Pan-third-polar environmental change and green silk road construction

Brief Introduction: Pan-third-polar environmental change and green silk road construction

Number of Datasets: 1099

  • Dataset of sustainable livelihood-Public infrastructure (2018)

    Dataset of sustainable livelihood-Public infrastructure (2018)

    This data includes the accessibility of 15 kinds of public facilities and services, such as roads and schools, in the communities of 1280 households at domestic and abroad, as well as the farmers' satisfaction with these public facilities and public services by comparing that with 3 years ago and current status with neighboring village. This data is used to support the analysis of the material capital part of sustainable livelihood. The data was collected by the research group through field survey in 2019. Before collecting the data, the research group and invited experts conducted a pretest and improved the survey questionnaire; Before the formal investigation, the members participating in the data collection were strictly trained; In the formal survey, each questionnaire is checked three times before it is filed. This data is of great value for understanding the physical capital accessibility and satisfaction of rural households in environment-economic fragile areas, and is an important supplement to national and macro data.

    2021-02-22 169 1

  • Normalized Vegetation Index Data Set of Aral Sea Basin (2015-2018)

    Normalized Vegetation Index Data Set of Aral Sea Basin (2015-2018)

    Data content: normalized vegetation index data of the Aral Sea basin from 2015 to 2018. Data sources and processing methods: the first band of mod13a2 product was extracted from NASA medium resolution imaging spectrometer as leaf area index data and multiplied by the scale factor of 0.0001. Data quality: the spatial resolution is 1000m × 1000m, the temporal resolution is 8 days, and the value of each pixel is the average value of eight days' normalized vegetation index. Data application results: under the background of climate change, it can be used to analyze the correlation between meteorological elements and vegetation characteristics, and can also be combined with other vegetation data to analyze the regional distribution of a certain vegetation type.

    2021-02-22 419 3

  • A dataset of land surface temperature in the Aral Sea Basin (2015-2018)

    A dataset of land surface temperature in the Aral Sea Basin (2015-2018)

    Data content: surface temperature data of the Aral Sea basin from 2015 to 2018. Data sources and processing methods: the first band of mod11a2 product was extracted from the NASA medium resolution imaging spectrometer as the surface temperature data, multiplied by the scale factor of 0.02. Data quality: the spatial resolution is 1000m × 1000m, the temporal resolution is 8 days, and the value of each pixel is the average value of land surface temperature in 8 days. Data application results: under the background of climate change, it can be used to analyze the correlation between meteorological elements and vegetation characteristics, and can also be combined with other meteorological data to analyze the regional distribution of a certain vegetation type.

    2021-02-22 144 9

  • A dataset of planting structure in the Aral Sea basin (2019)

    A dataset of planting structure in the Aral Sea basin (2019)

    Data content: data set of planting structure in the Aral Sea Basin in 2019. Data sources and processing methods: 2019 is divided into three time periods, and the sentry-2 data with the least cloud cover and the highest quality in each time period is spliced into a complete map to obtain the remote sensing image of sentry-2 in the third phase of the Aral Sea basin. The NDVI values of the three images are calculated, and then combined with the cultivated land data and field sampling data, the random forest algorithm is used to classify them, and finally the planting structure type of each plot is obtained. Data quality: spatial resolution is 10m × 10m, temporal resolution is year, kappa coefficient is 0.8. Data application results: it can be used for crop yield estimation and water resource utilization efficiency calculation.

    2021-02-22 31 0

  • Data set of soil moisture in the Aral Sea Basin (2015-2018)

    Data set of soil moisture in the Aral Sea Basin (2015-2018)

    Data content: soil moisture data of the Aral Sea basin from 2015 to 2018. Data sources and processing methods: from the National Aeronautics and Space Administration of the United States, the daily soil moisture data are added to get the sum of eight days of soil, and then divided by the number of days to get the average value of eight days of rainfall. Data quality: the spatial resolution is 0.25 ° x 0.25 ° and the temporal resolution is 8 days. The value of each pixel is the average value of soil moisture in 8 days. Results and prospects of data application: under the background of climate change, it can be used to analyze the correlation between meteorological elements and vegetation characteristics, and can also be combined with other meteorological data to analyze the regional distribution of a certain vegetation type.

