Data on SAR remote sensing in mode transportation studies

This study explores the application of SAR remote sensing data in transportation studies. The research methodology is based on the PRISMA framework, which employs systematic reviews and meta-analyses. Only articles and journals published between 1990 and 2022 were selected for analysis. A systematic search strategy was conducted using three major scientific databases: Web of Science (https://www.webofscience.com/), IEEE Xplore (https://ieeexplore.ieee.org/), and ScienceDirect (https://www.sciencedirect.com/). The selected articles were classified into five categories aligned with the review objectives. The first category focused on classifying different modes of transportation, namely air, land, and water. The second category examined specific transportation vehicles, including airplanes, cars, trucks, trains, and ships or vessels. The third category addressed transportation infrastructure, such as airports, runways, roads, railways, ports, and harbors. Lastly, the fourth and fifth categories analyzed the geographic distribution of studies and publication patterns, respectively. The datasets include raw data from the articles and a shapefile containing point vector data to map the spatial distribution of articles or journals.本研究探讨了合成孔径雷达（SAR）遥感数据在交通研究中的应用。本研究的方法基于PRISMA框架，采用系统综述与元分析方法。仅选取1990年至2022年间发表的期刊与文章开展分析。研究采用系统检索策略，检索了三大主流科学数据库：Web of Science（https://www.webofscience.com/）、IEEE Xplore（https://ieeexplore.ieee.org/）以及ScienceDirect（https://www.sciencedirect.com/）。 所遴选的文章依据本次综述的研究目标划分为五大类别。第一类聚焦于不同交通方式的分类，即航空、陆路与水路运输。第二类针对特定交通运载工具展开研究，涵盖飞机、轿车、卡车、列车以及船舶。第三类探讨交通基础设施，例如机场、跑道、公路、铁路、港口与海港。第四类与第五类则分别分析了研究的地理分布特征与出版物发表模式。 本数据集包含来自所遴选文献的原始数据，以及一套用于绘制文献或期刊空间分布的点矢量数据形状文件（shapefile）。