An Open Dataset of Yangtze River Docks Based on OSM and Google Satellite Imagery (2024)

As critical infrastructure at the sea-land interface, docks support regional economies and transportation networks. They include seaport docks and inland docks, the latter widely distributed along rivers, lakes, and canals. However, existing studies have mainly focused on seaport dock identification, with limited research and data products for inland docks. To address this gap, we developed an inland dock identification method for the Yangtze River by integrating crowdsourced OpenStreetMap (OSM) data with high-resolution Google satellite images. Based on OSM-derived prior information, we constructed a dedicated dock annotation dataset and applied YOLO-series models with a multi-scale detection strategy to identify and classify docks. The method achieved precision, recall, and F1-score above 0.9. A total of 3,562 docks were detected, including 2,738 floating and 824 vertical docks. To support diverse applications, the released dataset provides both bounding box representations and polygon vector delineations. As the first open inland dock dataset for the Yangtze River, it offers valuable support for studies on inland dock systems, waterway optimization, and regional economic analysis.