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原文传递 Mining Marine Vessel AIS Data to Inform Coastal Structure Management

题名：	Mining Marine Vessel AIS Data to Inform Coastal Structure Management
正文语种：	英文
作者：	Brandan M. Scully;F.ASCE;David L. Young;James E. Ross
作者单位：	Coastal and Hydraulics Laboratory, US Army Engineer Research and Development Center
摘要：	This study demonstrates the use of a multiyear country-scale automatic identification system (AIS) data set to partition a nationwide portfolio of navigation structures managed by the US Army Corps of Engineers (USACE) into affinity groups based on emergent vessel traffic characteristics. The marine vessel AIS was originally intended to prevent the collision of ships at sea. As a remote sensing technology, it provides continuous monitoring for marine vessel traffic and has enabled a variety of unforeseen applications. The methodology presented uses spatial distance criteria to identify vessel traffic local to each structure. Metrics characterizing traffic behavior including traffic com-position, spatial position, trip frequency, and traffic seasonality are derived from vessel data. AIS-derived metrics are combined into feature vectors describing each structure. Pearson correlation of feature vectors with r-neighborhood pruning of the affinity matrix is used to identify similar structure pairs. Semisynchronous label propagation is used to partition the structure portfolio graph into prototype groups with strong similarity in underlying traffic characteristics that may be further refined to align maintenance activity with organizational goals.
出版日期：	2020.03-04
出版年：	2020
期刊名称：	Journal of Waterway, Port, Coastal, and Ocean Engineering
卷：	Vol.146
期：	No.02
页码：	04019042