    2021-02-22 511 28

  • Dataset of population, agriculture and  animal husbandry of the Qinghai-Tibet Plateau in the past 100 years

    Dataset of population, agriculture and animal husbandry of the Qinghai-Tibet Plateau in the past 100 years

    The data set is mainly included the population, arable land and animal husbandry data of Qinghai Province and Tibet Autonomous Region in the past 100 years. The data mainly comes from historical documents and modern statistics. The data quality is more reliable. It mainly provides arguments for the majority of researchers in the development of agriculture and animal husbandry on the Qinghai-Tibet Plateau.

    2021-02-22 289 1

  • Spatial distribution of Active Layer Thickness and Soil Freeze Depth in Qilian Mountain

    Spatial distribution of Active Layer Thickness and Soil Freeze Depth in Qilian Mountain

    The widely definition of seasonally frozen ground include seasonally frozen layer (seasonally frozen ground regions) and seasonally thaw layer (active layer in permafrost regions). So the area extent of seasonally frozen ground occupied more than 80% land surface over Northern Hemisphere. Soil freeze/thaw cycle is one special character of seasonally frozen ground, which covers area extent, depth, time duration, variation of soil freeze/thaw. These changes in seasonally frozen ground have substantial impacts on energy, water and carbon exchange between the atmosphere and the land surface, surface and sub-surface hydrologic processes, vegetation growth, the ecosystem, carbon dioxide cycle, agriculture, and engineering constructuion, as a whole.Based on the observations from sites, CRU air temperature, we used the Stefan solution to calculate the spatial distribution of active layer thickness and soil freeze depth during 1971-2000. These results are helpful to further study the physical mechanism between seasonally frozen ground and climate change, eco-hydrology process.

    2021-02-05 200 14

  • One belt, one road area, 34 key nodes, extreme drought, spatio-temporal change state data set (2014-2015 /300m)

    One belt, one road area, 34 key nodes, extreme drought, spatio-temporal change state data set (2014-2015 /300m)

    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. The data one belt, one road area, and 34 extreme nodes in the "one area" area were evaluated by the extreme drought risk assessment index system. The time resolution and spatial resolution were 300 months. In order to facilitate the analysis of extreme drought risk index, the slope of the linear regression equation of monthly drought risk index at each pixel scale from 2014 to 2015 is calculated, which is used to represent the temporal variation characteristics of extreme drought (greater than 0 means drought aggravation, less than 0 means drought alleviation). At the same time, it can also reflect the spatial difference of extreme drought on the regional scale because it calculates the temporal change rate of each pixel.

    2021-02-04 214 11

  • One belt, one road, 34 key nodes, extreme drought, spatio-temporal change state data set (2011-2015 /1km)

    One belt, one road, 34 key nodes, extreme drought, spatio-temporal change state data set (2011-2015 /1km)

    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.

    2021-02-04 220 9

  • "One belt, one road" critical node extreme drought vulnerability data set (2015)

    "One belt, one road" critical node extreme drought vulnerability data set (2015)

    One belt, one road, one belt, one road, one belt, one road, is the key city to solve the extreme drought climate events in 34 key nodes (important cities, major projects, ports and industrial parks). The risk assessment of extreme drought is carried out. The research supports the green "one belt and one road" construction of the spatial route map, and serves the green "one belt and one road" construction. Design. For the risk assessment of drought disaster in each node, the hazard of disaster causing factors refers to the change characteristics and abnormal degree of the main meteorological factors causing drought disaster, such as the abnormal reduction of natural precipitation, the increase of evaporation or the abnormal high temperature. It is generally believed that the risk of drought disaster increases with the increase of the risk of disaster causing factors. Based on the spatialized satellite and reanalysis data of temperature, precipitation and soil available water content, the Palmer drought index of key node area was calculated to characterize the risk of extreme drought disaster factors in each node. One belt, one road and the other major projects should be built for the construction of the overseas parks, ports, major projects, and the scientific basis and Countermeasures for dealing with the drought disasters.

