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: 660

  • Dataset of GF-2 satellite images (2017)

    Dataset of GF-2 satellite images (2017)

    Gf-2 satellite is the first civil optical remote sensing satellite independently developed by China with a spatial resolution better than 1 meter. It is equipped with two high-resolution 1-meter panchromatic and 4-meter multi-spectral cameras, and the spatial resolution of the sub-satellite can reach 0.8 meters. This data set is the remote sensing image data of 6 jing gaofen-2 satellite in 2017.The folder list is: GF2_PMS1_E100.5_N37.2_20171013_L1A0002678101 GF2_PMS1_E100.5_N37.4_20171013_L1A0002678097 GF2_PMS1_E100.6_N37.6_20171013_L1A0002678096 GF2_PMS2_E100.3_N37.4_20170810_L1A0002534662 File naming rules: satellite name _ sensor name _ center longitude _ center latitude _ imaging time _L****

    2020-10-13 3971 66 View Details

  • Dataset of ZY-3 satellite images (2017)

    Dataset of ZY-3 satellite images (2017)

    The data set is the remote sensing image of ZY-3 satellite. The ZY-3 satellite was successfully launched on January 9, 2012. The main task of the satellite is to obtain high-resolution stereo and multi-spectral images covering the whole country in a long-term, continuous, stable and fast manner, and to provide services for land and resources survey and monitoring, disaster prevention and reduction, agriculture, forestry and water conservancy, ecological environment, urban planning and construction, transportation, major national projects and other fields. List of files: ZY3_MUX_E99.8_N36.6_20171011_L1A0003817398 ZY3_MUX_E99.9_N37.0_20171011_L1A0003817397 ZY3_MUX_E100.0_N37.4_20171011_L1A0003817396 ZY3_MUX_E100.1_N36.6_20170625_L1A0003738882 ZY3_MUX_E100.8_N36.6_20170710_L1A0003748776 ZY3_MUX_E100.9_N37.0_20170710_L1A0003748775 ZY3_NAD_E99.8_N36.6_20171011_L1A0003817439 ZY3_NAD_E99.9_N37.0_20171011_L1A0003817438 ZY3_NAD_E100.0_N37.4_20171011_L1A0003817437 ZY3_NAD_E100.1_N36.6_20170625_L1A0003746917 ZY3_NAD_E100.8_N36.6_20170710_L1A0003748580 ZY3_NAD_E100.9_N37.0_20170710_L1A0003748579

    2020-10-13 1491 24 View Details

  • GF-1 NDVI dataset in Maduo County (2016)

    GF-1 NDVI dataset in Maduo County (2016)

    This is the vegetation index (NDVI) for Maduo County in July, August and September of 2016. It is obtained through calculation based on the multispectral data of GF-1. The spatial resolution is 16 m. The GF-1 data are processed by mosaicking, projection coordinating, data subsetting and other methods. The maximum synthesis is then conducted every month in July, August, and September.

    2020-10-13 1989 21 View Details

  • Time series dataset of the long-term dry-wet index in Western China (AD1500-BP2000)

    Time series dataset of the long-term dry-wet index in Western China (AD1500-BP2000)

    Original information on the long-term dry-wet index (1500-2000) in western China is obtained by integrating data on dry-wet/drought-flood conditions and precipitation amounts in the western region published over more than a decade. The integrated data sets include tree rings, ice cores, lake sediments, historical materials, etc., and there are more than 50 such data sets. In addition to widely collecting representative data sets on dry-wet changes in the western region, this study also clarifies the main characteristics of the dry-wet changes and climate zones in the western region, and the long-term dry-wet index sequence was generated by extracting representative data from different zones. The data-based dry-wet index sequence has a 10-year temporal resolution for five major characteristic climate zones in the western region over nearly four hundred years and a high resolution (annual resolution) for three regions over the past five hundred years. The five major characteristic climate zones in the western region with a 10-year dry-wet index resolution over the last four hundred years are the arid regions, plateau bodies, northern Xinjiang, Hetao region, and northeastern plateau, and the three regions with a annual resolution over the last five hundred years are the northeastern plateau, Hetao region, and northern Xinjiang. For a detailed description of the data, please refer to the data file named Introduction of Dry-Wet Index Sequence Data for West China.doc.

