The China Mongolia Russia economic corridor starts from China in the East, passes through Mongolia in the west to Russia, and crosses the Mongolian Plateau, West Siberian plain and Eastern European Plain. There are great differences in natural environment and complex geological conditions in the region. Driven by regional differences in structure, earthquake, meteorology, hydrology and ecology, landslides are widely distributed in China Mongolia Russia economic corridor. Based on remote sensing images, the landslide and debris flow disasters in China Mongolia Russia economic corridor are interpreted. Statistics show that there are 396 landslide disasters in China Mongolia Russia economic corridor, and the landslide disaster area is between 0.0006km2 ~ 8.57km2. The watershed area within 100km on both sides of the railway line, with a total area of 1.43 × 106km2, has identified 1336 debris flow gullies in the China Mongolia Russia economic corridor.
ZOU Qiang
On the basis of the global tropical cyclone track dataset, the global disaster events and losses dataset, the global tide level observation dataset and DEM data, coastline distribution data, land cover information, population and other related data of the Belt and Road, indicators related to the disaster risk and vulnerability of storm surge in each unit are extracted and calculated using10 meter grid as evaluation unit, such as historical intensity of tide level frequency of storm historic arrival, historical loss, population density, land cover type, etc. The comprehensive index of storm surge disaster risk is constructed, and the risk index of storm surge is obtained by using the weighted method. Finally, the storm surge risk index is normalized to 0-1, which can be used to evaluate the risk level of storm surge in each assessment unit. The data set includes 20-year, 50-year, and 100-year corresponding risks.
There are 428 large and medium-sized landslides in the Bangladesh China India Myanmar economic corridor. The number of landslides in Myanmar is the largest, reaching 304, accounting for 71% of the total landslides, followed by China and India. The number of landslides is 71 and 52, accounting for 17% and 12% of the total landslides, respectively. There is only one landslide in Bangladesh. According to the material composition of landslide, it can be divided into rock landslide and soil landslide. There are 343 rock landslides in this area, accounting for 80% of the total number of landslides, and 85 soil landslides, accounting for 20% of the total number of landslides. Rock landslides are mainly distributed in the north of China, India and Myanmar, while soil landslides are mainly distributed in the middle and south of Myanmar. A total of 1569 debris flows were interpreted in the Bangladesh China India Myanmar corridor, including 574 gully debris flows and 995 slope debris flows. In the eastern part of the study area, debris flows are mainly distributed on both sides of Lancang River, Nujiang River, Mojiang River and Honghe River, and they are distributed in the north-south direction along these rivers. In the central part of the study area, debris flows are distributed in the ruokai mountain area. Compared with the gully type debris flow, the scale and harm of slope debris flow are much smaller. In this study, the correlation analysis of debris flow is mainly aimed at the gully type debris flow.
ZOU Qiang
This data set is a collection of statistics on major geological disasters in the Himalayas, the study area starts in Zada County, Guer County of The Ali region in the west, the east side is bounded by the Yalu-Zanbu River, the northern boundary is the Yalu-Zanbu River break, south to the vast Himalayan region of the national boundary. The Himalayas are located in the southwest of China, the southwest of the Qinghai-Tibet Plateau, the world's largest, highest and youngest mountain range, the world's highest peak Mount Qomolangma is located here. Here the geological structure is complex, seismic activity is frequent, the new tectonic movement is strong, the internal and external dynamic geological action is very active, is one of the most serious geological disasters in China. The original data of the data set is digitized from the report of the Remote Sensing Survey of Major Geological Disasters in the Himalayas, and the total number of disaster statistics is more than 540, including three types of disasters: landslides, mudslides and glacial final lake collapses. This data set provides basic data for the study of disaster reduction and prevention in the Himalayas region of Tibet, and is of reference value for research in related fields.