    2021-02-04 1071 15

  • Species list and distribution data set of the genera Eremias and Phrynocephalus in Tarim Basin (2008-2020)

    Species list and distribution data set of the genera Eremias and Phrynocephalus in Tarim Basin (2008-2020)

    1) Data content: species list and distribution data of Phrynocephalus and Eremais in Tarim Basin, including class, order, family, genus, species, and detailed distribution information including country, province, city and county; 2) Data source and processing method: Based on the field survey of amphibians and reptiles in Tarim Basin from 2008 to 2020, and recording the species composition and distribution range of Phrynocephalus and Eremias in this area; 3) Data quality description: the investigation, collection and identification of samples are all conducted by professionals, and the collection of samples information are checked to ensure the quality of distribution data; 4) Data application results and prospects: Through comprehensive analysis of the dataset, the list of species diversity and distribution can provide important data for biodiversity cataloguing in arid central Asia, and provide scientific basis for assessing biodiversity pattern and formulating conservation strategies.

    2021-02-03 657 1

  • Spatio-temporal change data of Fraction Vegetation Coverage in Central Asia (2010, 2015, 2020)

    Spatio-temporal change data of Fraction Vegetation Coverage in Central Asia (2010, 2015, 2020)

    This dataset includes Fraction Vegetation Coverage (FVC) data for five countries in Central Asia (Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan) during 2010, 2015 and 2020. The data is calculated from the MODIS-NDVI data set (product number MOD13A2.006) based on the empirical relationship between FVC in arid areas and NDVI. The product has a time resolution of 1 year and a spatial resolution of 1 km. The algorithm selects the best available pixel value based on low cloud, low detection angle and highest NDVI value from all the observation data of the year, and performs conversion.

    2021-02-03 652 39

  • Observation data  glacier meteorological station from West Pamir in Tajikistan (2020)

    Observation data glacier meteorological station from West Pamir in Tajikistan (2020)

    The West Pamir glacier meteorological station in Tajikistan (38 ° 3 ′ 15 ″ n, 72 ° 16 ′ 52 ″ e, 3730m) is jointly constructed by Urumqi Institute of desert meteorology of China Meteorological Administration, Institute of water energy and ecology of Tajik National Academy of Sciences and Tajik hydrometeorological Bureau. The observational data include hourly meteorological elements (average wind direction (°), average internal wind speed (M / s), maximum wind speed (°), maximum wind speed (M / s), average temperature (℃), maximum temperature (℃), minimum temperature (℃), average relative humidity (%), minimum relative humidity (%), average atmospheric pressure (HPA), maximum atmospheric pressure (HPA), minimum atmospheric pressure (HPA)). The data period is from November 1, 2019 to November 30, 2020 Meteorological observation data can provide important basic data for the study of the relationship between climate change, glaciers and water resources in the West Pamir mountains, and provide important data for the economic construction of the lower reaches of the Amu Darya River Basin in Tajikistan.

    2021-02-03 1104 1

  • One belt, one road critical node extreme drought vulnerability data set (2015)

    One belt, one road critical node extreme drought vulnerability data set (2015)

    One belt, one road, one belt, one road, one belt, one road, is the key city to solve the extreme drought climate events in 34 key nodes (important cities, major projects, ports and industrial parks). The risk assessment of extreme drought is carried out. The research supports the green "one belt and one road" construction of the spatial route map, and serves the green "one belt and one road" construction. Design. The vulnerability of drought disaster risk assessment for each node, on the one hand, depends on the sensitivity of different land cover types to drought disasters; on the other hand, it reflects the health of the ecological environment, determines the region's ability to bear and recover from drought disasters, which shows that the surface features under different land cover types are adversely affected by drought disasters The tendency to be loud. Using the 2015 land cover data of the "2018 silk road environment special project" source data, the vulnerability characteristics of different land cover types are measured by factor analysis method, and the weight of land vulnerability is assigned. The extreme drought vulnerability index with 100 m resolution of each node is obtained, which can provide reference for the construction planning, operation management and environmental problems of China's overseas parks, ports and major projects One belt, one road, one is the first and third, the other is the first and third.

