The consequences of recent floods and flash floods in many parts of the world have been devastating. One way to improving flood management practice is to invest in data collection and modelling activities which enable an understanding of the functioning of a system and the selection of optimal mitigation measures. A Digital Terrain Model (DTM) provides the most essential information for flood managers. Light Detection and Ranging (LiDAR) surveys which enable the capture of spot heights at a spacing of 0.5m to 5m with a horizontal accuracy of 0.3m and a vertical accuracy of 0.15m can be used to develop high accuracy DTM but needs careful processing before using it for any application.This book presents the augmentation of an existing Progressive Morphological filtering algorithm for processing raw LiDAR data to support a 1D/2D urban flood modelling framework. The key characteristics of this improved algorithm are: (1) the ability to deal with different kinds of buildings; (2) the ability to detect elevated road/rail lines and represent them in accordance to the reality; (3) the ability to deal with bridges and riverbanks; and (4) the ability to recover curbs and the use of appropriated roughness coefficient of Manning‘s value to represent close-to-earth vegetation (e.g. grass and small bush).
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Ahmad Fikri bin Abdullah was born in the state of Terengganu, Malaysia. In 1996 he enrolled to the BSc degree course with a full scholarship from the Public Service Department of Malaysia for 4 years in Geoinformatics (GIS) at the Malaysia University of Technology. He was graduated (with distinction) in 2000. Soon after that, he was hired as a GIS Executive at Geomatika Technology Sdn Bhd and after that as a GIS Manager at Guardian Data Sdn Bhd. In July 2006 he was offered a full scholarship UNESCO-IHE under SWITCH project for PhD degree. In 2008 he received a full scholarship from the Ministry for Higher Education of Malaysia for pursuing his PhD. The period of the scholarship was 5 years. His research was devoted for A Methodology for Processing Raw LiDAR Data to Support Urban Flood Modelling Framework which is presented in this thesis.
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