TONG Liqiang
The accuracy of tropical cyclone (tropical storm) track forecasting improved by nearly 50% for lead times of 24–72 h since 1990s. Over the same period forecasting of tropical cyclone intensity showed only limited improvement. Given the limited prediction skill of models of tropical cyclone intensity based on environmental properties, there have been a wealth of studies of the role of internal dynamical processes of tropical cyclones, which are largely linked to precipitation properties and convective processes. The release of latent heat by convection in the inner core of a tropical cyclone is considered crucial to tropical cyclone intensification. 16-year satellite-based precipitation, and clouds top infrared brightness temperature were used to explore the relationship between precipitation, convective cloud, and tropical cyclone intensity change. The 6-hourly TC centers were linearly interpolated to give the hourly and half hourly tropical cyclone center positions, to match the temporal resolution of the precipitation and clouds top infrared brightness temperature. More precipitation is found as storms intensify, while tropical cyclone 24 h future intensity change is closely connected with very deep convective clouds with IR BT < 208 K. Intensifying tropical cyclones follow the occurrence of colder clouds with IR BT < 208 K with greater areal extents. As an indicator of very deep convective clouds, IR BT < 208 K is suggested to be a good predictor of tropical cyclone intensity change（Ruan&Wu，2018，GRL）. The properties of the satellite-based precipitation, and clouds top infrared brightness temperature are therefore suggested to be important measurements to study tropical cyclone intensity, intensity change and their underlying mechanisms. The high resolution of the satellite-based precipitation (3h), and cloud top infrared brightness temperature (half hour) datasets also makes them possible to be used to study tropical cyclone variability associated with diurnal cycle.
WU Qiaoyan
The data set describes the hypocentre parameters of intermediate- and deep-focus earthquakes in the Pamir-Hindu Kush region from 1964 to 2011. The earthquake relocation results clarified the complex deformation characteristics of underground structures in the deep subduction area in the Pamir-Xindu Kush region. The seismic waveform data are from the IRIS website (http://ds.iris.edu/wilber3/find_event), and the arrival time data are from the ISC website (http://www.isc.ac.uk/) and the CEDC website (http:// Data.earthquake.cn/data/index.jsp?id=11number=9). Seismic location was determined using the teleseismic waveform fitting and the multi-scale double-difference (Multi-DD) method developed in this study. The errors in latitude and longitude data are approximately ±7 km and ±7 km, respectively. Origin Time: yyyy (year), mm (month), dd (day), hh (hour), mm (minute), ss.ss (second) Earthquake Magnitude: Magnitude (from the ISC seismic catalogue) Earthquake Location: Latitude, Longitude, Depth Hypocentre determination method: Hypocentres marked with an "F" were determined by the waveform fitting method
BAI Ling
This data set contains 2018 global forest fire case data for the whole year and 2019, including the forest fire in California in November 2018, the forest fire in Attica, Greece in July 2018, and the forest fire in Shanxi Province in March 2019. Case data. Specific data include: fire intensity data of the monitoring range and data of vegetation index changes before and after the disaster. The data set is mainly used to describe the occurrence, development, impact and recovery of major global forest fire events in the first half of 2018-2019. The data mainly comes from NASA official website and EM-DAT database, it was processed by statistical and spatial analysis methods using EXCEL and ArcGIS tools. The data source is reliable, the processing method is scientific and rigorous, and it can be effectively applied to global (forest fire) disaster case analysis research.
YANG Yuqing, GONG Adu, WU Jianjun, ZHOU Hongmin
1) The dataset includes the raster data of soil erosion intensity in Pan-Third Pole 65 countries.2) The data of soil erosion intensity are obtained by using the Chinese soil loss equation (CSLE). The formula of soil erosion prediction model includes rainfall erosivity factor, soil erodibility factor, slope length factor, slope factor, vegetation cover and biological measure factor, engineering measure factor and tillage measure factor. Rainfall erodibility factors are calculated from the daily rainfall data by the US Climate Prdiction Center (CPC); soil erodibility factors are calculated by 250 m soil grid data; engineering measure factors are calculated based on vegetation cover, land use and rainfall erosivity ratio; tillage measure factors haven't been considered yet, and the default value is 1; slope length factors and slope factors are obtained by resampling after calculating 30 m elevation data; vegetation coverage and biological measures factors are obtained by combining fractional vegetation cover with land use data and rainfall erodibility proportionometer. The fractional vegetation cover is calculated by MODIS vegetation index products through pixel dichotomy. 3) Compared with the data of soil erosion intensity in the same region in the same year, there is no significant difference and the data quality is good.4) the data of soil erosion intensity is of great significance for studying the present situation of soil erosion in Pan third polar 65 countries and better implementation of the development policy of the Silk Road Economic Belt and the 21st-Century Maritime Silk Road.
