Point Cloud Data Fusion for Enhancing 2D Urban Flood Modelling  book cover
1st Edition

Point Cloud Data Fusion for Enhancing 2D Urban Flood Modelling

ISBN 9781138306172
Published August 1, 2017 by CRC Press
270 Pages

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Book Description

Modelling urban flood dynamics requires proper handling of a number of complex urban features. Although high-resolution topographic data can nowadays be obtained from aerial LiDAR surveys, such top-view LiDAR data still have difficulties to represent some key components of urban features. Incorrectly representing features like underpasses through buildings or apparent blockage of flow by sky trains may lead to misrepresentation of actual flood propagation, which could easily result in inadequate flood-protection measures. Hence proper handling of urban features plays an important role in enhancing urban flood modelling.

This research explores present-day capabilities of using computer-based environments to merge side-view Structure-from-Motion data acquisition with top-view LiDAR data to create a novel multi-source views (MSV) topographic representation for enhancing 2D model schematizations. A new MSV topographic data environment was explored for the city of Delft and compared with the conventional top-view LiDAR approach. Based on the experience gained, the effects of different topographic descriptions were explored for 2D urban flood models of (i) Kuala Lumpur, Malaysia for the 2003 flood event; and (ii) Ayutthaya, Thailand for the 2011 flood event.

It was observed that adopting the new MSV data as the basis for describing the urban topography, the numerical simulations provide a more realistic representation of complex urban flood dynamics, thus enhancing conventional approaches and revealing specific features like flood watermarks identification and helping to develop improved flood-protection measures.

Table of Contents

1 Introduction
1.1 Urban flooding
1.2 Topographic input data for urban flood modelling
1.3 Objectives and research questions
1.4 Dissertation outline

2 State of the art in urban flood modelling
2.1 Approaches to urban flood modelling
2.2 1D flood modelling
2.3 Quasi 2D approaches from 1D models
2.4 2D flood modelling
2.5 Coupled 1D-2D modelling
2.6 Comparisons of simulated results
2.7 Issues concerning complex-urban flood modelling

3 Conventional top-view LiDAR topographic data
3.1 Evolution in topographic data acquisition
3.2 Top-view LiDAR data acquisition
3.3 Raw LiDAR data processing and registration
3.4 Top-view LiDAR data simplification
3.5 Issues concerning top-view LiDAR data

4 Introducing new side-view SfM topographic data
4.1 Land surveying approaches
4.2 Side-view SfM data acquisition
4.3 Raw SfM data processing and registration
4.4 Side-view SfM data simplification
4.5 Issue concerning the side-view SfM data

5 A novel approach for merging multi-views topographic data
5.1 Multi-view enhancements
5.2 Effect of grid size
5.3 Considerations for raster-based topographic data
5.4 Selection of case study areas

6 Applying multi-source views DEM to the case study of Kuala Lumpur, Malaysia
6.1 The case study
6.2 Topographic data acquisition and rasterization
6.3 Numerical modelling schemes
6.4 Results
6.5 Discussion
6.6 Conclusions

7 Extracting inundation patterns from flood watermarks: the case study of Ayutthaya, Thailand
7.1 The case study
7.2 Top-view LiDAR data acquisition and processing
7.3 Side-view data acquisition and processing
7.4 Flood watermark extraction
7.5 Creating multi-source views digital elevation model (MSV-DEM)
7.6 Numerical modelling setups
7.7 Results
7.8 Discussion
7.9 Conclusions

8 Recommendations for developing flood-protection measures: the case study of Ayutthaya, Thailand
8.1 Problem identification
8.2 Proposed flood-protection measures
8.3 Establishment of scenarios
8.4 Evaluation of the simulated measures
8.5 Stakeholder preferences for flood-protection measures
8.6 Conclusions

9 Outlook of multi-view surveys and applications
9.1 Obtaining topographic data from different views
9.2 Unmanned aerial vehicle (UAV)
9.3 Mobile mapping system (MMS)
9.4 Unmanned surface vehicle (USV)
9.5 Night vision cameras for enhancing side-view surveys
9.6 Enhancing 2D model schematics
9.7 3Di for enhancing 2D models
9.8 High-performance computers for minimising computational costs

10 Conclusions and recommendations
10.1 Limitations of using conventional top-view LiDAR data
10.2 Benefits of using SfM technique for creating topographic data
10.3 3D point cloud data can be fused for constructing proper elevation maps
10.4 3D point cloud data can be used for enhancing 2D flood models
10.5 Enhanced computer-based environments can help developing flood protection measures
10.6 Recommendations


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Vorawit Meesuk is a PhD candidate in hydroinformatics for urban flood modelling at UNESCO-IHE and TU-Delft, the Netherlands. He holds a background MSc degree in Remote Sensing and GIS technologies (2003) from Khon Kaen University, Thailand. His PhD research focuses on the topic of applying computer vision and photogrammetry techniques to create better topographical data by merging different sources and difference viewpoints to enhance 2D flood simulation for complex urban cities. Besides doing research, he organised the Ayutthaya workshop in a joint effort with ADB, UNESCO-BANGKOK, in 2014. He also guided MSc students and gave GIS and coupled 1D-2D modelling lectures at UNESCO-IHE. Currently, he works at (HAII/MOST) as a Head of Observation and Telemetry Section, whose responsibilities are to provide and maintain telemetry systems for monitoring weather conditions and water-level changes in over 700 stations in Thailand and neighbouring countries.