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: 642

  • The digital elevation model of the Tibetan Plateau (2000)

    The digital elevation model of the Tibetan Plateau (2000)

    This data set is a digital elevation model of the Tibetan Plateau and can be used to assist in analysis and research of basic geographic information for the Tibetan Plateau. The raw data were the Shuttle Radar Topography Mission (SRTM) data, which were provided by Global Land Cover Network (GLCN), and the raw data were framing data , using the WGS84 coordinate system, including latitude and longitude, with a spatial resolution of 3″. After the mosaic processing, the Nodata (null data) generated in the mosaic process were interpolated and filled. After filling, the projection conversion process was performed to generate data as Albers equal area conical projection. After the conversion projection, the spatial resolution of the data was 90 m. Finally, the boundary of the Tibetan Plateau was used for cutting to obtain DEM data. This data table has two fields. Field 1: value Data type: long integer Interpretation: altitude elevation Unit: m Field 2: count Data type: long integer Interpretation: The number of map spots corresponding to the altitude elevation Data accuracy: spatial resolution: 90 m

    2020-06-03 891 42 View Details

  • The slope map of the Tibetan Plateau (2000)

    The slope map of the Tibetan Plateau (2000)

    This data set contains the digital slope distribution and slope degree data of the Tibetan Plateau, which can be used to assist in basic geographic information analysis and research work on the Tibetan Plateau region. The raw data were the Shuttle Radar Topography Mission (SRTM) data provided by Global Land Cover Network (GLCN) using the WGS84 coordinate system, and the raw data were framing data, including latitude and longitude data, with a spatial resolution of 3″. After the mosaic processing, the Nodata (null data) generated in the mosaic process were interpolated and filled, and after filling, a projection conversion process was performed to generate an equal-area conical projection of the data bit Albers, after conversion projection, the spatial resolution was 90 m. Finally, the boundary of the Tibetan Plateau was used for cutting to obtain DEM data. Use the spatial analysis module under ArcMap to calculate the slope aspect and generate the slope map. Field: value Data type: floating point Interpretation: slope degree Dimension: degree Data accuracy: spatial resolution 90 m

    2020-06-03 706 20 View Details

  • Precipitation observation data of Jaggang Snow Mountain (2016-2017)

    Precipitation observation data of Jaggang Snow Mountain (2016-2017)

    This is the precipitation observation data of the observation point in Jaggang Snow Mountain. It can be used in Glaciology, Climatology, Environmental Change, Hydrologic Process in Cold Regions and other disciplinary areas. The data is observed from September 14, 2016 to June 19, 2017. It is measured by automatic rain gauge and a piece of data is recorded every 60 minutes. The original data forms a continuous time series after quality control, and the daily mean index data is obtained through calculation. The original data meets the accuracy requirements of China Meteorological Administration (CMA) and the World Meteorological Organization (WMO) for meteorological observation. Quality control includes eliminating the systematic error caused by the missing point data and sensor failure. The data is stored as an excel file.

    2020-06-03 577 3 View Details

  • Drone orthophoto image and DSM of Qinghai Hoh Xil plot (2018)

    Drone orthophoto image and DSM of Qinghai Hoh Xil plot (2018)

    On August 22, 2018, a DJI camera was used in the fixed sample of Lancang River headwaters. The overlap degree of adjacent photos was not less than 70% according to the set flight route. The Orthophoto Image and DSM were generated using the photographs taken. The Orthophoto Image included three bands of red, green and blue, with a ground resolution of 2.5 cm, a shooting area of 1000m x 1000m and a DSM resolution of 4.5 cm. Due to the communication failure, the middle four airstrips were not photographed, so there was a band in the middle of the image missing.

    2020-06-03 950 8 View Details

  • Drone photoes of Qumalai wetland plot (2018)

    Drone photoes of Qumalai wetland plot (2018)

    On August 19, 2018, the wetland sample in Qumali County, located in the source area of the Yangtze River, was aerially photographed by DJI Elf 4 UAV. A total of 31 routes were set up, flying at a height of 100 m, and the overlap of adjacent photographs was not less than 70%. A total of 1551 aerial photographs were obtained and stored in two folders named "Drone Photoes Part1" and "Drone Photoes Part2".

