Urban flood modelling combining top-view LiDAR data with ground-view SfM observations

Remote Sensing technologies are capable of providing high-resolution spatial data needed to set up advanced flood simulation models. Amongst them, aerial Light Detection and Ranging (LiDAR) surveys or Airborne Laser Scanner (ALS) systems have long been used to provide digital topographic maps. Nowad...

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Main Authors: Meesuk, Vorawit, Vojinovic, Zoran, Mynett, Arthur E., Abdullah, Ahmad Fikri
Format: Article
Published: Elsevier 2015
Online Access:http://psasir.upm.edu.my/id/eprint/35928/
http://www.sciencedirect.com/science/article/pii/S0309170814002280
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spelling my.upm.eprints.359282016-02-11T08:47:49Z http://psasir.upm.edu.my/id/eprint/35928/ Urban flood modelling combining top-view LiDAR data with ground-view SfM observations Meesuk, Vorawit Vojinovic, Zoran Mynett, Arthur E. Abdullah, Ahmad Fikri Remote Sensing technologies are capable of providing high-resolution spatial data needed to set up advanced flood simulation models. Amongst them, aerial Light Detection and Ranging (LiDAR) surveys or Airborne Laser Scanner (ALS) systems have long been used to provide digital topographic maps. Nowadays, Remote Sensing data are commonly used to create Digital Terrain Models (DTMs) for detailed urban-flood modelling. However, the difficulty of relying on top-view LiDAR data only is that it cannot detect whether passages for floodwaters are hidden underneath vegetated areas or beneath overarching structures such as roads, railroads, and bridges. Such (hidden) small urban features can play an important role in urban flood propagation. In this paper, a complex urban area of Kuala Lumpur, Malaysia was chosen as a study area to simulate the extreme flooding event that occurred in 2003. Three different DTMs were generated and used as input for a two-dimensional (2D) urban flood model. A top-view LiDAR approach was used to create two DTMs: (i) a standard LiDAR-DTM and (ii) a Filtered LiDAR-DTM taking into account specific ground-view features. In addition, a Structure from Motion (SfM) approach was used to detect hidden urban features from a sequence of ground-view images; these ground-view SfM data were then combined with top-view Filtered LiDAR data to create (iii) a novel Multidimensional Fusion of Views-Digital Terrain Model (MFV-DTM). These DTMs were then used as a basis for the 2D urban flood model. The resulting dynamic flood maps are compared with observations at six measurement locations. It was found that when applying only top-view DTMs as input data, the flood simulation results appear to have mismatches in both floodwater depths and flood propagation patterns. In contrast, when employing the top-ground-view fusion approach (MFV-DTM), the results not only show a good agreement in floodwater depth, but also simulate more correctly the floodwater dynamics around small urban feature. Overall, the new multi-view approach of combining top-view LiDAR data with ground-view SfM observations shows a good potential for creating an accurate digital terrain map which can be then used as an input for a numerical urban flood model. Elsevier 2015-01 Article PeerReviewed Meesuk, Vorawit and Vojinovic, Zoran and Mynett, Arthur E. and Abdullah, Ahmad Fikri (2015) Urban flood modelling combining top-view LiDAR data with ground-view SfM observations. Advances in Water Resources, 75. pp. 105-117. ISSN 0309-1708 http://www.sciencedirect.com/science/article/pii/S0309170814002280 10.1016/j.advwatres.2014.11.008
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
description Remote Sensing technologies are capable of providing high-resolution spatial data needed to set up advanced flood simulation models. Amongst them, aerial Light Detection and Ranging (LiDAR) surveys or Airborne Laser Scanner (ALS) systems have long been used to provide digital topographic maps. Nowadays, Remote Sensing data are commonly used to create Digital Terrain Models (DTMs) for detailed urban-flood modelling. However, the difficulty of relying on top-view LiDAR data only is that it cannot detect whether passages for floodwaters are hidden underneath vegetated areas or beneath overarching structures such as roads, railroads, and bridges. Such (hidden) small urban features can play an important role in urban flood propagation. In this paper, a complex urban area of Kuala Lumpur, Malaysia was chosen as a study area to simulate the extreme flooding event that occurred in 2003. Three different DTMs were generated and used as input for a two-dimensional (2D) urban flood model. A top-view LiDAR approach was used to create two DTMs: (i) a standard LiDAR-DTM and (ii) a Filtered LiDAR-DTM taking into account specific ground-view features. In addition, a Structure from Motion (SfM) approach was used to detect hidden urban features from a sequence of ground-view images; these ground-view SfM data were then combined with top-view Filtered LiDAR data to create (iii) a novel Multidimensional Fusion of Views-Digital Terrain Model (MFV-DTM). These DTMs were then used as a basis for the 2D urban flood model. The resulting dynamic flood maps are compared with observations at six measurement locations. It was found that when applying only top-view DTMs as input data, the flood simulation results appear to have mismatches in both floodwater depths and flood propagation patterns. In contrast, when employing the top-ground-view fusion approach (MFV-DTM), the results not only show a good agreement in floodwater depth, but also simulate more correctly the floodwater dynamics around small urban feature. Overall, the new multi-view approach of combining top-view LiDAR data with ground-view SfM observations shows a good potential for creating an accurate digital terrain map which can be then used as an input for a numerical urban flood model.
format Article
author Meesuk, Vorawit
Vojinovic, Zoran
Mynett, Arthur E.
Abdullah, Ahmad Fikri
spellingShingle Meesuk, Vorawit
Vojinovic, Zoran
Mynett, Arthur E.
Abdullah, Ahmad Fikri
Urban flood modelling combining top-view LiDAR data with ground-view SfM observations
author_facet Meesuk, Vorawit
Vojinovic, Zoran
Mynett, Arthur E.
Abdullah, Ahmad Fikri
author_sort Meesuk, Vorawit
title Urban flood modelling combining top-view LiDAR data with ground-view SfM observations
title_short Urban flood modelling combining top-view LiDAR data with ground-view SfM observations
title_full Urban flood modelling combining top-view LiDAR data with ground-view SfM observations
title_fullStr Urban flood modelling combining top-view LiDAR data with ground-view SfM observations
title_full_unstemmed Urban flood modelling combining top-view LiDAR data with ground-view SfM observations
title_sort urban flood modelling combining top-view lidar data with ground-view sfm observations
publisher Elsevier
publishDate 2015
url http://psasir.upm.edu.my/id/eprint/35928/
http://www.sciencedirect.com/science/article/pii/S0309170814002280
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score 13.211869