North Pacific and Arctic Marine Vessel Traffic Dataset (2015-2020); 25 Kilometer Resolution.

These data are a spatially explicit representation of monthly shipping intensity in the Pacific Arctic region from January 1, 2015 to December 31, 2020. We calculated shipping intensity based on Automatic Identification System (AIS) data, a type of Global Positioning System (GPS) transmitter required by the International Maritime Organization on all ships over 300 gross tonnes on an international voyage, all cargo ships over 500 gross tonnes, and all passenger ships. We used AIS data received by the exactEarth satellite constellation (64 satellites as of 2020), ensuring spatial coverage regardless of national jurisdiction or remoteness. Our analytical approach converted raw AIS input into monthly raster datasets, separated by vessel type. We first filtered raw AIS messages to remove spurious records and GPS errors, then joined remaining vessel positional records with static messages including descriptive attributes. We further categorized these messages into one of four general ship types (cargo; tanker; fishing; and other). To develop the raster dataset, we created a series of spatially explicit daily vessel tracks according to unique voyages and aggregated tracks by ship type and month. We then created a 25-km raster grid and calculated the total length, in meters, of all vessel tracks within each raster cell. These monthly datasets provide a critical snapshot of dynamic commercial and natural systems in the Pacific Arctic region. Recent declines in sea ice have lengthened the duration of the shipping season and have expanded the spatial coverage of large vessel routes, from the Aleutian Islands through the Bering Strait and into the southern Chukchi Sea. As vessel traffic has increased, so has exposure to the myriad environmental risks posed by large ships, including oil spills, underwater noise pollution, large cetacean ship-strikes, and discharges of pollutants. This dataset provides scientific researchers, local community members, mariners, and decision-makers with a quantitative means to evaluate the distribution and intensity of shipping across space and through time. In addition to these 25-km raster data, we also produced data products in 10-km raster format as well as a 1-km coastal data subset and a hex data set which contains additional attributes (e.g., number of ships, ship speed). To find these products, search for “North Pacific and Arctic Marine Vessel Traffic Dataset” in the Arctic Data Center’s data repository.

本数据集为2015年1月1日至2020年12月31日期间北太平洋北极区域月度船舶航行强度的空间显式表征。我们基于自动识别系统（Automatic Identification System, AIS）数据计算船舶航行强度：自动识别系统是国际海事组织规定，所有国际航行总吨位300吨以上船舶、总吨位500吨以上货船及所有客船必须搭载的全球定位系统（Global Positioning System, GPS）发射装置所产生的数据。本研究采用exactEarth卫星星座（截至2020年共64颗卫星）接收的AIS数据，确保无论是否处于国家管辖范围或偏远区域，均可实现空间覆盖。本研究的分析流程将原始AIS输入数据转换为按船舶类型分类的月度栅格数据集：首先过滤原始AIS报文以剔除虚假记录与GPS误差，随后将剩余船舶位置记录与携带描述性属性的静态报文进行关联；进一步将这些报文划分为四大通用船舶类型，分别为货船、油轮、渔船及其他船舶。为生成栅格数据集，我们依据唯一航次生成一系列空间显式的每日船舶轨迹，并按船舶类型与月度对轨迹进行聚合。随后创建25公里分辨率的栅格网格，并计算每个栅格单元内所有船舶轨迹的总长度（单位：米）。这些月度数据集为北太平洋北极区域的动态商业与自然系统提供了关键快照。近年来海冰减少延长了通航季时长，并拓宽了大型船舶航线的空间覆盖范围，从阿留申群岛经白令海峡延伸至楚科奇海南部。随着船舶交通量增长，大型船舶带来的各类环境风险也随之加剧，包括船舶溢油、水下噪声污染、大型鲸类船舶碰撞事故以及污染物排放。本数据集为科研人员、当地社区成员、航海人员及决策者提供了量化手段，以评估船舶航运在空间与时间维度上的分布与强度。除上述25公里分辨率栅格数据外，本研究还生成了10公里分辨率栅格格式的数据产品，以及1公里分辨率的海岸数据子集与包含额外属性（如船舶数量、航速）的六边形网格数据集。相关数据产品可在北极数据中心（Arctic Data Center）的数据仓库中检索"North Pacific and Arctic Marine Vessel Traffic Dataset"获取。