30 July 2024 Identifying coral reef ecosystem benthic substances based on multi-source remote sensing imagery: a case study of the Sanya area
Xiaohong Wang, Shouying Xin, Minghao Ma, Linlin Jiao, Dan Shen
Author Affiliations +
Abstract

Identifying coral reef ecosystem benthic substances is extremely important for protecting coral reef ecosystems and monitoring their health status. Using remote sensing images and the object-based image analysis (OBIA) method could effectively improve the identification accuracy of coral reef ecosystem benthic substances. Among them, the core of the OBIA is the selection of optimal scale parameters. In this study, we used Sentinel-2 (S2) and Gaofen-2 (GF-2) images to identify the benthic substances of coral reef ecosystems in the coastal area of Sanya City, Hainan Province. The results show that: (1) the simple benthic substances of coral reef ecosystems could be identified through the analysis of spectral separability of the benthic substances from remote sensing images, and the optimal scale parameters were determined by combining the estimation of scale parameters model method and visual identification (74 for large-scale areas and 3 for small-scale coral reef ecosystems); (2) the S2 images combined with pixel-based maximum likelihood method and support vector machine (SVM) could identify three benthic types of coral reef, coral bleaching, and sand, whose overall accuracy (OA) was 83.89% and 88.89%, respectively; (3) the GF-2 images combined with object-based K-nearest neighbors and SVM could effectively identify six benthic types of coral reef, coral bleaching, algal ridge, algae, sand, and rock, whose OA was 85.39% and 89.39%, respectively; and (4) compared with the S2 images, the GF-2 images could identify finer types of benthic substances and provide data for the analysis of the benthic substances in coral reef ecosystems, and the results of GF-2 images combined with object-based SVM showed that coral reefs in Dongmaozhou Island had the best development; coral reefs in Luhuitou Peninsula and Yulin Bay suffered severe bleaching; coral reefs in Ximaozhou Island are ordinary under serious threat from other benthic organisms. In conclusion, remote sensing technology combined with appropriate interpretation algorithms can improve the identification accuracy of coral reef ecosystem benthic substances, which can effectively maintain the health status of coral reefs and realize the long-term protection of the coral reef ecosystems.

© 2024 Society of Photo-Optical Instrumentation Engineers (SPIE)
Xiaohong Wang, Shouying Xin, Minghao Ma, Linlin Jiao, and Dan Shen "Identifying coral reef ecosystem benthic substances based on multi-source remote sensing imagery: a case study of the Sanya area," Journal of Applied Remote Sensing 18(3), 034505 (30 July 2024). https://doi.org/10.1117/1.JRS.18.034505
Received: 10 May 2023; Accepted: 25 April 2024; Published: 30 July 2024
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KEYWORDS
Ecosystems

Remote sensing

Sand

Spatial resolution

Image segmentation

Reflectivity

Visualization

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