Application of Drones for the Analysis of Hazard Areas in Mountainous Disaster 


Vol. 33,  No. 3, pp. 65-70, Jun.  2018
10.14346/JKOSOS.2018.33.3.65


PDF
  Abstract

Terrain data for disaster analysis in hazardous or disaster areas is not only important but also needs to be built quickly. In particular, the introduction of drones is in the early stages of research using drones in a variety of fields such as shooting, analyzing and managing hazardous areas. It is expected that drone will be faster, safer and more effective than existing data collection method in case of small scale disaster hazard area and disaster area where equipment or manpower input is difficult. Therefore, in this study, drone shooting was performed for hazardous areas in mountainous roads located in Samcheok city, Gangwon province, and ground reference points were measured by RTK-GPS. The measured data were converted into DSM (Digital Surface Model) data by coordinate correction using Pix4D postprocessing program and then applied to the analysis of the hazard area of mountainous area. As a result, it was shown that it is effective to identify the risk by using the basic terrain data obtained from the drones.

  Statistics
Cumulative Counts from November, 2022
Multiple requests among the same browser session are counted as one view. If you mouse over a chart, the values of data points will be shown.


  Cite this article

[IEEE Style]

이정훈, 전계원, 전병희, "Application of Drones for the Analysis of Hazard Areas in Mountainous Disaster," Journal of the Korean Society of Safety, vol. 33, no. 3, pp. 65-70, 2018. DOI: 10.14346/JKOSOS.2018.33.3.65.

[ACM Style]

이정훈, 전계원, and 전병희. 2018. Application of Drones for the Analysis of Hazard Areas in Mountainous Disaster. Journal of the Korean Society of Safety, 33, 3, (2018), 65-70. DOI: 10.14346/JKOSOS.2018.33.3.65.

Search
(IN TITLE, AUTHOR, ABSTRACT,KEYWORDS)

Advanced Search ▼

POPULAR KEYWORDS
(TOP 10 KEYWORDS)

Recent Publications
(LAST 3 YEARS)

pISSN : 1229 - 9197
eISSN : 1875 - 0052

Impact Factor(2022): 2.5