    2020-10-09 9365 43 View Details

  • Geocryological regionalization and classification map of the frozen soil in China (1:10,000,000) (2000)

    Geocryological regionalization and classification map of the frozen soil in China (1:10,000,000) (2000)

    These data are digitized for the Geocryological Regionalization and Classification Map of the Frozen Soil in China (1:10 million) (Guoqing Qiu et al., 2000; Youwu Zhou et al., 2000), adopting a geocryological regionalization and classification dual series system. The geocryological regionalization system and classification system are used on the same map to reflect the commonality and individuality of the formation and distribution of frozen soil at each level. The geocryological regionalization system consists of three regions of frozen soil: (1) the frozen soil region of eastern China; (2) the frozen soil region of northwestern China; and (3) the frozen soil region of southwestern China (Tibetan Plateau). Based on the three large regions, 16 regions and several subregions are further divided. In the division of the geocryological boundary in the frozen soil area, the boundary between major regions I and III mainly consults the results of Bingyuan Li (1987). The boundary between major regions II and III is the northern boundary of the Tibetan Plateau, which is the Kunlun Mountains-Altun Mountains-Northern Qilian Mountains and the piedmont line. The boundary between major regions I and II is in the area of Helan Mountain-Langshan Mountain. The boundary of the secondary region is divided by the geomorphological conditions in regions II and III. However, in region I, it is mainly divided by the ratio of the annual temperature range A to the annual mean temperature T, and the frozen depths of various regions are taken into consideration. The classification system is divided into 8 types based on the continuity of frozen soil, the time of existence of frozen soil and the seasonal frozen depth. The various classifications of boundaries are mainly taken from the "Map of Snow, Ice and Frozen Ground in China" (1:4 million) (Yafeng Shi et al., 1988) and consult some new materials, whereas the seasonal frozen soil boundary is mainly based on the weather station data. The definitions of each classification are as follows: (1) Large permafrost: the continuous coefficient is 90%-70%; (2) Large-island permafrost: the continuous coefficient is 70%-30%; (3) Sparse island-shaped permafrost: the continuous coefficient is <30%; (4) Permafrost in the mountains; (5) Medium-season seasonal frozen soil: the maximum seasonal frozen depth that can be reached is >1 m; (6) Shallow seasonal frozen soil: the maximum seasonal frozen depth that can be reached is <1 m; (7) Short-term frozen soil: less than one month of storage time; and (8) Nonfrozen soil. According to the data, China's permafrost areas sum to approximately 2.19 × 106 km², accounting for 22.83% of China's territory. Among those areas, the mountain permafrost is found over 0.42×106 km2, which is 4.39% of the territory of China. The seasonal frozen soil area is approximately 4.76×106 km², accounting for 49.6% of China's territory, and the instantaneous frozen soil area is approximately 1.86×106 km², i.e., 19.33% of China's territory. For more information, please see the references (Youwu Zhou et al., 2000).

    2020-10-09 20526 152 View Details

  • Inventory of glaciers in Pakistan (2003-2004)

    Inventory of glaciers in Pakistan (2003-2004)

    This dataset is the spatial distribution map of the marshes in the source area of the Yellow River near the Zaling Lake-Eling Lake, covering an area of about 21,000 square kilometers. The data set is classified by the Landsat 8 image through an expert decision tree and corrected by manual visual interpretation. The spatial resolution of the image is 30m, using the WGS 1984 UTM projected coordinate system, and the data format is grid format. The image is divided into five types of land, the land type 1 is “water body”, the land type 2 is “high-cover vegetation”, the land type 3 is “naked land”, and the land type 4 is “low-cover vegetation”, and the land type 5 is For "marsh", low-coverage vegetation and high-coverage vegetation are distinguished by vegetation coverage. The threshold is 0.1 to 0.4 for low-cover vegetation and 0.4 to 1 for high-cover vegetation.

