이전|다음

HY-1C/1D 위성 COCTS 데이터 클로로필-a 농도 역산 신경망 알고리즘 연구

  • role： First author第一作者
  • Affiliation：

    National Key Laboratory of Marine Biogeochemistry, Xiamen University, Xiamen 361102, China

  • Email：mywei@stu.xmu.edu.cn
  • Introduction：韦美怡，研究方向为海洋水色遥感。E-mail： mywei@stu.xmu.edu.cn
WEI Meiyi1,  
  • Affiliation：

    National Key Laboratory of Marine Biogeochemistry, Xiamen University, Xiamen 361102, China

WU Jingyu1,  
  • Affiliation：

    National Key Laboratory of Marine Biogeochemistry, Xiamen University, Xiamen 361102, China

ZHENG Lufei1,  
  • Affiliation：

    National Key Laboratory of Marine Biogeochemistry, Xiamen University, Xiamen 361102, China

WANG Daosheng1,  
  • Affiliation：

    National Key Laboratory of Marine Biogeochemistry, Xiamen University, Xiamen 361102, China

LEE Zhongping1,  
  • Affiliation：

    National Key Laboratory of Marine Biogeochemistry, Xiamen University, Xiamen 361102, China

SHANG Shaoling1,  
  • Affiliation：

    National Satellite Ocean Application Service, Beijing 100081, China

YE Xiaomin2,  
  • Affiliation：

    National Key Laboratory of Marine Biogeochemistry, Xiamen University, Xiamen 361102, China

LIN Gong1,  
  • role： Corresponding author通信作者
  • Affiliation：

    National Key Laboratory of Marine Biogeochemistry, Xiamen University, Xiamen 361102, China

  • Email：xlyu@xmu.edu.cn
  • Introduction：余小龙，研究方向为水色遥感机理与应用。E-mail： xlyu@xmu.edu.cn
YU Xiaolong1*

추상적인

수체 내 클로로필-a(Chl-a) 농도는 핵심 기후 인자로서, 정확한 원격 감지 역반전은 전 세계 탄소 순환 연구, 해양 환경 모니터링 및 관리에 중요한 의미를 가집니다. 중국의 해양일호 시리즈 위성(HY-1C/1D)에 탑재된 해양 수색 수온스캐너(COCTS)는 킬로미터급의 전 지구 해양 수색 모니터링을 실현할 수 있습니다. COCTS 데이터를 대상으로 한 고정밀 Chl-a 원격 감지 알고리즘의 개발은 자율 위성 데이터로 해양 모니터링 및 기후 변화 연구를 지원하는 핵심 전제 조건입니다. 본 연구는 전 세계 수역을 포괄하는 2165개의 실측 데이터를 기반으로 HY-1C/1D COCTS의 다중 파장 반사비(Rrs) 및 환경 변수를 활용한 다층 퍼셉트론 신경망(MLP-NN) 모델을 구축하여 전 세계 수체의 Chl-a 농도를 고정밀로 역산하였습니다. 입력 인자 민감도 분석을 통해 412, 443, 490, 520, 565, 670 nm 파장의 Rrs, 위도, 월, 전월 평균 해수면 온도 및 전월 기후 상태 광합성 유효 복사량 변수가 최적의 입력 조합으로 확정되었습니다. 검증 결과 MLP-NN 모델로 추정한 Chl-a 농도의 로그 변환 후 평균 제곱근 편차(RMSD)는 0.22, 중앙값 절대 백분율 편차(MAPD)는 29.1%로 NASA 상업용 해색 지수 알고리즘(OCI) 대비 각각 0.1 및 16.9% 감소한 결과를 보였습니다. 추가 위성 및 실측 데이터 연계 검증에서 MLP-NN 모델 추정 Chl-a의 RMSD와 MAPD는 OCI 알고리즘 대비 0.09와 9.8% 감소하여 우수한 알고리즘 안정성을 나타냈습니다. 본 연구는 국내 위성의 해양 생태계 모니터링 분야에 혁신적인 방법을 제공하며, HY-1C/1D 위성 관측을 통한 전 세계 Chl-a 농도 활용 능력을 크게 향상시켰습니다.

키워드

클로로필-a (Chl-a); 원격 감지 반사비; 역산 알고리즘; HY-1C/1D 위성; 신경망; COCTS; 해양 수색

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