    2021-02-02 735 27

  • Metabolomic data of modern Chinese population v1.1

    Metabolomic data of modern Chinese population v1.1

    It is not clear how the Tibetan people adapt to the extreme environment on the plateau. As an important phenotype, metabolism plays an important role in maintaining the normal biological function of individuals. Previous studies have shown that some small metabolic molecules can adapt to the extreme environment by regulating energy metabolism, oxidative stress and other biological processes. In view of this, the project is expected to find the relationship between human metabolism and extreme environmental adaptation by studying the unique metabolic characteristics of Tibetan people compared with plain people, and then study the plateau adaptation mechanism of Tibetan people from the perspective of metabolism. This data is the metabolomic data generated during the implementation of the project, and the current data includes the metabolomic data of 30 people in the plain. The combined analysis of these data and the subsequent metabolomic data can be used to study the metabolic characteristics of Tibetan people in the plateau hypoxia environment. This data set is the update and continuation of metabolomic data v1.0 of modern Chinese population.

    2021-02-02 194 1

  • Meteorological monitoring data of Kara-Batkak glacier in the Western Tianshan Mountains of Kyrgyzstan(2020)

    Meteorological monitoring data of Kara-Batkak glacier in the Western Tianshan Mountains of Kyrgyzstan(2020)

    Kara batkak glacier weather station in Western Tianshan Mountains of Kyrgyzstan (42 ° 9'46 ″ n, 78 ° 16'21 ″ e, 3280m). The observational data include hourly meteorological elements (hourly rainfall (mm), instantaneous wind direction (°), instantaneous wind speed (M / s), 2-minute wind direction (°), 2-minute wind speed (M / s), 10 minute wind direction (°), 10 minute wind speed (M / s), maximum wind direction (°), maximum wind speed (M / s), maximum wind speed time, maximum wind direction (°), maximum wind speed (M / s), maximum wind speed time, maximum instantaneous wind speed within minutes) Direction (°), maximum instantaneous wind speed in minutes (M / s), air pressure (HPA), maximum air pressure (HPA), time of maximum air pressure, time of minimum air pressure (HPA), time of minimum air pressure. Meteorological observation elements, after accumulation and statistics, are processed into climate data to provide important data for planning, design and research of agriculture, forestry, industry, transportation, military, hydrology, medical and health, environmental protection and other departments.

    2021-02-02 964 1

  • Remote sensing data of NDVI changes in Central Asia (2010, 2015, 2020)

    Remote sensing data of NDVI changes in Central Asia (2010, 2015, 2020)

    This dataset includes normalized difference vegetation index (NDVI) data of five Central Asian countries (Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan and Uzbekistan) in 2010, 2015 and 2020. This data is derived from MODIS Image data used by the earth observation system (EOS) program of the United States, product number mod13a2.006. The time resolution of the product is 16 days, and the spatial resolution is 1km. The product algorithm selects the best available pixel value from all the observed data during the 16 days, taking the low cloud, low detection angle and the highest NDVI value as the standard.

    2021-02-02 265 23

  • Remote sensing data of NDVI changes in Central Asia (2010, 2015, 2020)
  • Hydrological data of Central Asia's SYR River Basin (2020)

    Hydrological data of Central Asia's SYR River Basin (2020)

    This data is the hydrological data of kuzhan hydrological station in the middle reaches of the Xier river. The station is jointly built by Urumqi Institute of desert meteorology of China Meteorological Administration, Institute of water energy and ecology of Tajik National Academy of Sciences and Tajik hydrometeorological Bureau. The data can be used for scientific research such as water resources assessment and water conservancy projects in Central Asia. Data period: November 2, 2019 to December 5, 2020. Data elements: Hourly velocity (M / s), hourly water level (m) and hourly rainfall (m) Site location: 40 ° 17 ′ 38 ″ n, 69 ° 40 ′ 18 ″ e, 320m

    2021-02-02 387 6

  • Urban land use change data in Central Asia (1985-2018)

    Urban land use change data in Central Asia (1985-2018)

    This dataset includes year-on-year data on urban construction land changes in five countries in Central Asia (Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan) from 1985 to 2018. The data has a spatial resolution of 30m and a temporal resolution of one year. It is derived from the Global Artificial Impervious Area (GAIA) change data extracted from Landsat images from 1985 to 2018 (Gong Peng et al.). The researchers evaluated 7 sets of data every 5 years from 1985 to 2015. The average overall accuracy is over 90%, and it is the only urban construction land dataset spanning 30 years.

    2021-02-02 1008 15