Typical case dataset of major global flood disasters (2018.01-2018.12)


The data set analyzes the spatial and temporal distribution, impact and loss of typical global flood disasters from 2018 to 2019. In 2018, there were 109 flood disasters in the world, with a death toll of 1995. The total number of people affected was 12.62 million. The direct economic loss was about 4.5 billion US dollars, which was at a low level in the past 30 years. The number of global flood incidents in 2018 was higher in the first half of the year than in the second half of the year, and the frequency of occurrence was higher from May to July. Therefore, based on three typical disaster events such as the hurricane flood in Florence in the United States in 2018, the flooding of the Niger River in Nigeria in 2018, and the Shouguang flood in Shandong Province in 2018, the disaster background, hazard factors, and disaster situation were analyzed. .


Data file naming and use method

File naming: The flooded area is stored as a vector file with the name “xxxx.shp”, and xxxx represents the flooded files in the area;
In the case of disaster damage, the land use is “xxxx.shp”, and xxxx is the English name of the land use type.
Rainfall is stored in raster form under the name "dddd.tif" and ddd is the date of the year, which is 2018 of the region's rainfall.
File reading method: If you use the icon to display it, you can open it with Arcgis.


Required Data Citation View Data Cite Help About Data Citation
Cite the data

JIANG Zijie, JIANG Weiguo, WU Jianjun, ZHOU Hongmin. Typical case dataset of major global flood disasters (2018.01-2018.12). National Tibetan Plateau Data Center, 2019. doi: 10.11888/Disas.tpdc.270209. (Download the reference: RIS | Bibtex )

Using this data, you must reference article references listed in the Required Data Citation and reference data


User Limit

To respect the intellectual property rights, protect the rights of data authors,expand servglacials 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the data in the research results generated by using the data (including published papers, articles, data products, and unpublished research reports, data products and other results).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.

Example of acknowledgement statement is included below: The data set is provided by National Tibetan Plateau Data Center (http://data.tpdc.ac.cn).


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


Related Resources

1. 2019-10-01 郑州大学 王文 Usage:作为实验课程数据

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Keywords
Geographic coverage
Spatial coverage

East: 180.00

South: 90.00

West: 180.00

North: 90.00

Detail
  • Temporal resolution: Daily
  • Spatial resolution: m
  • File size: 3,010 MB
  • Browse count: 99 Times
  • Download count: 4 Times
  • Share mode: online
  • Temporal coverage: 2018-01-01 To 2018-12-31
  • Updated time: 2019-08-30
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Contact Information
: JIANG Zijie   JIANG Weiguo   WU Jianjun   ZHOU Hongmin  

Distributor: National Tibetan Plateau Data Center

Email: data@itpcas.ac.cn

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