and Knowledge Management, UNESCO-IHE, Delft, The Netherlands

    Giuliano Di Baldassarre

  2. School of Geographical Sciences, University of Bristol, Bristol, UK

    Guy Schumann & Paul Bates

  3. Department of Water Engineering, UNESCO-IHE, Delft, The Netherlands

    Luigia Brandimarte

Authors
  1. Giuliano Di Baldassarre
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Guy Schumann
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Luigia Brandimarte
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Paul Bates
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Giuliano Di Baldassarre.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Di Baldassarre, G., Schumann, G., Brandimarte, L. et al. Timely Low Resolution SAR Imagery To Support Floodplain Modelling: a Case Study Review. Surv Geophys 32, 255–269 (2011). https://doi.org/10.1007/s10712-011-9111-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10712-011-9111-9

Keywords

Search

Navigation