    2020-10-09 10296 70 View Details

  • Oxygen isotope, dust, anion and accumulation data from the Guliya ice core (1992)

    Oxygen isotope, dust, anion and accumulation data from the Guliya ice core (1992)

    This data set contains the oxygen isotope, dust, anion and accumulation data obtained from the deep ice core drilled in 1992 in the Guliya ice cap, which is located in the west Kunlun Mountains on the Tibetan Plateau. The length of the ice core was 308.6 m. The ice core was cut into samples, 12628 of which were used to measure the oxygen isotope values, 12480 of which were used to measure the dust concentrations, and 9681 of which were used to measure the anion concentrations. Data Resource: National Centers for Environmental Information(http://www.ncdc.noaa.gov/data-access/paleoclimatology-data/datasets/ice-core). Processing Method: Average. The data set contains 4 tables, namely: oxygen isotope, dust and anion data from different depths in the Guliya ice core, 10-year mean data of oxygen isotopes, dust, anions and net accumulation in the Guliya ice core, 400-year mean data of oxygen isotopes, dust and anions in the Guliya ice core, and chlorine-36 data from different depths. Table 1: Data on oxygen isotopes, dust and anion concentrations at different depths in the Guliya ice core. a. Name explanation Field 1: Depth Field 2: Oxygen isotope value Field 3: Dust concentration (diameter 0.63 to 20 µm) Field 4: Cl- Field 5: SO42- Field 6: NO3- b. Dimensions (unit of measure) Field 1: m Field 2: ‰ Field 3: particles/mL Field 4: ppb Field 5: ppb Field 6: ppb Table 2: 10-year mean oxygen isotope, dust, anion and net accumulation data for the Guliya ice core (0-1989) a. Name explanation Field 1: Start time Field 2: End time Field 3: Oxygen isotope value Field 4: Dust concentration (diameter 0.63 -20 µm) Field 5: Cl- Field 6: SO42- Field 7: NO3- Field 8: Net accumulation b. Dimensions (unit of measure) Field 1: Dimensionless Field 2: Dimensionless Field 3: ‰ Field 4: particles/mL Field 5: ppb Field 6: ppb Field 7: ppb Field 8: cm/year Table 3: 400-year mean oxygen isotope, dust and anion data for the Guliya ice core. a. Name explanation Field 1: Time Field 2: Oxygen isotope Field 3: Dust concentration (diameter 0.63-20 µm) Field 4: Cl- Field 5: SO42- Field 6: NO3- b. Dimensions (unit of measure) Field 1: Millennium Field 2: ‰ Field 3: particles/mL Field 4: ppb Field 5: ppb Field 6: ppb Table 4: Chlorine-36 data at different depths a. Name explanation Field 1: Depth Field 2: 36Cl Field 3: 36Cl error Field 4: Year b. Dimensions (unit of measure) Field 1: m Field 2: 104 atoms g-1 Field 3: % Field 4: Millennium

    2020-10-09 1074 22 View Details

  • The recipitation of main areas in Qinghai Province (1988-2016)

    The recipitation of main areas in Qinghai Province (1988-2016)

    The data set includes precipitation data of main areas in Qinghai Province from 1988 to 2016 such as Xining, Haidong, Menyuan, Huangnan, Hainan, Guoluo, Yushu and Haixi. The data were derived from the Qinghai Society and Economics Statistical Yearbook and the Qinghai Statistical Yearbook. The accuracy of the data is consistent with that of the statistical yearbook. The data table records the monthly and annual precipitation in 8 regions of Qinghai with units of millimeters. The data set is mainly applied in geography and socioeconomic research.

