Numerical simulation data of river-blocking landslide (2018-2021)- A Big Earth Data Platform for Three Poles

Data content: Taking Baige landslide in 2018 as an example, the numerical simulation of typical river-blocking landslide was carried out

Data source: the numerical simulation data were collected and recorded by computer software (massflow developed by Mountain Institute of Chinese Academy of Sciences).

Data quality description: the data were mainly image JPG and video GIF files, which were processed by video editing and image processing software.

Data application results: Taking the latest river blocking landslide as a case, the numerical simulation of typical river-blocking landslide will provide a theoretical basis for the evaluation of the disaster effect of river blocking landslide in the deep valley area developed from similar strata and slope structure.

File naming and required software

File name: the numerical simulation data was stored in the format of picture JPG and video GIF. The file names are "numerical simulation data of river-blocking landslide 1. GIF", "numerical simulation data of river-blocking landslide 2. JPG", "numerical simulation data of river-blocking landslide 3. GIF", "numerical simulation data of river-blocking landslide 4. GIF" and "numerical simulation data of river-blocking landslide 5. GIF".
Data reading method: you can open it directly with a picture browser

Data Citations Data citation guideline What's data citation?

Cite as:

Xu, N. (2022). Numerical simulation data of river-blocking landslide (2018-2021). A Big Earth Data Platform for Three Poles, DOI: 10.11888/HumanNat.tpdc.272036. CSTR: 18406.11.HumanNat.tpdc.272036. (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

Catastrophic mechanisms and risk control of disastrous landslides in the Tibetan Plateau (No:2018YFC1505000)

Copyright & License

To respect the intellectual property rights, protect the rights of data authors, expand services of the data center, and evaluate the application potential of data, data users should clearly indicate the source of the data and the author of the data in the research results generated by using the data (including published papers, articles, data products, and unpublished research reports, data products and other results). For re-posting (second or multiple releases) data, the author must also indicate the source of the original data.

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