Journal of Korea Water Resources Association (한국수자원학회논문집)

Korea Water Resources Association (한국수자원학회)
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Development of tracer concentration analysis method using drone-based spatio-temporal hyperspectral image and RGB image

드론기반 시공간 초분광영상 및 RGB영상을 활용한 추적자 농도분석 기법 개발

  • Gwon, Yeonghwa (Department of Civil & Environmental Engineering, Dankook University) ;
  • Kim, Dongsu (Department of Civil & Environmental Engineering, Dankook University) ;
  • You, Hojun (Water Infrastructure Safety Research Center, K-water Research Institute) ;
  • Han, Eunjin (Water Quality Assessment Research Division, National Institute of Environmental Research) ;
  • Kwon, Siyoon (Department of Civil and Environmental Engineering, Seoul National University) ;
  • Kim, Youngdo (Department of Civil & Environmental Engineering, Myongji University)
  • 권영화 (단국대학교 토목환경공학과) ;
  • 김동수 (단국대학교 토목환경공학과) ;
  • 유호준 (K-water 연구원) ;
  • 한은진 (국립환경과학원) ;
  • 권시윤 (서울대학교 건설환경공학부) ;
  • 김영도 (명지대학교 토목환경공학과)
  • Received : 2022.03.08
  • Accepted : 2022.07.21
  • Published : 2022.08.31
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Abstract

Due to river maintenance projects such as the creation of hydrophilic areas around rivers and the Four Rivers Project, the flow characteristics of rivers are continuously changing, and the risk of water quality accidents due to the inflow of various pollutants is increasing. In the event of a water quality accident, it is necessary to minimize the effect on the downstream side by predicting the concentration and arrival time of pollutants in consideration of the flow characteristics of the river. In order to track the behavior of these pollutants, it is necessary to calculate the diffusion coefficient and dispersion coefficient for each section of the river. Among them, the dispersion coefficient is used to analyze the diffusion range of soluble pollutants. Existing experimental research cases for tracking the behavior of pollutants require a lot of manpower and cost, and it is difficult to obtain spatially high-resolution data due to limited equipment operation. Recently, research on tracking contaminants using RGB drones has been conducted, but RGB images also have a limitation in that spectral information is limitedly collected. In this study, to supplement the limitations of existing studies, a hyperspectral sensor was mounted on a remote sensing platform using a drone to collect temporally and spatially higher-resolution data than conventional contact measurement. Using the collected spatio-temporal hyperspectral images, the tracer concentration was calculated and the transverse dispersion coefficient was derived. It is expected that by overcoming the limitations of the drone platform through future research and upgrading the dispersion coefficient calculation technology, it will be possible to detect various pollutants leaking into the water system, and to detect changes in various water quality items and river factors.

하천 주변 친수구역 조성, 4대강 사업 등과 같은 하천정비 사업으로 인해 하천의 흐름특성은 계속적으로 변동하고 있으며, 각종 오염물질 유입으로 인한 수질사고의 위험이 높아지고 있다. 수질사고 발생시 하천의 흐름특성을 고려해 오염물질의 농도 및 도달시간을 예측해 신속한 방제작업으로 하류로의 영향을 최소화해야한다. 이러한 오염물질의 거동을 추적하기 위해서는 하천의 구간별 확산계수, 분산계수 산정이 필요하며 그중 분산계수는 용존성 오염물질의 확산범위 해석에 사용된다. 오염물질의 거동을 추적하기 위한 기존 실험적 연구사례들은 많은 인력과 비용이 소요되고, 한정적인 장비의 운용으로 공간적으로 높은 해상도의 자료 취득이 어려웠다. 최근에는 RGB드론을 이용한 오염물질의 추적연구가 수행되었지만, RGB영상 역시 분광정보를 한정적으로 수집한다는 한계가 있다. 본 연구에서는 기존 연구들의 한계점들을 보완하기 위해 드론을 활용한 원격탐사 플랫폼에 초분광센서를 탑재하여 기존 접촉식 측정보다 시간적, 공간적으로 고해상도의 자료를 수집하였다. 수집된 시공간(Spatio-temporal) 초분광영상을 활용해 추적자의 농도를 산정하고, 횡분산계수를 도출하였다. 향후 연구를 통해 드론 플랫폼의 한계를 극복하고, 분산계수 산정 기술을 고도화하면 수계로 유출되는 각종 오염물질의 감지 및 다양한 수질항목 및 하천인자의 변화량 감지가 가능할 것으로 기대된다.

Keywords

Acknowledgement

본 연구는 환경부 국토교통과학기술진흥원(22DPIW-C153746-04)의 지원을 받아 연구되었습니다.

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