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Change Detection of Building Demolition Area Using UAV

UAV를 활용한 건물철거 지역 변화탐지

Shin, Dongyoon;Kim, Taeheon;Han, Youkyung;Kim, Seongsam;Park, Jesung
신동윤;김태헌;한유경;김성삼;박제성

  • Received : 2019.09.19
  • Accepted : 2019.10.14
  • Published : 2019.10.31

Abstract

In the disaster of collapse, an immediate response is needed to prevent the damage from worsening, and damage area calculation, response and recovery plan should be established. This requires accurate detection of the damage affected area. This study performed the detection of the damaged area by using UAV which can respond quickly and in real-time to detect the collapse accident. The study area was selected as B-05 housing redevelopment area in Jung-gu, Ulsan, where the demolition of houses and apartments in progress as the redevelopment project began. This area resembles a collapsed state of the building, which clear changes before and after the demolition. UAV images were acquired on May 17 and July 9, 2019, respectively. The changing area was considered as the damaged area before and after the collapse of the building, and the changing area was detected using CVA (Change Vector Analysis) the Representative Change Detection Technique, and SLIC (Simple Linear Iterative Clustering) based superpixel algorithm. In order to accurately perform the detection of the damaged area, the uninterested area (vegetation) was firstly removed using ExG (Excess Green), Among the objects that were detected by change, objects that had been falsely detected by area were finally removed by calculating the minimum area. As a result, the accuracy of the detection of damaged areas was 95.39%. In the future, it is expected to be used for various data such as response and recovery measures for collapse accidents and damage calculation.

Keywords

Collapse;CVA;SLIC-superpixel;UAV;Change detection

Acknowledgement

Grant : 재난안전 관리업무지원기술개발(R&D)-재난원인 현장감식 기술개발

Supported by : 국립재난안전연구원