    2020-10-09 1323 20 View Details

  • The average wind speed of main areas in Qinghai Province (1988-2016)

    The average wind speed of main areas in Qinghai Province (1988-2016)

    The data set includes the average wind speed data of main areas in Qinghai Province from 1988 to 2016 such as Xining, Haidong, Menyuan, Huangnan, Hainan, Guoluo, Yushu and Haixi. The data were derived from the Qinghai Society and Economics Statistical Yearbook and the Qinghai Statistical Yearbook. The accuracy of the data is consistent with that of the statistical yearbook. The data table records the monthly and annual average wind speed in eight regions of Qinghai. Unit: m / s The data set is mainly applied in geography and socioeconomic research.

    2020-10-09 926 9 View Details

  • The annual sunshine hours and total solar radiation in Tibet Autonomous Region (1988-1994)

    The annual sunshine hours and total solar radiation in Tibet Autonomous Region (1988-1994)

    The data set contains data on the annual sunshine hours and total solar radiation in Tibet from 1988 to 1994. The data were derived from the Tibet Society and Economics Statistical Yearbook and the Tibet Statistical Yearbook. The accuracy of the data is consistent with that of the statistical yearbook. The table contains 5 fields. Field 1: Year Interpretation: Year of the data Field 2: Location Field 3: Annual sunshine hours Unit:hour Field 4: Annual sunshine percentage Unit: % Field 5: Total solar radiation Unit: Kcal/cm2 • Year

    2020-10-09 1111 14 View Details

  • The lakes above 5000 m in Tibet Autonomous Region (1988-2016)

    The lakes above 5000 m in Tibet Autonomous Region (1988-2016)

    The data set includes data on lakes with an altitude over 5,000 meters in Tibet from 1988 to 2016. The data were derived from the Tibet Society and Economics Statistical Yearbook and the Tibet Statistical Yearbook. The accuracy of the data is consistent with that of the statistical yearbook. The table contains 5 fields. Field 1: Year Field 2: Lake Name Field 3: Lake altitude Unit: meter Field 4: Lake area Unit: square kilometers Field 5: Lake Type

    2020-10-09 758 8 View Details

  • Administrative divisions of counties in Qinghai province (1992-2016)

    Administrative divisions of counties in Qinghai province (1992-2016)

    The data set contains the Chinese name, English name and the affiliation between the districts and counties in each administrative division of Qinghai. The data were derived from the Qinghai Society and Economics Statistical Yearbook and the Qinghai Statistical Yearbook. The accuracy of the data is consistent with that of the statistical yearbook. Table 1: The table of administrative divisions in Qinghai has 5 fields. Field 1: Regions Interpretation: Chinese names of the regions Field 2: English names of the regions Interpretation: English names of the regions Field 3: Districts and counties Interpretation: Chinese names of the districts and counties Field 4: English names of the districts and counties Interpretation: English names of the districts and counties Field 5: Land area Unit: square kilometers Table 2: The table of division changes of each county has 5 fields. Field 1: Districts and counties Field 2: Year Field 3: Area Unit: square kilometers Field 4: Number of townships Field 5: Number of Village Committees

    2020-10-09 1442 27 View Details

  • The Birth, Mortality, and Natural Growth Rate of Qinghai (1952-2016)

    The Birth, Mortality, and Natural Growth Rate of Qinghai (1952-2016)

    This data set contains data on the birth rate, mortality rate and natural growth rate in Qinghai. The data were derived from the Qinghai Society and Economics Statistical Yearbook and Qinghai Statistical Yearbook. The accuracy of the data is consistent with that of the statistical yearbooks. The table contains 8 fields. Field 1: Year of the data Field 2: The number of permanent residents, unit: 10,000 Field 3: The number of births Field 4: Birth rate, unit: ‰ Field 5: The number of deaths Field 6: Mortality rate, unit: ‰ Field 7: Natural growth of the population Field 8: Natural growth rate, unit: ‰

