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Development of methodology for calculating flooded area and flood volume in small urban areas based on unmanned aerial vehicle images

Autor(en):



Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Frontiers in Built Environment, , v. 10
DOI: 10.3389/fbuil.2024.1482330
Abstrakt:

Climate change has intensified flooding and increased localized torrential rainfalls, leading to disasters such as landslides, infrastructure collapse, and urban floods. The extent and accuracy of flood damage information significantly impact recovery processes. While previous studies primarily utilized satellite and aerial imagery for broad flood assessments, they often lacked the precision needed for accurate damage analysis. This study addresses the gap between rapid assessment needs and precise damage quantification in flood inundation analysis. This research introduces a novel image-based investigation approach to enhance the speed and accuracy of flood inundation assessment. By leveraging unmanned aerial vehicles (UAVs) and image-based spatial data technology, aerial images of flooded areas are rapidly captured to construct three-dimensional disaster site terrain information. The proposed methodology employs advanced techniques in aerial photography, image processing, and geographic analysis to quantitatively analyze flood inundation scale using only aerial images and geographic information systems (GIS). The research yielded a calculated flood inundation area of 3,847.36 m2 and a flood volume of 13,895.13 m3. This methodology complements existing flood inundation assessment techniques and has the potential to significantly improve disaster management efforts by providing rapid, accurate, and actionable data for decision-makers.

Structurae kann Ihnen derzeit diese Veröffentlichung nicht im Volltext zur Verfügung stellen. Der Volltext ist beim Verlag erhältlich über die DOI: 10.3389/fbuil.2024.1482330.
  • Über diese
    Datenseite
  • Reference-ID
    10806498
  • Veröffentlicht am:
    10.11.2024
  • Geändert am:
    10.11.2024
 
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