基于遥感技术的2000年以来钦州湾筏架养殖空间扩展模式分析

doi:10.11978/2025200

Abstract

Abstract:

Mapping the distribution of shallow-sea aquaculture and monitoring its spatial expansion are essential for implementing dynamic marine monitoring, improving regional aquaculture management, optimizing spatial layout, and promoting ecological conservation. This study selects Qinzhou Bay as the research area and proposes an adaptive threshold algorithm for extracting aquaculture raft frames to characterize their spatiotemporal dynamics. A raft index (RI) is constructed based on Landsat series imagery. A fuzzy clustering algorithm was employed to enhance structural features of the raft frames, and a chessboard segmentation algorithm was applied to partition the clustered RI image. The Otsu’s threshold method (OTSU) is then used to identify raft frames in the segmented images. The results reveal a significant expansion of aquaculture raft frames in Qinzhou Bay since 2000, with the maximum area reaching 7860.96 hm² in 2022. The distribution of raft frames has expanded from the coastal waters near Longmen Town toward the outer parts of Qinzhou Bay and into the Maowei Sea (inner bay). A strong correlation was observed between the raft frame area and seawater quality in Qinzhou Bay, with coefficients of determination (r²) of 0.73 for active phosphate, 0.50 for the composite pollution index, and 0.36 for the eutrophication index. The findings of this study offer valuable insights into the spatiotemporal evolution of aquaculture raft frames in Qinzhou Bay and their relationship with the marine environment.

Key words: raft extraction, adaptive threshold algorithm, Landsat images, Qinzhou Bay

CLC Number:

P714

JIN Song, ZOU Tao, LIAO Riquan, CHEN Chaohao, MI Huan, TANG Jianhui. Study on the spatial expansion mode of raft aquaculture in Qinzhou Bay since 2000 using remote sensing technology[J].Journal of Tropical Oceanography, 2026, 45(4): 104-115.

Figures/Tables 12

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Landsat影像	选取年份	中心波长/nm				分辨率/m	影像数量
Landsat影像	选取年份	蓝光(band 1)	绿光(band 2)	红光(band 3)	近红外(band 4)	分辨率/m	影像数量
Landsat 5	2000—2011	486	571	660	839	30	37
Landsat 7	2012—2013	479	561	661	835	30	12
Landsat 8	2013—2024	483	561	665	865	30	30
Landsat 9	2022—2024	482	561	654	865	30	11

方法	精度/%	Kappa系数
自适应滤波算法	95.9	0.85
支持向量机	88.3	0.49
最大似然法	90.5	0.60
马氏距离分类法	84.0	0.17

Study on the spatial expansion mode of raft aquaculture in Qinzhou Bay since 2000 using remote sensing technology

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