TY  - Data
T1  - Highway Infrastructure Damage Dataset for High-Altitude Regions (2019–2023)
A1  - Chai Mingtang
DO  - 10.12072/ncdc.nieer.db7064.2026
PY  - 2026
DA  - 2026-01-28
PB  - National Cryosphere Desert Data Center
AB  - This dataset is aimed at the needs of disease identification, mechanism analysis, and risk assessment of high-altitude cold region highways under years of freeze-thaw and strong environmental disturbance conditions. Based on the field survey data of highway diseases from 2019 to 2023, a background dataset from 2019 to 2023 is established around the Qinghai Tibet Highway (Golmud Anduo), Xinzang Highway (Yecheng Lazi), and the northern Sichuan Tibet Highway (Nagqu Changdu). Through unified coordinates and road network mileage reference, quality control, and spatiotemporal registration, a continuous road domain background representation with 2-year time resolution and 1 km spatial resolution is formed; Secondly, at the scale of typical disease prone road sections, 15 representative road sections were selected to construct a derived dataset. Based on high-resolution images/point clouds and standardized annotation processes, key derived indicators such as disease types, geometric shapes, and spatial distributions were extracted to form a 2-year time resolution and 10 cm spatial resolution disease fine characterization product. The data content includes: multi-year background information at the macro road domain level, as well as derived information such as disease types and geometric features at the typical road segment level. It can be used for multi-scale disease spatiotemporal evolution analysis, model training and generalization verification, as well as intelligent inspection and maintenance decision support for high-altitude highways, providing a data foundation for improving the resilience and fine maintenance of highways in high-altitude areas.
DB  - NCDC
UR  - http://www.ncdc.ac.cn/portal/metadata/bc991fa1-b98d-4983-81f2-9cff42f8cbc2
ER  -