ZHANG Wenbo
One belt, one road, one belt, one road, one belt, one road, is the key city to solve the extreme drought climate events. 34 key nodes (important cities, major projects, ports and industrial parks) are selected to carry out extreme drought risk assessment. Construction. In one belt, one road area is divided into 34 zones with 1km resolution. The data are based on the linear regression slope of 2011-2015 years' multi period drought risk as the "extreme drought state change". The scientific basis for the drought disaster in China's overseas parks, ports, major construction projects, operation management, environmental problems, and prevention and control is provided. One belt, one road, the third pole area, is to promote and ensure the smooth implementation of the regional development strategy.
WU Hua, ZHANG Dan, CHEN Baozhang
A gridded ocean temperature dataset with complete global ocean coverage is a highly valuable resource for the understanding of climate change and climate variability. The Institute of Atmospheric Physics (IAP) provides a new objective analysis of historical ocean subsurface temperature since 1990 for the upper 2000m through several innovative steps. The first was to use an updated set of past observations that had been newly corrected for biases (e.g., in XBTs). The XBT bias was corrected by CH14 scheme, which is recommended by the XBT community. The second was to use co-variability between values at different places in the ocean and background information from a number of climate models that included a comprehensive ocean model. The third was to extend the influence of each observation over larger areas, recognizing the relative homogeneity of the vast open expanses of the southern oceans. Then the observations were also used to provide finer scale detail. Finally, the new analysis was carefully evaluated by using the knowledge of recent well-observed ocean states, but subsampled using the sparse distribution of observations in the more distant past to show that the method produces unbiased historical reconstruction. The ocean wind data set is constructed using RSS Version-7 microwave radiometer wind speed data. The input microwave data are processed by Remote Sensing Systems with funding from the NASA MEaSUREs Program and from the NASA Earth Science Physical Oceanography Program. This wind speed product is intended for climate study as the input data have been carefully intercalibrated and consistently processed. Each netCDF file contains: 1) monthly means of wind speed, grid size 360x180xnumber of all months since Jan 1988(increases over time) 2) a 12-month set of climatology wind speed, grid size 360x180, the climatology is an average calculated over the 20-year period 1988-2007 3) monthly anomalies of wind speed derived by subtracting the above climatology maps from the monthly means, grid size 360x180x#months since Jan 1988 (increases over time) 4) a wind speed trend map, grid size 360x180, the trend is calculated from 1988-01-01 to the latest complete calendar year 5) a time-latitude plot (a minimum of 10% of latitude cells is required for valid data), grid size 180x#months since Jan 1988 (increases over time).
GE Yong, LI Qiangzi, DONG Wen
On the basis of the global tropical cyclone track dataset, the global disaster events and losses dataset, the global tide level observation dataset and DEM data, coastline distribution data, land cover information, population and other related data of 34 key nodes, indicators related to the disaster danger of storm surge in each unit are extracted and calculated using handred meters grid as evaluation unit, such as historical intensity of tide level frequency of storm historic arrival, historical loss, distance of offshore line, etc. The comprehensive index of storm surge disaster danger is constructed, and the danger index of storm surge is obtained by using the weighted method. Finally, the storm surge danger index is normalized to 0-1, which can be used to evaluate the danger level of storm surge in each assessment unit. The key nodes data set only contains 11 nodes which have risks.
