Heat wave vulnerability data set of 34 key nodes in 2015

Vulnerability refers to a property of the system that is susceptible to changes in structure and function due to the system's sensitivity to internal and external disturbances and its lack of ability to respond, that is, the ability of the region to cope with disasters to reduce losses when heat waves occur. This dataset is based on the pan-third pole regional road network data, GDP data, medical facility spatial distribution data, vegetation coverage data, and water distribution data as basic data,and takes 2015 as the base year. The Euclidean Metric calculation method is adopted to determine the spatial distribution of road networks, water and medical facilities in the area. The distance from roads, water bodies, medical facilities, GDP, and vegetation coverage are used as evaluation indicators. The equal-weight overlapping addition is used to evaluate the vulnerability of heat waves at each node. In order to eliminate the impact of unit differences, the data of each index layer is normalized before the evaluation.Finally, the vulnerability level of each node is divided by the natural Jenks method.

0 2020-07-23

Meteorological drought index data set of 34 key nodes of Pan third pole precipitation anomaly percentage (2014-2015)

Under the background of global warming, the frequency and intensity of drought are increasing. The lack of water resources, food crisis and ecological deterioration (such as desertification) caused by drought disasters directly threaten the national food security and social and economic development. The technical level of drought disaster risk assessment and emergency management needs to be improved. One belt, one road area has one belt, one road area is fragile, agricultural land is concentrated and drought is frequent. Monitoring the drought level and its temporal and spatial changes in large areas by using remote sensing satellites is of great scientific and practical significance for scientifically grasping the drought pattern, regional differentiation characteristics and its impact on agricultural land in the "one belt and one road" area. The percentage of precipitation anomaly reflects the deviation degree between the precipitation of a certain period and the average state of the same period, expressed as a percentage. Based on the daily rainfall data of GPM imerg final run (GPM), the precipitation of corresponding area is calculated. The distribution characteristics of drought of different grades are analyzed by using the grade evaluation index of precipitation anomaly percentage. The spatial resolution is 200m. The data area is 34 key nodes of Pan third pole (Abbas, Astana, Colombo, Gwadar, Mengba, Teheran, Vientiane, etc.).

0 2020-07-21

Slope and aspect data of 34 key nodes of Pan third pole (2000-2016)

"Digital data including slope and aspect (slope and aspect) data are the basic data of GIS, and can be used as two important indicators to describe the terrain feature information, which can not only indirectly express the relief shape and structure of the terrain, It includes hydrological model, landslide monitoring and analysis, surface material movement, soil erosion, land use planning, etc The basic data of geoscience analysis model. At present, slope and aspect data are generally calculated by certain calculation model on digital elevation model (DEM). This data takes 34 key nodes of Pan third pole as the research area, takes DEM data with resolution of 30 meters as the base, realizes the digital simulation of slope and aspect in terrain data (that is, the digital expression of slope and aspect in terrain surface data), and finally obtains the slope and aspect data of pan third pole key nodes. The data area is 34 key nodes of Pan third pole (Abbas, Astana, Colombo, Gwadar, Mengba, Teheran, Vientiane, etc.).

0 2020-07-21

high temperature heat wave risk dataset at 34 key nodes of the third pole (2015)

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.

0 2020-06-18

Dataset of precipitation anomaly in percentage at 34 key nodes of Pan-Third Pole (2011-2015)

Water scarcity,food crises and ecological deterioration caused by drought disasters are a direct threat to food security and socio-economic development. Improvement of drought disaster risk assessment and emergency management is now urgently required. This article describes major scientific and technological progress in the field of drought disaster risk assessment. Drought is a worldwide natural disaster that has long affected agricultural production as well as social and economic activities. Frequent droughts have been observed in the Belt and Road area, in which much of the agricultural land is concentrated in fragile ecological environment. The percentage of precipitation anomaly is the percentage of the precipitation between a certain period of time and the average climate precipitation of the same period divided by the average climate precipitation of the same period.Based on the daily rainfall data of GPM IMERG Final Run(GPM), this data set calculates the precipitation of the corresponding region, adopts the evaluation index of precipitation anomaly percentage grade, and analyzes the distribution characteristics of drought of different grades. The data area is 34 key nodes of the pan-third pole (Abbas, Astana, Colombo, Gwadar, Mamba, Tehran, Vientiane, etc.).

0 2020-06-18

34 key nodes of Pan third pole historical extreme precipitation dataset (2000-2018)

The pan third pole historical extreme precipitation data set includes 2000-2018 extreme precipitation identification data. One belt, one road, was used to assess the rainfall in the important area along the GPM IMERG Final Run (GPM) daily rainfall. The extreme precipitation threshold of 34 important nodes was evaluated by percentile method. The daily precipitation period was identified by the calculated threshold, and the surface inundation area was produced on the basis of extreme precipitation. The data range mainly includes 34 key nodes of Pan third pole (Vientiane, Alexandria, Yangon, Calcutta, Warsaw, Karachi, yekajerinburg, Chittagong, Djibouti, etc.) The data set can provide the basis for local government decision-making, so as to correctly identify extreme precipitation and reduce the loss of life and property caused by extreme precipitation.

0 2020-06-18

Dataset of surface inundation caused by historical extreme precipitation for The 34 critical nodes of the pan third pole (2014-2018)

Data set of surface inundation caused by historical extreme precipitation evaluated the surface inundation range of One Belt And One Road key areas under extreme precipitation, providing a basis and reference for the decision-making of local government departments, so as to give early warning before the occurrence of extreme precipitation and reduce the loss of life and property caused by extreme precipitation.This data set to the extreme precipitation threshold set "and" the extreme precipitation recognition "as the foundation, to confirm the extreme precipitation time node and the area, and then to NASA's web site to download the submerged range products corresponding to the time and region, combining ArcGIS spatial analysis was used to connect the above data, build the data sets of historical extreme precipitation caused surface submerged range for 34 key nodes. The data mainly includes 34 key nodes (Vientiane, China-Myanmar oil and gas pipeline, China-Laos Thai-Cambodia railway, Alexandria, Yangon, Kwantan, Kolkata, Warsaw, Karachi, Yekaterinburg, Yekaterinburg and other regions).

0 2020-06-17

Dataset for vulnerability assessment of the disaster bearing body of the extensive third pole (2018)

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 vulnerability of storm surge in each unit are extracted and calculated using 100 meter grid as evaluation unit, such as population density, land cover type, etc. The comprehensive index of storm surge vulnerability is constructed, and the vulnerability index of storm surge is obtained by using the weighted method. Finally, the storm surge vulnerability index is normalized to 0-1, which can be used to evaluate the vulnerability level of storm surge in each assessment unit. 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).

0 2020-06-17

Risk assessment dataset of storm surge disasters at hundred meters scale of Pan-third pole critical node region (2018)

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).

0 2020-06-17

Data set of meteorological observation day, month and year of Pan third critical node area stations (2000-2016)

The site's daily and monthly statistical data sets are the key parameters reflecting the weather conditions of the site, and are the GSOM data. Meteorology plays an important role in the lithosphere, biosphere, soil circle and the atmosphere, providing a basis for assessing the regional contribution and response of climate factors to the world. This data set takes 34 key node regions of the pan third pole as the study area (Abbas, Astana, Bangkok, etc.),based on the site climate data from 2000 to 2016, the meteorological factors in different regions were counted, and the data series of meteorological observations in key nodes were obtained. The main parameters are: annual average maximum value, average minimum value and average temperature; monthly total precipitation and snowfall.

0 2020-06-17