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UAV-borne, LiDAR-based elevation modelling: a method for improving local-scale urban flood risk assessment

Author

Listed:
  • Katerina Trepekli

    (University of Copenhagen
    University of Copenhagen)

  • Thomas Balstrøm

    (University of Copenhagen)

  • Thomas Friborg

    (University of Copenhagen)

  • Bjarne Fog

    (University of Copenhagen)

  • Albert N. Allotey

    (Council for Scientific & Industrial Research)

  • Richard Y. Kofie

    (Council for Scientific & Industrial Research)

  • Lasse Møller-Jensen

    (University of Copenhagen)

Abstract

In this study, we present the first findings of the potential utility of miniaturized light and detection ranging (LiDAR) scanners mounted on unmanned aerial vehicles (UAVs) for improving urban flood modelling and assessments at the local scale. This is done by generating ultra-high spatial resolution digital terrain models (DTMs) featuring buildings and urban microtopographic structures that may affect floodwater pathways (DTMbs). The accuracy and level of detail of the flooded areas, simulated by a hydrologic screening model (Arc-Malstrøm), were vastly improved when DTMbs of 0.3 m resolution representing three urban sites surveyed by a UAV-LiDAR in Accra, Ghana, were used to supplement a 10 m resolution DTM covering the region’s entire catchment area. The generation of DTMbs necessitated the effective classification of UAV-LiDAR point clouds using a morphological and a triangulated irregular network method for hilly and flat landscapes, respectively. The UAV-LiDAR data enabled the identification of archways, boundary walls and bridges that were critical when predicting precise run-off courses that could not be projected using the coarser DTM only. Variations in a stream’s geometry due to a one-year time gap between the satellite-based and UAV-LiDAR data sets were also observed. The application of the coarser DTM produced an overestimate of water flows equal to 15% for sloping terrain and up to 62.5% for flat areas when compared to the respective run-offs simulated from the DTMbs. The application of UAV-LiDAR may enhance the effectiveness of urban planning by projecting precisely the locations, extents and run-offs of flooded areas in dynamic urban settings.

Suggested Citation

  • Katerina Trepekli & Thomas Balstrøm & Thomas Friborg & Bjarne Fog & Albert N. Allotey & Richard Y. Kofie & Lasse Møller-Jensen, 2022. "UAV-borne, LiDAR-based elevation modelling: a method for improving local-scale urban flood risk assessment," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 113(1), pages 423-451, August.
    • Handle: RePEc:spr:nathaz:v:113:y:2022:i:1:d:10.1007_s11069-022-05308-9
    DOI: 10.1007/s11069-022-05308-9
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    References listed on IDEAS

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    1. Yun Xing & Qiuhua Liang & Gang Wang & Xiaodong Ming & Xilin Xia, 2019. "City-scale hydrodynamic modelling of urban flash floods: the issues of scale and resolution," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 96(1), pages 473-496, March.
    2. Cools, Jan & Innocenti, Demetrio & O’Brien, Sarah, 2016. "Lessons from flood early warning systems," Environmental Science & Policy, Elsevier, vol. 58(C), pages 117-122.
    3. Scott A. Kulp & Benjamin H. Strauss, 2019. "New elevation data triple estimates of global vulnerability to sea-level rise and coastal flooding," Nature Communications, Nature, vol. 10(1), pages 1-12, December.
    4. M. Mazzoleni & P. Paron & A. Reali & D. Juizo & J. Manane & L. Brandimarte, 2020. "Testing UAV-derived topography for hydraulic modelling in a tropical environment," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 103(1), pages 139-163, August.
    5. Scott A. Kulp & Benjamin H. Strauss, 2019. "Author Correction: New elevation data triple estimates of global vulnerability to sea-level rise and coastal flooding," Nature Communications, Nature, vol. 10(1), pages 1-2, December.
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