이전|다음

시계열 Sentinel-2 및 Landsat 8 영상을 기반으로 한 외래식물 호프만개자리 관리 방식 인식 및 동적 모니터링

  • role： First author第一作者
  • Affiliation：

    State Key Laboratory Cultivation Base of Urban Environment Process and Simulation, Beijing 100048, China

    Beijing Laboratory of Water Resources Security, Beijing 100048, China

    College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China

  • Email：2230902139@cnu.edu.cn
  • Introduction：戚炜淳，研究方向为湿地变化检测，生态水文遥感应用。E-mail： 2230902139@cnu.edu.cn
QI Weichun123,  
  • role： Corresponding author通信作者
  • Affiliation：

    State Key Laboratory Cultivation Base of Urban Environment Process and Simulation, Beijing 100048, China

    Beijing Laboratory of Water Resources Security, Beijing 100048, China

    College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China

  • Email：yke@cnu.edu.cn
  • Introduction：柯樱海，研究方向为多源遥感数据融合、人工智能及数据挖掘方法，生态水文遥感应用。E-mail： yke@cnu.edu.cn
KE Yinghai123*,  
  • Affiliation：

    State Key Laboratory Cultivation Base of Urban Environment Process and Simulation, Beijing 100048, China

    Beijing Laboratory of Water Resources Security, Beijing 100048, China

    College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China

LI Jinyuan123,  
  • Affiliation：

    State Key Laboratory Cultivation Base of Urban Environment Process and Simulation, Beijing 100048, China

    Beijing Laboratory of Water Resources Security, Beijing 100048, China

    College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China

MIN Yukui123,  
  • Affiliation：

    State Key Laboratory Cultivation Base of Urban Environment Process and Simulation, Beijing 100048, China

    Beijing Laboratory of Water Resources Security, Beijing 100048, China

    College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China

ZHUO Zhaojun123,  
  • Affiliation：

    State Key Laboratory Cultivation Base of Urban Environment Process and Simulation, Beijing 100048, China

    Beijing Laboratory of Water Resources Security, Beijing 100048, China

    College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China

WU Xin123,  
  • Affiliation：

    College of Harbour and Coastal Engineering, Jimei University, Xiamen 361021, China

LI Peng4

추상적인

외래식물인 호프만개자리 관리(삽목개자리)는 해안 습지 생태계 보호 및 복원의 중요한 내용입니다. 현재 여러 연안 지방에서 호프만개자리 관리 사업을 단계적으로 시행하고 있으며, 관리 방법으로는 물리적 제거와 화학적 제거가 포함됩니다. 전자는 효과가 빠르나 재발이 쉽고, 후자는 비용이 저렴하지만 환경에 잠재적인 부정적 영향을 미칠 수 있습니다. 호프만개자리 제거 동태를 시기적절하게 모니터링하고 제거 방식을 식별하는 것은 관리 사업의 성과 평가와 환경 영향 평가에 매우 중요합니다. 본 연구는 저장성과 상하이 연안 습지의 호프만개자리 분포 지역을 연구 대상으로 하여, 시계열 광학 위성영상인 Sentinel-2와 Landsat 8 데이터를 기반으로 제거 상태 및 관리 방식(미제거/물리적 제거/화학적 제거)을 인식하는 방법을 제안하고, 물리적 제거 날짜도 추출하였습니다. 먼저 Sentinel-2 MSI와 Landsat 8 OLI 영상을 융합하여 시계열 스펙트럼 지수 데이터셋을 구축하고, 슬라이딩 윈도우와 규칙 기반 판별 방법으로 관리 영향기간을 인식해 제거 상태를 판단하였습니다. 이어서 랜덤 포레스트 기법으로 관리 방식을 분류하여 미제거, 물리적 제거, 화학적 제거 세 가지 범주를 도출하고, 물리적 제거 날짜를 추가로 인식하였습니다. 결과는 제거 상태 및 제거 방식 분류 정확도가 높아, 전체 정확도가 98.8%, 카파 계수는 0.979였으며, 물리적 제거 날짜 검출의 평균 절대 오차 일수는 3.91일이고 정확도는 93.67%였습니다. 2023년 저장성과 상하이시의 호프만개자리 제거율은 각각 4.2%와 62.7%였습니다. 본 연구의 제거 방식 인식 및 동적 모니터링 방법은 연안 습지 관리 의사결정에 중요한 참고 자료가 될 것입니다.

키워드

광학 원격 탐사;종 침입;시계열 분석;습지 복원;식생 동태

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