Hydraulic and event knowledge to reduce the positional uncertainty in SAR flood images for improved flood model calibration and development

Guy Schumann 1,2, Andrew Black 2,Mark Cutler 2, Jean-Baptiste Henry 3, Lucien Hoffmann 1, Patrick Matgen 1 and Laurent Pfister 1
1 Department of Environment and Agro-Biotechnologies, Public Research Centre-Gabriel Lippmann
41, rue du Brill, L-4422, Belvaux, Luxembourg
Tel: +352 47 02 61 417
schumann@lippmann.lu
2 Department of Geography, Dundee University
Nethergate Dundee, DD14HN, UK
3 Service Régional de Traitement d’Images et de Télédétection 
BP 10413, F-67412 Illkirch, Strasbourg, France

Abstract
In an attempt to reduce the positional uncertainty in SAR images depicting floods and lakes, thereby largely improving the  spatial accuracy of SAR-derived maps, this paper presents a Monte Carlo (MC) simulation-like image shifting procedure that shifts the X and Y coordinates of a SAR image until an acceptable minimum absolute error in elevation between the left and right flood extent level is found, whilst assuming a horizontal water surface on river cross sections. Independent Check Points (ICPs) indicating flood positions at bridges and elevated roads and railways are integrated with the MC-based procedure to provide direct validation of the image shifts. The proposed method, which requires hydraulic as well as event knowledge, greatly improves the positional accuracy of SAR-derived flood maps  and thus presents an inviting alternative to adjust the initial inaccurate geo-referencing often encountered with SAR images. The importance of applying the proposed method is illustrated by applying it to a flood inundation model calibration procedure using a SAR-derived flood extent. 

Keywords: SAR flood imagery, geometric correction, Monte Carlo Simulation, flood inundation model calibration, positional uncertainty

In: Caetano, M. and Painho, M. (eds). Proceedings of the 7th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, 5 – 7 July 2006, Lisboa, Instituto Geográfico Português

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