2026-10-10T20:40:41Z https://www.scidb.cn/oai

10.57760/sciencedb.39094 2026-06-15T10:57:32Z

2026-06-15 A dataset of blowing snow event visibility classification for the Makitasi Wind Zone, China, 2024–2025 doi:10.57760/sciencedb.39094 en Low visibility induced by blowing snow disasters is a key factor affecting traffic safety and operational efficiency on high-grade highways. Fine-grained visibility grading data are of great significance for model training, control strategy formulation, and the deployment of roadside edge computing devices. Based on continuous videos from four roadside fixed monitoring cameras and visibility instrument observations along the G3015 Keketa Expressway (K264+700–K272+700) in the Makatag Wind Area, Xinjiang, from November 2024 to March 2025, this dataset was constructed by filtering video time based on visibility instrument data, extracting frames at a frequency of 1 minute per frame, and applying manual grading annotation. The dataset consists of one compressed archive containing seven folders corresponding to seven visibility levels (0–100 m, 100–200 m, 200–300 m, 300–400 m, 400–500 m, 500–1000 m, and 1000–2000 m), comprising 13,124 roadside camera images with a spatial resolution of 640×480 pixels. It also includes one visibility instrument data file in tabular format, containing time, wind speed, wind direction, minimum visibility, and average visibility. This dataset can be used to characterize the spatiotemporal distribution and variation of highway visibility under blowing snow conditions, serving traffic meteorological warning and dynamic expressway control in blowing snow-prone areas. Makitasi Wind Zone; 2024-2025; blowing snow; visibility classification; highway Ma Lei Hu Zhixuan Zhao Jing Li Pengbo Zhao Qin Pan Xingyu Li Taizhi RESTRICTED dataset Science Data Bank