    2020-06-03 1094 12 View Details

  • MODIS vegetation index dataset in Sanjiangyuan (2000-2018)

    MODIS vegetation index dataset in Sanjiangyuan (2000-2018)

    The data set is MODIS vegetation index data (MOD13Q1). The source areas of the three rivers are extracted to carry out the research and analysis of the source areas of the three rivers separately. MOD13Q1 is a 16-day composite vegetation index, including normalized vegetation index (NDVI) and enhanced vegetation index (EVI). The spatial scope of Sanjiang Source covers two MODIS files (h25v05 and h26v05). Data storage format is hdf. Each file contains 12 bands: Normalized Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Data Quality (VI Quality), Red Reflectance, Near Infrared Reflectance (NIR Reflectance), Blue Reflectance, Mid Infrared Reflectance, Observation. Viewzenith angle, sun zenith angle, relative azimuth angle, composite day of the year and pixel reliability. The data format of this data set is hdf, spatial resolution is 250m, temporal resolution is 16 days, time range: February 2000 to October 2018.

    2020-06-03 1349 24 View Details

  • Spot vegetation NDVI dataset for Sanjiangyuan (1998-2013)

    Spot vegetation NDVI dataset for Sanjiangyuan (1998-2013)

    The data set is extracted from the NDVI data of long time series acquired by VEGETATION sensor on SPOT satellite. The time range of the data set is from May 1998 to 2013. In order to remove the noise in NDVI data, the maximum synthesis is carried out. A NDVI image is synthesized every 10 days. The data set is cut out from the global data set, so as to carry out the research and analysis of the source areas of the three rivers separately. The data format of this data set is geotiff, spatial resolution is 1 km, temporal resolution is 10 days, time range: May 1998 to December 2013.

    2020-06-03 1255 13 View Details

  • SeaWiFS NDVI dataset for Sanjiangyuan (1997-2007)

    SeaWiFS NDVI dataset for Sanjiangyuan (1997-2007)

    The data set is NDVI data of long time series acquired by SeaWiFS. The time range of the data set is from September 1997 to 2007. In order to remove the noise in NDVI data, the maximum synthesis is carried out. A NDVI image is synthesized every 15 days. The data set is cut out from the global data set, so as to carry out the research and analysis of the source areas of the three rivers separately. The data format of this data set is geotiff, spatial resolution is 4 km, temporal resolution is 15 days, time range: 256 days in 1997 to 365 days in 2007.

    2020-06-02 1029 11 View Details

  • Distribution of the average vegetation coverage in Central Asia (2017)

    Distribution of the average vegetation coverage in Central Asia (2017)

    The data set is the vegetation coverage in Central Asia including three temperate deserts, the Karakum, Kyzylkum and Muyunkun Deserts, and one of the world's largest arid zones. This is the MODIS-NDVI data set calculated by using the NDVI and the vegetation coverage in arid region. The space and time resolutions are 500 m and 16 days, respectively. The time is from 01, January, 2017 to 18, December, 2017. The data set uses the the Geodetic coordinate system. It can be used for the investigation of the Desert oil and gas field, and oasis cities.

    2020-06-02 792 10 View Details

  • Frozen land temperature monitoring dataset of  Tibet Plateau Beibeihe meteorological station (2017-2018)

    Frozen land temperature monitoring dataset of Tibet Plateau Beibeihe meteorological station (2017-2018)

    Frozen soil refers to a soil or rock mass with a temperature lower than or equal to 0 ° C and containing ice. It is particularly sensitive to temperature and its physical and mechanical properties change significantly with temperature. The frost heaving deformation and melt settlement deformation of frozen soil are the most common frozen soil disasters. Their occurrence is mainly caused by the change of the inherent temperature of frozen soil due to the frozen soil engineering activities. Therefore, the protection of frozen soil is mainly to protect the temperature of frozen soil. , to maintain it in the closest state before the engineering activities. The main method for obtaining the temperature of the frozen land is to embed the temperature measuring cable. Through the data acquisition function of the CR3000, the resistance value of the temperature measuring cable is obtained at different times, and the temperature value is calculated by the correspondence between the calibration coefficient and the resistance value. According to the sensitive characteristics of frozen soil to temperature, the change of ground temperature can reflect the change of climate, and can also analyze the influence mechanism and degree of human activities on the stability of frozen soil in combination with other factors, so as to guide the later engineering activities. Upgrading and upgrading of frozen soil protection measures.