    2020-10-09 946 17 View Details

  • The statistic data of highways, bridges and ferries in Tibet Autonomous Region (1954-2016)

    The statistic data of highways, bridges and ferries in Tibet Autonomous Region (1954-2016)

    The data set recorded the sequence data of highway traffic mileage, all-weather traffic mileage, highway maintenance, number of bridges, bridge length and ferries from 1954 to 2016 in Tibet. The data were derived from the Tibet Society and Economics Statistical Yearbook and the Tibet Statistical Yearbook. The accuracy of the data is consistent with that of the statistical yearbook. The table contains 7 fields. Field 1: Year Interpretation: Year of the data Field 2: Highway traffic mileage Interpretation: Highway traffic mileage Unit: kilometer Field 3: All-weather traffic mileage Unit: kilometer Field 4: Highway maintenance Interpretation: Highway maintenance mileage Unit: kilometer Field 5: Number of bridges Interpretation: Total number of bridges Field 6: Bridge length Interpretation: Total length of the bridges Unit: meter Field 7: Ferries Interpretation: Number of ferries

    2020-10-09 795 13 View Details

  • Different glacier status with atmospheric circulations in Tibetan Plateau and surroundings (1970s-2000s)

    Different glacier status with atmospheric circulations in Tibetan Plateau and surroundings (1970s-2000s)

    This data set is collected from the supplementary information part of the paper: Yao, T. , Thompson, L. , & Yang, W. . (2012). Different glacier status with atmospheric circulations in tibetan plateau and surroundings. Nature Climate Change, 1580, 1-5. This paper report on the glacier status over the past 30 years by investigating the glacial retreat of 82 glaciers, area reductionof 7,090 glaciers and mass-balance change of 15 glaciers. This data set contains 8 tables, the names and content are as follows: Data list: The data name list of the rest tables; t1: Distribution of Glaciers in the TP and surroundings; t2: Data and method for analyzing glacial area reduction in each basin; t3: Glacial area reduction during the past three decades from remote sensing images in the TP and surroundings; t4: Glacial length fluctuationin the TP and surroundings in the past three decades; t5: Detailed information on the glaciers for recent mass balance measurement in the TP and surroundings; t6: Recent annual mass balances in different regions in the TP; t7: Mass balance of Long-time series for the Qiyi, Xiaodongkemadi and Kangwure Glaciers in the TP. See attachments for data details: Supplementary information.pdf, Different glacier status with atmospheric circulations in Tibetan Plateau and surroundings.pdf.

    2020-10-09 4243 101 View Details

  • Seismic velocity reduction and accelerated recovery due to earthquakes on the Longmenshan fault (2000-2014)

    Seismic velocity reduction and accelerated recovery due to earthquakes on the Longmenshan fault (2000-2014)

    This data set is collected from the supplementary information part of the paper: Pei, S.P., Niu, F.L., Ben-Zion, Y., Sun, Q., Liu, Y.B., Xue, X.T., Su,J.R., & Shao, Z.G. (2019). Seismic velocity reduction and accelerated recovery due to earthquakes on the Longmenshan fault. Nature Geoscience. 12. 387-392. doi:10.1038/s41561-019-0347-1. This paper studies the structural evolution process of The Longmenshan fault zone located at a pronounced topographic boundary between the eastern margin of the Tibetan plateau and the western Sichuan basin. With the observations on coseismic velocity reductions and the healing phases, it is found that the healing phase of Wenchuan earthquake fracture zone accelerated significantly in response to the Lushan earthquake. This data set contains 3 tables, table names and content are as follows: Data list: The data name list of the rest tables; t1: Data of the four periods (befor Wenchuan earthquake, after Wenchuan earthquake, before Lushan earthquake, after Lushan earthquake); t2: The average velocities with error in Figure 2 in the paper for Wenchuan earthquake (WCEQ) and Lushan earthquake (LSEQ) area. See attachments for data details: Supplementary information.pdf, Seismic velocity reduction and accelerated recovery due to earthquakes on the Longmenshan fault.pdf.

