This paper addresses the issue of a detailed representation of an urban catchment in terms of hydraulic and hydrologic
attributes. Modelling of urban flooding requires a detailed knowledge of urban surface characteristics. The advancement
in spatial data acquisition technology such as airborne LiDAR (Light Detection and Ranging) has greatly facilitated the
collection of high-resolution topographic information. While the use of the LiDAR-derived Digital Surface Model
(DSM) has gained popularity over the last few years as input data for a flood simulation model, the use of LiDAR
intensity data has remained largely unexplored in this regard. LiDAR intensity data are acquired along with elevation
data during the data collection mission by an aircraft. The practice of using of just aerial images with RGB (Red, Green
and Blue) wavebands is often incapable of identifying types of surface under the shadow. On the other hand, LiDAR
intensity data can provide surface information independent of sunlight conditions. The focus of this study is the use of
intensity data in combination with aerial images to accurately map pervious and impervious urban areas. This study
presents an Object-Based Image Analysis (OBIA) framework for detecting urban land cover types, mainly pervious and
impervious surfaces in order to improve the rainfall-runoff modelling. Finally, this study shows the application of highresolution DSM and land cover maps to flood simulation software in order to visualize the depth and extent of urban
flooding phenomena.
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