    2020-06-02 596 27 View Details

  • Geological records and photograph dataset of the Jilong-Oma and Dati Basins During the field investigation over Southern Tibetan Plateau

    Geological records and photograph dataset of the Jilong-Oma and Dati Basins During the field investigation over Southern Tibetan Plateau

    The Southern Tibet Rift System (STRS) is one of the most prominent tectonic and geomorphological features in the southern Tibetan Plateau. The Jilong-Oma and Dati basins are located in the northern Himalaya Mountains. The late Cenozoic sedimentary sequences deposited in these two rift basins have archived abundant information about formation and evolution of the STRS and the uplift process of the Tibetan Plateau. The detailed stratigraphic and sedimentologic investigations were conducted on the late Cenozoic sediments in the Jilong-Oma basins. The late Cenozoic sediments in the Jilong-Oma Basin is over 610 m in thickness, including the lower conglomerate member of the fan delta facies (Danzengzhukang Fm., 400-600 m), the middle mudstone interbedded with sandstone member of fluvio-lacustrine facies (Oma Fm., 200-400 m) and the upper conglomerate intercalated with mudstone member of alluvial fan facies (Gongba Fm., 200-0 m). The Hipparion fossils were previously found at the bottom of the Oma Fm. The late Cenozoic sediments in the Dati Basin have a thickness of ~300 m, iucluding the lower mudstone, sandstone and sandy conglomerate member of fluvio-lacustrine faceis (Dati Fm., 80-305 m), and the upper conglomerate member of alluvial fan facies (Gongba Fm., 80-0 m). The Hipparion fossils were previously found at the upper part of the Dati Fm. By comparing with the Zhada Basin in the west part of the Himalaya orogen, it shows that these rift basins experienced the similar sedimentary evolution history and have the comparable Hipparion fossils. Establishing the precise chronology of these sediments and carrying out comprehensive comparison analyses between the rift basins play important roles in understanding the formation and evolution of the STRS, the uplift and deformation processes of the southern Tibetan Plateau and the climate change in the surrounding areas.

    2020-06-02 540 2 View Details

  • Yulong snow mountain glacier No.1, 3046 m altitude  the daily average meteorological observation dataset (2014-2018)

    Yulong snow mountain glacier No.1, 3046 m altitude the daily average meteorological observation dataset (2014-2018)

    1.The data content: air temperature, relative humidity, precipitation, air pressure, wind speed, the average daily data of total radiation and vapor pressure. 2. Data sources and processing methods: campel mountain type automatic meteorological station observation by the United States, including air temperature and humidity sensor model HMP155A;Wind speed and direction finder models: 05103-45;Net radiation instrument: CNR four radiometer component;The atmospheric pressure sensor: CS106;The measuring cylinder: TE525MM.Automatic meteorological station every ten minutes automatic acquisition data, after complete automatic acquisition daily meteorological data then daily mean value were calculated statistics. 3. Data quality description: automatic continuous access to data. 4.Data application results and prospects: the weather stations of underlying surface type as the alpine meadow, meteorological data can provide basic data for GaoHan District land surface process simulation.

    2020-06-02 391 5 View Details

  • LAI dataset of remote sensing for ecological assets assessment in Tibet Plateau (2000-2017)

    LAI dataset of remote sensing for ecological assets assessment in Tibet Plateau (2000-2017)

    The basic data set of remote sensing for ecological assets assessment of the Qinghai-Tibet Plateau includes the annual Fraction Vegetation Coverage (FVC), Net Primary Productivity (NPP) and Leaf Area Index (LAI) of the Qinghai-Tibet Plateau since 2000, and other ecological parameters based on remote sensing inversion. The improved LAI estimation method based on TSF filter and scale down method are used to improve the LAI data.

    2020-06-02 521 19 View Details

  • NPP dataset of remote sensing for ecological assets assessment in Qinghai-Tibet Plateau

    NPP dataset of remote sensing for ecological assets assessment in Qinghai-Tibet Plateau

    The basic data set of remote sensing for ecological assets assessment of the Qinghai-Tibet Plateau includes the annual Fraction Vegetation Coverage (FVC), Net Primary Productivity (NPP) and Leaf Area Index (LAI) of the Qinghai-Tibet Plateau since 2000, and other ecological parameters based on remote sensing inversion. The FVC data are mainly developed from MODIS NDVI data. NPP estimation method based on algorithm of CASA model.

    2020-06-02 535 46 View Details

  • Yulong snow mountain glacier No.1, 4 300 m altitude, 2014-2018, the daily average meteorological observation dataset

    Yulong snow mountain glacier No.1, 4 300 m altitude, 2014-2018, the daily average meteorological observation dataset

    1.The data content: air temperature, relative humidity, precipitation, air pressure, wind speed and vapor pressure. 2. Data sources and processing methods: campel mountain type automatic meteorological station observation by the United States, including air temperature and humidity sensor model HMP155A;Wind speed and direction finder models: 05103-45;The atmospheric pressure sensor: CS106;The measuring cylinder: TE525MM.Automatic meteorological station every ten minutes automatic acquisition data, after complete automatic acquisition daily meteorological data then daily mean value were calculated statistics. 3.Data quality description: automatic continuous access to data. 4.Data application results and prospects: the weather stations set in the upper of the glacier terminal, meteorological data can be used to simulate for predict the future climate change under the background of type Marine glacial changes in response to global climate change research provides data.

