skip to main content
10.1145/3557915.3560945acmconferencesArticle/Chapter ViewAbstractPublication PagesgisConference Proceedingsconference-collections
short-paper
Open Access

A geospatial modelling framework to assess flood risk under future scenarios of urban form (vision paper)

Published:22 November 2022Publication History

ABSTRACT

Simulations of future urban form (road networks, land use type, building density and building type) are needed to provide greater clarity of future urban flooding dynamics. This paper proposes an interdisciplinary and novel geospatial approach involving advanced geosimulations, artificial intelligence algorithms and hydrodynamic modelling to assess how flood risk is exacerbated under different urban form scenarios. It is envisioned that the final output will have a pivotal impact on urban growth modelling research and enhance community-level knowledge and resilience to urban flooding.

References

  1. Mickaël Brasebin, Julien Perret, Sébastien Mustière, and Christiane Weber. 2016. A Generic Model to Exploit Urban Regulation Knowledge. ISPRS International Journal of Geo-Information 5, 2 (2016), 1--17.Google ScholarGoogle ScholarCross RefCross Ref
  2. Mickaël Brasebin, Julien Perret, Sébastien Mustière, and Christiane Weber. 2018. 3D urban data to assess local urban regulation influence. Computers, Environment and Urban Systems 68 (2018), 37--52.Google ScholarGoogle ScholarCross RefCross Ref
  3. Hui Cao, Jian Liu, Jianglong Chen, Jinlong Gao, Guizhou Wang, and Wanfeng Zhang. 2019. Spatiotemporal patterns of urban land use change in typical cities in the greater mekong subregion (GMS). Remote sensing 11, 7 (2019), 1--28.Google ScholarGoogle Scholar
  4. Ylenia Casali and Hans R Heinimann. 2019. A topological characterization of flooding impacts on the Zurich road network. PLoS one 14, 7 (2019), 1--15.Google ScholarGoogle ScholarCross RefCross Ref
  5. Conservation International. 2021. Mekong river catchment map. Available at: https://www.conservation.org/places/greater-mekong [Accessed: December 2021].Google ScholarGoogle Scholar
  6. Rui Ding, Yilin Zhang, Ting Zhang, and Can Ma. 2021. Development of a Complex Network-Based Integrated Multilayer Urban Growth and Optimisation Model for an Efficient Urban Traffic Network. Complexity 2021 (2021).Google ScholarGoogle Scholar
  7. Vassilis Glenis, Vedrana Kutija, and Chris G Kilsby. 2018. A fully hydrodynamic urban flood modelling system representing buildings, green space and interventions. Environmental Modelling & Software 109 (2018), 272--292.Google ScholarGoogle ScholarCross RefCross Ref
  8. D Sathish Kumar, DS Arya, and Zoran Vojinovic. 2013. Modeling of urban growth dynamics and its impact on surface runoff characteristics. Computers, Environment and Urban Systems 41 (2013), 124--135.Google ScholarGoogle ScholarCross RefCross Ref
  9. Han Li, Yehua Dennis Wei, and Kim Korinek. 2018. Modelling urban expansion in the transitional Greater Mekong Region. Urban Studies 55, 8 (2018), 1729--1748.Google ScholarGoogle ScholarCross RefCross Ref
  10. Carlos Molinero and Alberto Hernando. 2020. A model for the generation of road networks. arXiv preprint (2020), 1--15.Google ScholarGoogle Scholar
  11. National Institute of Statistics. 2019. General Population Census of the Kingdom of Cambodia 2019. Ministry of Planning.Google ScholarGoogle Scholar
  12. Eduardo Pérez-Molina, Richard Sliuzas, Johannes Flacke, and Victor Jetten. 2017. Developing a cellular automata model of urban growth to inform spatial policy for flood mitigation: A case study in Kampala, Uganda. Computers, environment and urban systems 65 (2017), 53--65.Google ScholarGoogle ScholarCross RefCross Ref
  13. RStudio. 2021. Shiny. Available at: https://shiny.rstudio.com/ [Accessed: December 2021].Google ScholarGoogle Scholar
  14. Yikang Rui and Yifang Ban. 2011. Urban growth modeling with road network expansion and land use development. Advances in Cartography and GIScience 2 (2011), 399--412.Google ScholarGoogle Scholar
  15. Yikang Rui, Yifang Ban, Jiechen Wang, and Jan Haas. 2013. Exploring the patterns and evolution of self-organized urban street networks through modeling. The European Physical Journal B 86, 3 (2013), 1--8.Google ScholarGoogle ScholarCross RefCross Ref
  16. Hossein Shafizadeh-Moghadam and Marco Helbich. 2015. Spatiotemporal variability of urban growth factors: A global and local perspective on the megacity of Mumbai. International Journal of Applied Earth Observation and Geoinformation 35 (2015), 187--198.Google ScholarGoogle ScholarCross RefCross Ref
  17. Patrick Taillandier, Arnaud Banos, Alexis Drogoul, Benoit Gaudou, Nicolas Marilleau, and Quang Truong. 2016. Simulating Urban Growth with Raster and Vector models: A case study for the city of Can Tho, Vietnam. International Conference on Autonomous Agents and Multiagent Systems (2016), 154--171.Google ScholarGoogle ScholarCross RefCross Ref
  18. Lars Tierolf, Hans de Moel, and Jasper van Vliet. 2021. Modeling urban development and its exposure to river flood risk in Southeast Asia. Computers, Environment and Urban Systems 87 (2021), 1--11.Google ScholarGoogle ScholarCross RefCross Ref
  19. World Bank. 2015. East Asia's Changing Urban Landscape: Measuring a Decade of Spatial Growth. The World Bank.Google ScholarGoogle Scholar
  20. Tingting Xu, Jay Gao, Giovanni Coco, and Shuliang Wang. 2020. Urban expansion in Auckland, New Zealand: a GIS simulation via an intelligent self-adapting multiscale agent-based model. International Journal of Geographical Information Science 34, 11 (2020), 2136--2159.Google ScholarGoogle ScholarCross RefCross Ref
  21. Hao Zheng and Yue Ren. 2020. Architectural layout design through simulated annealing algorithm. (2020), 275--284.Google ScholarGoogle Scholar

Index Terms

  1. A geospatial modelling framework to assess flood risk under future scenarios of urban form (vision paper)

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Conferences
      SIGSPATIAL '22: Proceedings of the 30th International Conference on Advances in Geographic Information Systems
      November 2022
      806 pages
      ISBN:9781450395298
      DOI:10.1145/3557915

      Copyright © 2022 ACM

      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 22 November 2022

      Permissions

      Request permissions about this article.

      Request Permissions

      Check for updates

      Qualifiers

      • short-paper

      Acceptance Rates

      Overall Acceptance Rate220of1,116submissions,20%
    • Article Metrics

      • Downloads (Last 12 months)76
      • Downloads (Last 6 weeks)12

      Other Metrics

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader