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Extraction and change detection analysis of occupied anchor position in ports based on AIS data
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AI
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DOI：10.1080/15230406.2026.2666416.png)
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Abstract
En 中文
As critical nodes in the global shipping network, port anchorage areas directly reflect operational efficiency and resource allocation. However, due to limited access to occupied anchor position data, most studies remain at the ship behavior level, lacking systematic analysis of individual anchor positions. To address this gap, this study proposes a Centroid-Expansion Anchor Position Extraction (CEAPE) algorithm based on Automatic Identification System (AIS) data and defines six types of occupied anchor position changes, enabling identification and analysis of port occupied anchor positions data. The algorithm constructs convex hulls of anchoring behaviors, identifies the center areas of occupied anchor positions, and performs spatial expansion, effectively avoiding fusion and mismatch issues found in traditional convex hull overlap methods. Using AIS data from the Port of Los Angeles – Long Beach (2019–2023), experiments validate the algorithm’s accuracy and robustness. Within a three-dimensional framework analyzing changes in number, range, and location, this study systematically characterizes the dynamic evolution of occupied anchor positions and reveals the correlations between these changes and port congestion processes. Overall, the proposed approach uncovers the spatiotemporal evolution patterns of occupied anchor positions and providing a quantitative perspective for understanding port congestion and anchorage spatial planning.
Keywords:
AIS data
port occupied anchor position
change detection
anchor position extraction algorithm
change analysis
Journal
IF:
2.4
Papers:
103
Citations:
1.5K
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Cited Papers