Fractal analysis of urban environment: land use and sewer system

Tuesday, 16 December 2014
Auguste Gires1, Susana Ochoa Rodriguez2, Johan Van Assel3, Guendalina Bruni4, Damian Murla Tulys5, Lipen Wang5, Rui Pina2, Julien Richard1, Abdellah Ichiba1, Patrick Willems5, Ioulia Tchiguirinskaia1, Marie-Claire ten Veldhuis4 and Daniel J M Schertzer1, (1)U. Paris Est, Ecole des Ponts ParisTech,, Marne-la-Vallee,, France, (2)Imperial College London, London, United Kingdom, (3)Aquafin, Antwerpen, Netherlands, (4)Delft University of Technology, Delft, Netherlands, (5)KULeuven, Leuven, Belgium
Land use distribution are usually obtained by automatic processing of satellite and airborne pictures. The complexity of the obtained patterns which are furthermore scale dependent is enhanced in urban environment. This scale dependency is even more visible in a rasterized representation where only a unique class is affected to each pixel. A parameter commonly analysed in urban hydrology is the coefficient of imperviousness, which reflects the proportion of rainfall that will be immediately active in the catchment response. This coefficient is strongly scale dependent with a rasterized representation. This complex behaviour is well grasped with the help of the scale invariant notion of fractal dimension which enables to quantify the space occupied by a geometrical set (here the impervious areas) not only at a single scale but across all scales. This fractal dimension is also compared to the ones computed on the representation of the catchments with the help of operational semi-distributed models. Fractal dimensions of the corresponding sewer systems are also computed and compared with values found in the literature for natural river networks.

This methodology is tested on 7 pilot sites of the European NWE Interreg IV RainGain project located in France, Belgium, Netherlands, United-Kingdom and Portugal. Results are compared between all the case study which exhibit different physical features (slope, level of urbanisation, population density...).