GE Yong, LI Qiangzi, DONG Wen
Data from EM-DAT. EM-DAT is a global database on natural and technological disasters, containing essential core data on the occurrence and effects of more than 21,000 disasters in the world, from 1900 to present. EM-DAT is maintained by the Centre for Research on the Epidemiology of Disasters (CRED) at the School of Public Health of the Université catholique de Louvain located in Brussels, Belgium.The main objective of the database is to serve the purposes of humanitarian action at national and international levels. The initiative aims to rationalise decision making for disaster preparedness, as well as provide an objective base for vulnerability assessment and priority setting.The database is made up of information from various sources, including UN agencies, non-governmental organizations, insurance companies, research institutes and press agencies. Priority is given to data from UN agencies, governments, and the International Federation of Red Cross and Red Crescent Societies. This prioritization is not only a reflection of the quality or value of the data, it also reflects the fact that most reporting sources do not cover all disasters or have political limitations that could affect the figures. The entries are constantly reviewed for inconsistencies, redundancy, and incompleteness. CRED consolidates and updates data on a daily basis. A further check is made at monthly intervals, and revisions are made at the end of each calendar year.
GE Yong, LI Qiangzi, DONG Wen
The extreme drought damage historical events data of the 34 key areas along One Belt One Road were collected from Internet. First, a Web crawler was coded by python language. Using several key words about extreme drought damage, web pages were then collected by Google and Baidu search engine. Last, important information about the extreme drought events (e.g., place, time, affected area, affected population, count of death) were extracted from web pages. This data can be used for risk assessment of extreme drought in the 34 key areas along One Belt One Road.
GE Yong, LING Feng
This data set collects the wave tide level data of the southern sea area of Sri Lanka from September 2013 to October 2014. Sri Lanka is located in the core node of the "maritime Silk Road", which is the necessary node of our oil transportation lifeline. The wave observation data of this sea area is of great significance to understand the wave characteristics of this sea area and ensure the navigation safety of cargo ships and sea convoys. The data is obtained by the pressure sensor deployed on the seabed, and the data reliability is ensured by the quality control segments such as the removal of abnormal values. This data is of great significance to the analysis of marine disaster assessment, ship passing safety assessment and the study of wave characteristics in the sea area.
LUO Yao
Apparent temperature refers to the degree of heat and cold that the human body feels, which is affected by temperature, wind speed and humidity. The spatial scope of the data covers 34 key nodes in the pan-third pole region (Vientiane, Yangon, Kolkata, Warsaw, Karachi, Yekaterinburg, Chittagong, Tashkent, etc.). The spatial resolution is 100m, and the temporal resolution is year. Processing process: Based on the monitoring data of the meteorological station, calculate the apperant temperature based on the Humidex index, and then use the temperature correction method based on elevation correction to obtain 1km gridded data of the entire area, and downscale it to 100m. The heat wave risk dataset mainly uses intensity as the evaluation index. The spatial range and spatial resolution are consistent with the somatosensory temperature data set, and the temporal resolution is years. The criterion for judging the heat wave is: the weather process in which the somatosensory temperature exceeds 29℃ for three consecutive days is judged to be a high-temperature heat wave.
YANG Fei, WU Xilin, YIN Cong
One belt, one road, 34 key nodes, is used to assess the risk of flooding in the key areas of the "one belt" Road area under extreme precipitation events. It provides a basis for local government departments to make decisions and early warning before the flood. Thus, we can gain valuable time to take measures to prevent and reduce disasters and reduce the lives of the people. Loss of property. The data set takes one belt, one road, 34 key nodes, and the ratio of cultivated land to land, the proportion of urban land, the proportion of interlaced zone, the density of road network and the impervious surface. Based on the spatial analysis method in ArcGIS, the weights of each index are assigned. The vulnerability of 34 key nodes under extreme precipitation conditions is evaluated, and the vulnerability is determined by natural breakpoint method. Sex is divided into five levels, which represent no vulnerability, low vulnerability, medium vulnerability, high vulnerability and extremely high vulnerability.
