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. .
JIANG Zijie JIANG Weiguo WU Jianjun ZHOU Hongmin
Slope data of economic corridors in Silk Road can reflect the degree of steepness of the surface units of the six major economic corridors, the unit is degree (°). The spatial resolution of the data is 0.016 degrees, which is about 1.8km. The longitude range is 12.09°E-180°, and the latitude range is 10.99°S-90°N. The source is derived from the Global Relief Model built by the National Oceanic and Atmospheric Administration of the United States (NOAA). The range is cut by the border of the Silk Road. This data is one of the basic data necessary to assess the risks of natural disasters (including debris flows, landslides, flash floods, etc.) in the six economic corridors. The application frequency will be high and the prospects will be broad.
The sand drift potential data sets of Central Asia in 2017 is in tif format. It covers five countries in Central Asia, including Uzbekistan, Tajikistan, Kyrgyzstan, Kazakhstan and Turkmenistan. The sand drift potential is absolutely drift potential, that is, the sum of the flux in all directions, regardless of the direction of the potential. The data was obtained by GLDAS global three-hour assimilation data extraction calculation. The temporal resolution is month, the spatial resolution is 0.25°, and the time range is 2017. This data set can be used as an important reference data for sand storm disaster assessment.