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

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 m 2 and a flood volume of 13,895.13 m 3 . 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.

Authors

Institutions

Publication Details

Journal
Frontiers in Built Environment
Published
2024-11-06
DOI
https://doi.org/10.3389/fbuil.2024.1482330
Citations
3
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
Field-Weighted Citation Impact
0.62

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Hye-Kyoung Lee, Hyun-Jung Woo, Minseok Kim, Dong-Min Seo
3 citations
Frontiers in Built Environment
Remote Sensing and LiDAR Applications
0.62
article

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

Hye-Kyoung Lee, Hyun-Jung Woo, Minseok Kim, Dong-Min Seo
article en
3 citations

Abstract

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 m 2 and a flood volume of 13,895.13 m 3 . 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.

Frontiers in Built EnvironmentVol. 10
Kyungpook National University (KR)
National Research Foundation of Korea
Climate action
Openalex Percentile: Top 35%
Remote Sensing and LiDAR Applications
0.62
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Development of methodology for calculating flooded area and flood volume in small urban areas based on unmanned aerial vehicle images — Hye-Kyoung Lee, Hyun-Jung Woo, et al. · Frontiers in Built Environment (2024) | TGRS Research Map | TGRS