GE Yong, LI Qiangzi, LI Yi
The data set records the statistical data of fire accidents in Qinghai Province from 1998 to 2010, which are divided by industry, region, affiliation and registration type. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of 13 tables Fire accident 2001.xls Fire accident 2006.xls Fire accident 2007.xls Fire accident 2008.xls Fire accident 2009.xls Fire accident 2010.xls Fire accident 1998.xls Fire accident 1999.xls Fire accident 2000.xls Fire accident 2002.xls Fire accident 2004.xls Fire accident 2006.xls Fire accident 2003.xls The data table structure is the same. For example, there are six fields in the data table of fire accidents in 2001 Field 1: Category Field 2: number of fires Field 3: number of deaths Field 4: number of injured persons Field 5: loss converted into RMB 10000 Field 6: cause of fire
Qinghai Provincial Bureau of Statistics
1) The data includes the soil erosion modulus of 22 watersheds with a resolution of 2.5 m in the year of 2019 in the Xinjiang Uygur Autonomous Region. 2）Based on the surface layer of rainfall erosivity R, soil erodibility K, slope length factor LS, vegetation coverage FVC, and rotation sampling survey unit, the Chinese soil erosion model (CSLE) was used to calculate soil erosin modulus in 22 watersheds respectively. Through spatial data processing (including chart linking and transformation, vector-grid conversion, and resampling), R, K, LS factors were calculated from the regional thematic map of rainfall erosivity, soil erodibility, and DEM. By half-month FVC, NPV, half-month rainfall erosivity data, we calculated the value of B factors in each sampling watershed. The value of E factor was calculated based on the remote sensing interpretation result and engineering measure factor table. The value of tillage factor T was obtained from tillage zoning map and tillage measure table. And then the soil erosion modulus in each sampling watershed was calculated by the equation: A=R•K•LS•B•E•T. The selection of 22 watersheds was based on the layout of sampling survey in pan-third polar region. 3) Compared with the data of soil erosion intensity in the same region in the same year, there is no significant difference and the data quality is good.4) the data of soil erosion modulus is of great significance for studying the present situation of soil erosion in Pan third polar region, and it is also crucial for the implementation of the development policy of the Silk Road Economic Belt and the 21st-Century Maritime Silk Road.
YANG Qinke
The data includes the path data of tropical cyclone "iday" in the southern hemisphere in March 2019, and the data of flood affected area in southern Africa caused by it. It is an important data source supplement for major global tropical cyclone disasters in 2019. The track data of the tropical cyclone is collected from the monitoring data of the National Satellite Meteorological Center, and the longitude and latitude coordinates are obtained by using ArcGIS software; the flooded range data of the southern Africa flood is extracted by the Institute of remote sensing of the Chinese Academy of Sciences Based on the high-resolution three satellite image. The data can be used for the path analysis, affected situation analysis and disaster damage assessment of tropical cyclone "Yidai".
CHEN Yiting, YANG Hua, WU Jianjun, ZHOU Hongmin
On the basis of the global tropical cyclone track dataset, the global disaster events and losses dataset, the global tide level observation dataset and DEM data, coastline distribution data, land cover information, population and other related data of the Belt and Road, indicators related to the disaster risk and vulnerability of storm surge in each unit are extracted and calculated using100 meter grid as evaluation unit, such as historical intensity of tide level frequency of storm historic arrival, historical loss, population density, land cover type, etc. The comprehensive index of storm surge disaster risk is constructed, and the risk index of storm surge is obtained by using the weighted method. Finally, the storm surge risk index is normalized to 0-1, which can be used to evaluate the risk level of storm surge in each assessment unit.At the same time, the data set includes the corresponding risk index, exposure index and vulnerability assessment results.The key nodes data set only contains 11 nodes which have risks ((Chittagong port, Bangladesh; Kyaukpyu Port, Myanmar; Kolkata, India; Yangon Port, Myanmar; Karachi, Pakistan; Dhaka, Bangladesh; Mumbai, India; Hambantota Port, Sri Lanka; Bangkok, Thailand; China-Myanmar Oil and Gas Pipeline; Jakarta-Bandung High-speed Railway).
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