Automated tornado damage assessment and wind speed estimation based on terrestrial laser scanning

Alireza G. Kashani, Patrick S. Crawford, Sufal K. Biswas, Andrew J. Graettinger, David Grau Torrent

Research output: Contribution to journalArticlepeer-review

25 Scopus citations

Abstract

There are more than 1,000 tornadoes in the United States each year, yet engineers do not typically design for tornadoes because of insufficient information about wind loads. Collecting building-level damage data in the aftermath of tornadoes can improve the understanding of tornado winds, but these data are difficult to collect because of safety, time, and access constraints. This study presents and tests an automated geographic information system (GIS) method using postevent point cloud data collected by terrestrial scanners and preevent aerial images to calculate the percentage of roof and wall damage and estimate wind speeds at an individual building scale. Simulations determined that for typical point cloud density (>25∈∈points/m2), a GIS raster cell size of 40-50 cm resulted in less than 10% error in damaged roof and wall detection. Data collected after recent tornadoes were used to correlate wind speed estimates and the percent of detected damage. The developed method estimated wind speeds from damage data collected after the 2011 Tuscaloosa, AL tornado at finer scales than the typical large-scale assessments done by reconnaissance engineers.

Original languageEnglish (US)
Article number04014051
JournalJournal of Computing in Civil Engineering
Volume29
Issue number3
DOIs
StatePublished - May 1 2015

Keywords

  • Assessment
  • Automatic identification systems
  • Damage
  • Geographic information systems (GIS)
  • Laser scanning
  • Natural disasters
  • Three-dimensional analysis
  • Wind speed

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Computer Science Applications

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