We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
A review of remote sensing in coastal aquaculture: data, geographic hotspots, methods, and challenges
Summary
A review of remote sensing applications in coastal aquaculture examined available data sources, geographic coverage, and analytical methods for monitoring aquaculture zones. This is relevant to microplastic research because aquaculture operations are both exposed to and potential sources of microplastic contamination in coastal waters.
Coastal aquaculture, involving the cultivation of aquatic organisms in near-coastal land-based ponds and marine-based suspended cages and floating rafts, is essential for meeting global fish demand. Yet, its rapid expansion, particularly in Asia, has raised concerns about seawater eutrophication, biodiversity loss, and food safety. Remote sensing has emerged as a critical tool for monitoring coastal aquaculture by scalable data collection, long-term monitoring, and access to remote marine areas. This study presents the first comprehensive review that integrates bibliometric and content analysis of 304 papers on remote sensing in coastal aquaculture (RSCA) published between 2000 and early 2024. It identifies three major research themes: aquaculture mapping (35.6%), land and sea use change detection (27.6%), and eco-environmental assessment (14.2%), with a notable growth in publications since 2014. Medium-resolution optical satellites (e.g. Landsat series and Sentinel-2) dominate coastal aquaculture studies in all themes. Geographically, RSCA studies are highly concentrated in Southeast Asia, particularly along China's coastline and the Mediterranean, with most conducted at small scales. In coastal aquaculture mapping, deep learning methods (43.5%) show strong potential for detecting complex features like raft boundaries, while traditional machine learning remains effective for large-scale, high-contrast aquaculture. For eco-environmental studies, spectral indicators derived from remote sensing effectively support indirect monitoring of land–sea transformation (e.g. mangrove degradation and coastline expansion), seawater quality degradation (e.g. eutrophication, algal blooms, and heavy metals), and biodiversity threats (e.g. habitat loss and microplastics). Key challenges include the lack of high-resolution open datasets, difficulties in summarizing the spectral characteristics of coastal aquaculture targets, accurate global aquaculture mapping, and the absence of an integrated environmental monitoring framework. Addressing these gaps is essential for advancing sustainable management and supporting global food security and eco-environmental goals.