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A Constantly Updated Flood Hazard Assessment Tool Using Satellite-Based High-Resolution Land Cover Dataset Within Google Earth Engine

Author

Listed:
  • Alexandra Gemitzi

    (Department of Environmental Engineering, Democritus University of Thrace, 67100 Xanthi, Greece)

  • Odysseas Kopsidas

    (Department of Environmental Engineering, Democritus University of Thrace, 67100 Xanthi, Greece)

  • Foteini Stefani

    (National School of Public Administration and Local Government, 17778 Athens, Greece)

  • Aposotolos Polymeros

    (Ministry of Rural Development and Food, 10176 Athens, Greece)

  • Vasilis Bellos

    (Department of Environmental Engineering, Democritus University of Thrace, 67100 Xanthi, Greece)

Abstract

This work aims to develop a constantly updated flood hazard assessment tool that utilizes readily available datasets derived by remote sensing techniques. It is based on the recently released global land use/land cover (LULC) dataset Dynamic World, which is readily available, covering the period from 2015 until now, as an open data source within the Google Earth Engine (GEE) platform. The tool is updated constantly following the release rate of Sentinel-2 images, i.e., every 2 to 5 days depending on the location, and provides a near-real-time detection of flooded areas. Specifically, it identifies how many times each 10 m pixel is characterized as flooded for a selected time period. To investigate the fruitfulness of the proposed tool, we provide two different applications; the first one in the Thrace region, where the flood hazard map computed with the presented herein approach was compared against the flood hazard maps developed in the frames of the EU Directive 2007/60, and we found several inconsistencies between the two approaches. The second application focuses on the Thessaly region, aiming to assess the impacts of a specific, unprecedented storm event that affected the study area in September 2023. Moreover, a new economic metric is proposed, named maximum potential economic loss, to assess the socioeconomic implications of the flooding. The innovative character of the presented methodology consists of the use of remotely sensed-based datasets, becoming available at increasing rates, for developing an operational instrument that defines and updates the flood hazard zones in real-time as required.

Suggested Citation

  • Alexandra Gemitzi & Odysseas Kopsidas & Foteini Stefani & Aposotolos Polymeros & Vasilis Bellos, 2024. "A Constantly Updated Flood Hazard Assessment Tool Using Satellite-Based High-Resolution Land Cover Dataset Within Google Earth Engine," Land, MDPI, vol. 13(11), pages 1-18, November.
  • Handle: RePEc:gam:jlands:v:13:y:2024:i:11:p:1929-:d:1522431
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    References listed on IDEAS

    as
    1. Quan Sun & John Mann & Mark Skidmore, 2022. "The Impacts of Flooding and Business Activity and Employment: A Spatial Perspective on Small Business," Water Economics and Policy (WEP), World Scientific Publishing Co. Pte. Ltd., vol. 8(03), pages 1-22, July.
    2. Ioanna Zotou & Vasilis Bellos & Angeliki Gkouma & Vassilia Karathanassi & Vassilios A. Tsihrintzis, 2020. "Using Sentinel-1 Imagery to Assess Predictive Performance of a Hydraulic Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(14), pages 4415-4430, November.
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