International Journal of Applied Earth Observation and Geoinformation
Integration of SAR-derived river inundation areas, high-precision topographic data and a river flow model toward near real-time flood management
Section snippets
Introduction and background
Repeated and increasingly frequent (e.g. Drogue et al., 2004) flood inundations occurring in many regions of the world and threatening human life and property enhance the need for effective flood risk management. The integration of various forms of geospatial information within a framework allows for flexible and timely analysis in the areas of flood forecasting, assessment and mitigation. Earth observation technologies and geographical information systems (GIS) are playing a large role in the
Study area and datasets
The SAR data used in this study relate to a flood prone area of the River Alzette, downstream of Luxembourg City (Grand Duchy of Luxembourg, Europe) (Fig. 1). The selected river floodplain with its surrounding villages has been subject to severe flooding in the past. The river reach between the gauging stations at Steinsel and Mersch has a length of approximately 10 km and its alluvial plain has an average width of about 300 m. A well-documented medium-sized flood event that occurred on 2 January
Hydraulic model description
Although believing any model is debatable as any model is subject to uncertainty, this study has assessed remotely sensed data uncertainties by turning the issue of model evaluation with remotely sensed data around. While most modellers in hydrology trust remotely sensed data to reliably evaluate or calibrate their models, in this study, on the contrary, the results of a hydraulic model conditioned on field data have been used as a benchmark test to evaluate SAR remote sensing methods that were
Methodology
Starting with the multi-look ASAR scene that is acquired at peak discharge during the 2 January 2003 flood and two digital elevation models with varying spatial resolution and accuracy, the flood depth mapping method follows the procedure illustrated in Fig. 3.
Results and discussion
This section outlines the application of the previously described methods to the VH-polarised ENVISAT ASAR image acquired during the 2 January 2003 flood in order to derive the water surface profile at peak discharge. The two images resulting from the thresholding and snake procedures were thematically classified into ‘flooded’ and ‘non-flooded’ (i.e. dry) pixels (Fig. 1). With the notable exception of some spurious ponds that were obtained by the thresholding method, the two inundation
Conclusion
This paper has proposed a methodology that acknowledges SAR based flood extent extraction uncertainty and goes beyond a mere descriptive exploitation of radar imagery. Two methods for accurate flood depth extraction are presented and validation with available evidence showed their usefulness for reliable flood stage estimation. With respect to traditional classification methods, substantial improvements were achieved. However, current sources of uncertainty like the coarse spatial resolution of
Acknowledgements
This study is supported by the ‘Ministère Luxembourgeois de la Culture, de l′Enseignement Supérieur et de la Recherche’. The authors would like to thank Jean-Paul Abadie at the French Space Agency (CNES) for supporting the research project and Florian Pappenberger at Lancaster University for helping with the model set-up. The DEM was made available by the ‘Ministère Luxembourgeois de l′Intérieur et de l′Aménagement du Territoire’. Matt Horritt from Bristol University is thanked for providing a
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