한국수자원학회논문집 (Journal of Korea Water Resources Association)

  • 제53권12호
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  • Pages.1059-1070
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  • 2020
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  • 2799-8746(pISSN)
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  • 2799-8754(eISSN)
한국수자원학회 (Korea Water Resources Association)
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무인기 지원 RGB 영상과 다중선형회귀분석을 이용한 하천 수심 추정

Estimation of river water depth using UAV-assisted RGB imagery and multiple linear regression analysis

  • 문현태 (서울시립대학교 토목공학과) ;
  • 이정환 (서울시립대학교 토목공학과) ;
  • 육지문 (서울시립대학교 토목공학과) ;
  • 문영일 (서울시립대학교 토목공학과)
  • Moon, Hyeon-Tae (Department of Civil Engineering, University of Seoul) ;
  • Lee, Jung-Hwan (Department of Civil Engineering, University of Seoul) ;
  • Yuk, Ji-Moon (Department of Civil Engineering, University of Seoul) ;
  • Moon, Young-Il (Department of Civil Engineering, University of Seoul)
  • 투고 : 2020.06.10
  • 심사 : 2020.10.14
  • 발행 : 2020.12.31
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초록

하천단면 계측자료는 하천관리를 위한 유량산정 및 홍수 예·경보 방안 등 수리·수문 모델링 관련 연구에서 가장 중요한 입력자료 중 하나이다. 그러나 불규칙한 기하학적 구조로 이어지는 하천의 정확하고 연속적인 단면자료의 취득은 시간과 비용적 측면에서 큰 제약이 따른다. 이러한 관점에서 본 연구의 목적은 연속적인 하천특성의 공간분포를 시간과 비용, 인력의 투입을 최소화하여 계측할 수 있는 방법론을 개발하는 것이다. 따라서 RGB기반 항공 이미지와 실측 자료를 이용한 다중 선형 회귀 분석을 통해 각 단면별로 수심을 추정하고 연속적인 단면 추정 가능성과 정확도를 검토하고자 하였다. 실측 자료와 비교검증을 통해 공간적으로 이질적인 관계를 포착할 수 있는 수심 약 2 m 내외에서 수심을 정확하게 추정할 수 있음을 확인하였으며 이를 통해 정확하고 연속적인 하천 단면 취득에 기여할 수 있을 것으로 기대한다.

River cross-section measurement data is one of the most important input data in research related to hydraulic and hydrological modeling, such as flow calculation and flood forecasting warning methods for river management. However, the acquisition of accurate and continuous cross-section data of rivers leading to irregular geometric structure has significant limitations in terms of time and cost. In this regard, a primary objective of this study is to develop a methodology that is able to measure the spatial distribution of continuous river characteristics by minimizing the input of time, cost, and manpower. Therefore, in this study, we tried to examine the possibility and accuracy of continuous cross-section estimation by estimating the water depth for each cross-section through multiple linear regression analysis using RGB-based aerial images and actual data. As a result of comparing with the actual data, it was confirmed that the depth can be accurately estimated within about 2 m of water depth, which can capture spatially heterogeneous relationships, and this is expected to contribute to accurate and continuous river cross-section acquisition.

키워드

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