    2020-10-09 1177 2 View Details

  • A tree ring-based winter temperature reconstruction for the southeastern Tibetan Plateau (1340-2007)

    A tree ring-based winter temperature reconstruction for the southeastern Tibetan Plateau (1340-2007)

    This dataset is provided by the author of the paper: Huang, R., Zhu, H.F., Liang, E.Y., Liu, B., Shi, J.F., Zhang, R.B., Yuan, Y.J., & Grießinger, J. (2019). A tree ring-based winter temperature reconstruction for the southeastern Tibetan Plateau since 1340 CE. Climate Dynamics, 53(5-6), 3221-3233. In this paper, in order to understand the past few hundred years of winter temperature change history and its driving factors, the researcher of Key Laboratory of Alpine Ecology, Institute of Tibetan Plateau Research, Chinese Academy of Sciences and CAS Center for Excellence in Tibetan Plateau Earth Sciences. Prof. Eryuan Liang and his research team, reconstructed the minimum winter (November – February) temperature since 1340 A.D. on southeastern Tibetan Plateau based on the tree-ring samples taken from 2007-2016. The dataset contains minimum winter temperature reconstruction data of Changdu on the southeastern TP during 1340-2007. The data contains fileds as follows: year Tmin.recon (℃) See attachments for data details: A tree ring-based winter temperature reconstruction for the southeasternTibetan Plateau since 1340 CE.pdf

    2020-10-09 2068 26 View Details

  • S receiver functions of the Northeastern Tibetan Plateau (2009-2016)

    S receiver functions of the Northeastern Tibetan Plateau (2009-2016)

    The dataset partially used in the study of paper 2018GC007986 includes S receiver functions derived from 48 permanent stations and 11 stations of a temporary HY array deployed in the northeastern Tibetan Plateau. The dataset as a zipped file contains one folder, two files including NETibet_SRF.QBN and NETibet_SRF.QHD. A spiking deconvolution in the time domain is used to calculate the P and S receiver functions, all the S receiver functions have been visually inspected to remove the bad traces that obviously different from the majority. The dataset is applied to explore the lithospheric structure and understand the mechanism of northeastern expansion and growth of NE Tibetan Plateau.

    2020-10-09 805 3 View Details

  • The lakes larger than 1k㎡ in Tibetan Plateau (V1.0) (1970s, 1990, 2000, 2010)

    The lakes larger than 1k㎡ in Tibetan Plateau (V1.0) (1970s, 1990, 2000, 2010)

    The dataset includes vector map of the lakes larger than 1k㎡ on Tibetan Plateau in 1970s, 1990, 2000, 2010. The lake boundry data was extracted from remote sensing image like Landsat MSS, TM, ETM+, by means of visual interpretation. The data type is vector data, and it's attribute class includes Area (km²). The Projected Coordinate System is Albers Conical Equal Area. It is mainly used in the study of changes in lakes, hydrological and meteorological on the Tibetan Plateau.

    2020-10-09 1317 52 View Details

  • The dataset of all the lakes on the Tibetan Plateau (2000)

    The dataset of all the lakes on the Tibetan Plateau (2000)

    The data set contains vector data of 32,840 lakes which can be recognized in the remote sensing image on the Tibetan plateau in 2000. The data was obstracted by visual interpretation from GeoCover Landsat Mosaic 2000 image data with a spatial resolution of 14.25 m. The data format is vector data, and the projection coordinate system is Albers Conical Equal Area. The data property fields are as follows: Area: lake Area (km); X: lake center longitude (°); Y: lake center latitude (°); Perimeter: the Perimeter of a lake (km).

    2020-10-09 1193 47 View Details