Spatial footprint of maritime vessels in the waters of a fast-growing coastal megalopolis
Lang, SDJ; Doherty, PD; Godley, BJ; et al.Lee, SY; Leung, F; Sharma, MD; Metcalfe, K
Date: 5 May 2025
Article
Journal
Marine Policy
Publisher
Elsevier
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Abstract
Coastal megalopolises are transportation gateways of the global economy, but marine traffic around these developed urban areas exerts considerable pressure on the environment. A key starting point in understanding how this pressure may impact marine species and ecosystems is to map the spatial footprint of maritime vessels. Using six ...
Coastal megalopolises are transportation gateways of the global economy, but marine traffic around these developed urban areas exerts considerable pressure on the environment. A key starting point in understanding how this pressure may impact marine species and ecosystems is to map the spatial footprint of maritime vessels. Using six years of vessel tracking data from 2013–18, we mapped fine-scale spatial (0.002°) and temporal (daily) distribution of marine traffic within the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) — a coastal megalopolis with the largest population (∼86 million) and second-largest economy of bay areas globally. Data indicates that on average, 5981 (± 1941 SD) unique vessels were active in the GBA daily. Space-use of both fishing and non-fishing vessels showed temporally consistent, persistent, and spatially-dense coverage, with 80 % of vessel traffic occurring in shallow water (0–20 m). Movement in such shallow water of the GBA likely results in increased rates of shoreline erosion, turbidity, noise pollution, and vessel collisions — posing a substantial threat to many regionally important marine species of conservation concern. Daily rates of disturbance in the GBA by non-fishing vessels were eight times higher than for fishing vessels, with some areas experiencing disturbance across more than 95 % of days in the study period. Our findings highlight how AIS data holds a wealth of information that takes considerable computing power to extract, so we make our processed datasets openly accessible to aid in future marine conservation planning and analyses.
Ecology and Conservation
Faculty of Environment, Science and Economy
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