Journal of Korean Society of Rural Planning (농촌계획)

Korean Society of Rural Planning (한국농촌계획학회)
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A Study on the Detection of Solar Power Plant for High-Resolution Aerial Imagery Using YOLO v2

YOLO v2를 이용한 고해상도 항공영상에서의 태양광발전소 탐지 방법 연구

  • Kim, Hayoung (Department of Rural and Biosystems Engineering & BK21 Education and Research Unit for Climate-smart Reclaimed-Tideland Agriculture, Chonnam National University) ;
  • Na, Ra (Department of Rural and Biosystems Engineering & BK21 Education and Research Unit for Climate-smart Reclaimed-Tideland Agriculture, Chonnam National University) ;
  • Joo, Donghyuk (Department of Rural and Biosystems Engineering & BK21 Education and Research Unit for Climate-smart Reclaimed-Tideland Agriculture, Chonnam National University) ;
  • Choi, Gyuhoon (WeDB) ;
  • Oh, Yun-Gyeong (Institute of Agricultural Science & Technology, Chonnam National University)
  • 김하영 (전남대학교 농업생명과학대학 지역.바이오시스템공학과 BK21) ;
  • 나라 (전남대학교 농업생명과학대학 지역.바이오시스템공학과 BK21) ;
  • 주동혁 (전남대학교 농업생명과학대학 지역.바이오시스템공학과 BK21) ;
  • 최규훈 (위디비 주식회사) ;
  • 오윤경 (전남대학교 농업생명과학대학 농업과학기술연구소)
  • Received : 2022.05.17
  • Accepted : 2022.05.30
  • Published : 2022.05.31
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Abstract

As part of strengthening energy security and responding to climate change, the government has promoted various renewable energy measures to increase the development of renewable energy facilities. As a result, small-scale solar installations in rural areas have increased rapidly. The number of complaints from local residents is increasing. Therefore, in this study, deep learning technology is applied to high-resolution aerial images on the internet to detect solar power plants installed in rural areas to determine whether or not solar power plants are installed. Specifically, I examined the solar facility detector generated by training the YOLO(You Only Look Once) v2 object detector and looked at its usability. As a result, about 800 pieces of training data showed a high object detection rate of 93%. By constructing such an object detection model, it is expected that it can be utilized for land use monitoring in rural areas, and it can be utilized as a spatial data construction plan for rural areas using technology for detecting small-scale agricultural facilities.

Keywords

Acknowledgement

2020년도 정부(과학기술정보통신부)의 재원으로 한국연구재단-중견연구사업의 지원을 받아 수행된 연구임(NRF-2020R1A2C1010502).

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