This data provides a detailed characterization of the spatial pattern of freeze-thaw disasters in the permafrost region of Northeast China under the coupling effects of climate change and human engineering activities. The resource content covers the distribution of disaster types from large discontinuous permafrost areas to seasonal permafrost transition zones, with a focus on identifying six major disaster types: uneven road settlement, hot melt lakes and ponds, road cracks, freeze-thaw erosion, ice cones, and water damage.
Resource characteristics: (1) Large spatial span: covering the main permafrost areas of Daxing'an Mountains and Xiaoxing'an Mountains. (2) High precision: Using a scale of 1:100000, it reveals the distribution characteristics of "north dense and south sparse, high dense and low sparse". (3) Strong engineering relevance: Highlighting the disaster gathering trend of linear engineering corridors such as highways (G111, G331, etc.), railways, and Sino Russian crude oil pipelines. (4) Typical representatives: Five typical regions including Mohe, Genhe Ituli River, Xinlin, Heihe, and the southern section of Gagdachi were selected for micro analysis.
Independently generated, integrating multiple field scientific expedition records and machine learning models to obtain prediction results.
Field investigation: Integrate long-term disease records from typical monitoring areas such as Mohe, Tahe, and Genhe in the Greater Khingan Range and Lesser Khingan Range.
Engineering interference simulation: Consider the strong heat absorption effect of asphalt pavement and the deep erosion of frozen soil upper limit caused by heat source emissions from ambient temperature crude oil pipelines.
(1) Resource accuracy: The scale is 1:100000. Based on machine learning models, its accuracy is sufficient to support regional frozen soil engineering risk assessment and disaster prevention decisions.
(2) Scope of application: Suitable for engineering planning in cold regions (highways, railways, pipelines), environmental monitoring in permafrost regions, assessment of climate change impacts, and scientific research related to geographic information systems.
(3) Model method: Advanced machine learning algorithms are used for spatial modeling, and the model fully considers the coupling relationship between natural background and human disturbance.
(4) Quality control: By amplifying and comparing typical areas with different permafrost gradients, the consistency between disaster types (such as settlement, cracks, erosion, etc.) and actual terrain, hydrological processes, and engineering disturbances was verified, ensuring accurate representation of spatial organizational characteristics.
| # | number | name | type |
| 1 | 2022FY100700 | Survey of Permafrost Conditions and Freeze-Thaw Damage in the High-Latitude Regions of Northeast China | Basic Resource Survey Project |
This work is licensed under
CC BY 4.0 (Creative Commons Attribution 4.0 International License).
CSTR:11738.11.NCDC.NIEER.DB7263.2026
10.12072/ncdc.nieer.db7263.2026
