According to the inducing factors of potential thermal melting disasters (mainly thermal melting landslides) in the pan Arctic, including temperature (freezing and Thawing Environment), rainfall, snow cover, soil type, topography and landform, and underground ice content, based on the basic data provided by the big data resource database of the earth, machine learning methods (logic regression, random forest, artificial neural network, support vector machine, etc.) are adopted, and the currently interpreted thermal melting landslides in the northern hemisphere are taken as training samples, Finally, the zonation map of thermal melt disaster susceptibility (occurrence probability) in the pan Arctic was obtained. According to the sensitivity of driving factors, it is found that climate factors (temperature and rainfall) have the largest contribution to the occurrence and distribution of thermal melt disasters, followed by slope factors, and ice content and radiation also have a high contribution.

File naming and required software

The thermal melt disaster susceptibility data is stored in TIFF grid data. The folder includes common railway and highway engineering vector (. SHP) format data and national vector boundary (. SHP) data. If you want to display them in a graphic, you can open it with ArcGIS. Among them, DN = 1 indicates that the susceptibility is extremely low, DN = 2 indicates that the susceptibility is low, DN = 3 indicates that the susceptibility is medium, DN = 4 indicates that the susceptibility is high, and DN = 5 indicates that the susceptibility is extremely high.

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Cite as:

Niu, F. (2022). Distribution of disaster susceptibility of circum-Arctic (2015-2020). A Big Earth Data Platform for Three Poles, DOI: 10.11888/Cryos.tpdc.272743. CSTR: 18406.11.Cryos.tpdc.272743. (Download the reference： RIS | Bibtex )

Using this data, the data citation is required to be referenced and the related literatures are suggested to be cited.

Support Program

CASEarth:Big Earth Data for Three Poles（grant No. XDA19070000） (No:XDA19000000)

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License： This work is licensed under an Attribution 4.0 International (CC BY 4.0)