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원격탐사기반 임분고 추정 모델 개발 국내외 현황 고찰 및 제언
Review of Remote Sensing Technology for Forest Canopy Height Estimation and Suggestions for the Advancement of Korea's Nationwide Canopy Height Map 원문보기

한국산림과학회지 = Journal of korean society of forest science, v.111 no.3, 2022년, pp.435 - 449  

이복남 (경북대학교 빅데이터 기반 글로컬 Forest Science 4.0 전문인력양성센터) ,  정건휘 (경북대학교 임학과) ,  류지연 (경북대학교 임학과) ,  권경원 (경북대학교 임학과) ,  임종수 (국립산림과학원 산림ICT연구센터) ,  박주원 (경북대학교 산림과학.조경학부)

초록
AI-Helper 아이콘AI-Helper

대면적 산림의 정확한 임분고 측정은 산림경영, 산림 탄소량 추정, 산림 생태계 관리를 위한 필수적인 지표인자로 다수의 국가에서 주기적인 현장조사를 수행하고 있다. 하지만, 현장조사는 많은 비용 및 시간 소요, 접근의 용이성이 낮은 지역의 조사의 기술적 한계성을 가지고 있다. 이를 극복하기 위한 대안으로 원격탐사 기술을 이용한 수고 및 임분고 추정 연구가 활발하다. 이에 본 논문에서는 해외 및 국내의 다양한 원격탐사기반 수고 및 임분고 추정 연구 사례를 분석하여 원격탐사기반 임분고 추정 연구의 동향을 크게 LiDAR기반, Stereo 및 SAR 이미지 점군(Image-based Point Clouds)기반, 원격탐사자료 융합기반 임분고 추정 모델로 나누어 살펴보았다. 또한, 대면적의 전국단위 산림 임분고 추정을 위한 원격탐사자료의 업스케일링(Upscaling) 기법의 사례 분석을 통해 향후 국내 산림환경 및 현황에 적합한 원격탐사기반 전국단위 산림 임분고 추정을 위한 방법의 발전 방향성을 고찰하였다.

Abstract AI-Helper 아이콘AI-Helper

Forest canopy height is an indispensable vertical structure parameter that can be used for understanding forest biomass and carbon storage as well as for managing a sustainable forest ecosystem. Plot-based field surveys, such as the national forest inventory, have been conducted to provide estimates...

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표/그림 (5)

AI 본문요약
AI-Helper 아이콘 AI-Helper

문제 정의

  • 본 연구에서는 다양한 원격탐사기반 수고 및 임분고 추정 연구 동향을 살펴봄으로써 향후 국내 산림환경 및 현황에 적합한 원격탐사기반 전국단위 산림 임분고 추정을 위한 방법에 대한 적용 방향성을 탐색해 보았다. 국내외 다양한 원격탐사기반 임분고 추정 연구사례 분석 결과, 현재까지 가장 정확한 임분고 추정 원격탐사기법으로 알려진LiDAR 기반 추정 방법에서부터 LiDAR 비용의 제한성의 대안으로 스테레오 및 SAR 이미지 점군 기반(Image-based Point Clouds) 임분고 추정, 원격탐사 방법의 장단점을 상호보완하여 임분고 추정의 정확성과 효율성을 높이기 위한 방안으로 원격탐사자료 융합기반 임분고 추정 방법이 대두되었다.
  • 하지만 국내의 경우 해외 연구동향과 비교하여 원격탐사기반 임분고 연구사례 및 기반 기술이 대부분 항공 LiDAR 및 UAV에 위주의 소규모 산림 연구지의 수고 추정 연구가 대부분으로 다양한 원격탐사자료의 적용이 미흡할 뿐 아니라 전국단위 임분고 추정에 대한 연구는 전무한 실정이다. 이에 본 연구는 국내외의 다양한 원격탐사기반 임분고 추정 모델 연구 사례를 검토하고, 국내 산림환경 및 현황에 적합한 원격탐사기반 전국단위 산림 임분고 추정을 위한 방법에 대한 고찰을 통해 향후 국내 원격탐사기반 임분고 연구의 방향을 제시하고자 한다.
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