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Assessing vulnerability due to sea-level rise in Maui, Hawai ‘i using LiDAR remote sensing and GIS

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  • Hannah Cooper
  • Qi Chen
  • Charles Fletcher
  • Matthew Barbee

Abstract

Sea-level rise (SLR) threatens islands and coastal communities due to vulnerable infrastructure and populations concentrated in low-lying areas. LiDAR (Light Detection and Ranging) data were used to produce high-resolution DEMs (Digital Elevation Model) for Kahului and Lahaina, Maui, to assess the potential impacts of future SLR. Two existing LiDAR datasets from USACE (U.S. Army Corps of Engineers) and NOAA (National Oceanic and Atmospheric Administration) were compared and calibrated using the Kahului Harbor tide station. Using tidal benchmarks is a valuable approach for referencing LiDAR in areas lacking an established vertical datum, such as in Hawai‘i and other Pacific Islands. Exploratory analysis of the USACE LiDAR ground returns (point data classified as ground after the removal of vegetation and buildings) indicated that another round of filtering could reduce commission errors. Two SLR scenarios of 0.75 (best-case) to 1.9 m (worst-case) (Vermeer and Rahmstorf Proc Natl Acad Sci 106:21527–21532, 2009 ) were considered, and the DEMs were used to identify areas vulnerable to flooding. Our results indicate that if no adaptive strategies are taken, a loss ranging from $18.7 million under the best-case SLR scenario to $296 million under the worst-case SLR scenario for Hydrologically Connected (HC; marine inundation) and Hydrologically Disconnected (HD; drainage problems due to a higher water table) areas combined is possible for Kahului; a loss ranging from $57.5 million under the best-case SLR scenario to $394 million under the worst-case SLR scenario for HC and HD areas combined is possible for Lahaina towards the end of the century. This loss would be attributable to inundation between 0.55 km 2 to 2.13 km 2 of area for Kahului, and 0.04 km 2 to 0.37 km 2 of area for Lahaina. Copyright Springer Science+Business Media B.V. 2013

Suggested Citation

  • Hannah Cooper & Qi Chen & Charles Fletcher & Matthew Barbee, 2013. "Assessing vulnerability due to sea-level rise in Maui, Hawai ‘i using LiDAR remote sensing and GIS," Climatic Change, Springer, vol. 116(3), pages 547-563, February.
    • Handle: RePEc:spr:climat:v:116:y:2013:i:3:p:547-563
    DOI: 10.1007/s10584-012-0510-9
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    References listed on IDEAS

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    1. Keqi Zhang & John Dittmar & Michael Ross & Chris Bergh, 2011. "Assessment of sea level rise impacts on human population and real property in the Florida Keys," Climatic Change, Springer, vol. 107(1), pages 129-146, July.
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    Cited by:

    1. Jejal Reddy Bathi & Himangshu S. Das, 2016. "Vulnerability of Coastal Communities from Storm Surge and Flood Disasters," IJERPH, MDPI, vol. 13(2), pages 1-12, February.
    2. Salim Mohammed Al-Hajri & George P. Petropoulos & Vassiliki Markogianni, 2021. "Seasonal variation of key environmental parameters in the Sea of Oman using EO data and GIS," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(4), pages 6021-6046, April.
    3. Thomas David Pol & Jochen Hinkel, 2019. "Uncertainty representations of mean sea-level change: a telephone game?," Climatic Change, Springer, vol. 152(3), pages 393-411, March.
    4. Xinyu Fu & Jie Song, 2017. "Assessing the Economic Costs of Sea Level Rise and Benefits of Coastal Protection: A Spatiotemporal Approach," Sustainability, MDPI, vol. 9(8), pages 1-14, August.
    5. Johnson Ankrah & Ana Monteiro & Helena Madureira, 2023. "Geospatiality of sea level rise impacts and communities’ adaptation: a bibliometric analysis and systematic review," 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. 116(1), pages 1-31, March.

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