Data Fusion Of Post-disaster VHR Aerial Imagery And LiDAR Data For Roof Classification Using Convolutional Neural Networks.pdf

2307.16177.pdf
Preview of Data Fusion of Post-disaster VHR Aerial Imagery and LiDAR Data for Roof Classification using Convolutional Neural Networks
🔗 Source: arxiv.org
📊 Size: 4.69 MB
📄 Pages: 8 pages
⬇️ Downloads: 59

Summary

Researchers leveraged deep learning techniques to classify roof characteristics from very high-resolution orthophotos and airborne LiDAR data obtained in Dominica after Hurricane Maria in 2017. They demonstrated that fusing multimodal earth observation data performs better than using any single data source alone, achieving F1 scores of 0.93 and 0.92 for roof type and roof material classification, respectively. The study aims to help governments produce timely building information to improve resilience and disaster response in the Caribbean.

Description

Researchers leveraged deep learning techniques to classify roof characteristics from very high-resolution orthophotos and airborne LiDAR data obtained in...

Technical Information

  • File Format: PDF
  • File Size: 4.69 MB
  • Pages: 8
  • Language: EN
  • Total Downloads: 59
  • Last Updated: 3 months ago

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