인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
Rakit Island in Saleh Bay, West Nusa Tenggara, possesses shallow marine ecosystems that are ecologically important but remain under-studied. This study aimed to map shallow marine benthic habitats in the waters of Rakit Island using Sentinel-2A satellite imagery. An object- based image analysis (OBIA) approach combined with a Support Vector Machine (SVM) classification algorithm was applied. The methodological workflow included atmospheric correction, water column correction, multiresolution segmentation, a two-level classification process, and accuracy assessment using field validation data. The classification results identified seven benthic habitat classes, namely rocks, sand, muddy sand, seaweed, debris, live coral, and dead coral with algae. The overall classification accuracy reached 69.01%, with a kappa coefficient of 0.63, indicating a good level of agreement between the classification results and field observations. The main limitations were spectral similarity among habitat classes and the influence of water turbidity, particularly affecting seaweed detection in deeper waters. Overall, the results demonstrate that the OBIA–SVM approach is effective for mapping shallow marine habitats using medium-resolution Sentinel-2A imagery.
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.