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Abstract

ERS-SAR images are used to detect flooded areas during the July 1997 flood in the Oder catchment and the January 1995 flood in the Meuse catchment. Several methods are used to obtain the flooded areas from the SAR images. Amongst these methods is a statistical snake based on the work of Ivins and Porrill (1994), which operates on the image itself rather than an edge map. The technique identifies the flood as a region of homogenous SAR speckle statistics, the decision as to whether to include a set of pixels on the boundary of the growing contour being based on both local tone and texture measures, measured over several pixels along the contour. This allows some degree of noise reduction without sacrificing spatial resolution, the algorithm generally being able to identify features to within 1 pixel. The model also includes curvature constraints that favour a smooth contour and further reduce the effects of noise. The algorithm is capable of spawning smaller sub snakes to depict islands in the flood. The different methods are validated using aerial photographs taken during the flood and classified using field data.

Additional information

Authors: DE ROO A, SAI, JRC-Ispra (IT);VAN DER KNIJFF J, Utrecht University (NL);HORRITT, Bristol University (GB);SCHMUCK G, Bristol University (GB);DE JONG S, Wageningen Agriculture University (NL)
Bibliographic Reference: Paper presented: 2nd International Symposium on Operationalization of Remote Sensing', Enschede (NL), August 16-20th (1999)
Availability: Available from the Public Relations and Publications Unit, Ispra (IT)
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