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Drone-Based Water Level Detection in Flood Disasters.

Hamada Rizk1,2, Yukako Nishimur1, Hirozumi Yamaguchi1

  • 1Graduate School of Information Science and Technology, Osaka University, Osaka 565-0871, Japan.

International Journal of Environmental Research and Public Health
|January 11, 2022
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Summary

A new drone-based system uses aerial images and AI to detect flood water levels, improving disaster response after events like Typhoon Hagibis. This technology offers a faster, broader, and more accurate assessment of flood damage.

Keywords:
drone-based visionemergency recoveryflood disaster assessmentwater level detection

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Area of Science:

  • Environmental Science
  • Computer Science
  • Remote Sensing

Background:

  • Typhoon Hagibis caused widespread flooding in Japan, damaging thousands of buildings.
  • Rapid and accurate flood damage assessment is crucial for effective disaster relief and recovery.
  • Traditional on-site sensors are costly and impractical for large-scale damage assessment.

Purpose of the Study:

  • To develop and evaluate a drone-based aerial image recognition system for detecting water levels during floods.
  • To overcome the limitations of ground-level imagery in flood assessment.
  • To provide a feasible alternative for rapid, broad, and accurate flood damage evaluation.

Main Methods:

  • Utilized aerial drone imagery for a top-view perspective of flood-affected areas.
  • Applied a novel labeling method for reference objects (houses, cars) within a Region-based Convolutional Neural Network (R-CNN) framework.
  • Employed data augmentation and transfer learning with Mask R-CNN to handle limited and varied flood image datasets.
  • Integrated the VGG16 network for precise water level detection.

Main Results:

  • The system achieved a 73.42% accuracy in detecting submerged objects.
  • Demonstrated a low error rate of 21.43 cm in estimating water levels.
  • Evaluated the system's performance using realistic images captured during a disaster event.

Conclusions:

  • Drone-based aerial image analysis offers a viable solution for flood water level detection.
  • The proposed system effectively addresses challenges associated with top-view flood imagery.
  • This technology can significantly enhance the speed and accuracy of flood damage assessment for disaster management.