    2020-06-02 453 4 View Details

  • FVC dataset of remote sensing for ecological assets assessment in Qinghai-Tibet Plateau

    FVC dataset of remote sensing for ecological assets assessment in Qinghai-Tibet Plateau

    The basic data set of remote sensing for ecological assets assessment of the Qinghai-Tibet Plateau includes the annual Fraction Vegetation Coverage (FVC), Net Primary Productivity (NPP) and Leaf Area Index (LAI) of the Qinghai-Tibet Plateau since 2000, and other ecological parameters based on remote sensing inversion. The FVC data are mainly developed from MODIS NDVI data. Based on pixel dichotomy model, the vegetation coverage model is developed by using multi-scale remote sensing images, combining with high precision remote sensing parameters such as vegetation community type and distribution characteristics, and the mixed pixel decomposition method is used to construct the vegetation coverage model. All data could be used only after the permission of the data distributor.

    2020-06-02 623 29 View Details

  • A new map of permafrost distribution on the Tibetan Plateau (2017)

    A new map of permafrost distribution on the Tibetan Plateau (2017)

    Qinghai Tibet Plateau is the largest permafrost area in the world. At present, some permafrost distribution maps have been compiled. However, due to the limited data sources, unclear standards, insufficient verification and lack of high-quality spatial data sets, there is great uncertainty in drawing Permafrost Distribution Maps on TP. Based on the improved medium resolution imaging spectrometer (MODIS) surface temperature (LSTS) model of 1 km clear sky mod11a2 (Terra MODIS) and myd11a2 (Aqua MODIS) product (reprocessing version 5) in 2003-2012, the data set simulates the distribution of permafrost and generates the permafrost map of Qinghai Tibet Plateau. The map was verified by field observation, soil moisture content and bulk density. Permafrost attributes mainly include: seasonally frozen ground, permafrost and unfrozen ground. The data set provides more detailed data of Permafrost Distribution and basic data for the study of permafrost in the Qinghai Tibet Plateau.

    2020-06-02 2855 140 View Details

  • Yulong snow mountain glacier No.1, 4 506 m altitude the daily average meteorological observation dataset (2014-2018)

    Yulong snow mountain glacier No.1, 4 506 m altitude the daily average meteorological observation dataset (2014-2018)

    1. Data content: air temperature, relative humidity, precipitation, air pressure, wind speed, average total radiation, total net radiation value and daily average water vapor pressure data. 2. Data source and processing method: Observed by American campel high-altitude automatic weather station, air temperature and humidity sensor model HMP155A; wind speed and wind direction model: 05103-45; net radiometer: CNR 4 Net Radiometer four component; atmospheric pressure sensor: CS106; Rain gauge: TE525MM. The automatic weather station automatically collects data every 10 minutes, and collects daily statistical data to obtain daily average weather data. 3. Data quality description: Data is automatically acquired continuously. 4. Data application results and prospects: The weather station is located in the middle of the glacier, and the meteorological data can provide data guarantee for simulating the response of oceanic glacier changes to global climate change in the context of future climate change.

    2020-06-01 458 5 View Details

  • Vegetation and soil characteristics in different degradation period in three temperate grassland of Inner Mogolia

    Vegetation and soil characteristics in different degradation period in three temperate grassland of Inner Mogolia

    By means of field survey, sampling and indoor test and analysis, three types of warm grasslands in different degradation stages in Inner Mongolia were systematically collected, namely, the vegetation and soil data of meadow grasslands, typical grasslands and desert grasslands from east to west.Specifically, it includes: coordinate information of sample collection points, sample square table of plant survey, aboveground biomass during the flourishing period of plant growth, organic carbon content of plants, total nitrogen of plants and total potassium of plants;Soil moisture content, soil PH value, soil conductivity, soil inorganic nitrogen content, soil bulk density, soil aggregate proportion, soil organic carbon content, soil total nitrogen, soil total potassium.These data are all standardized test methods, which have certain reference value for the systematic study of Inner Mongolia warm grassland.

    2020-06-01 193 1 View Details

  • Monthly average flow statistics of Baishuihe station in Jinsha River Basin of Yunnan Province (2018)

    Monthly average flow statistics of Baishuihe station in Jinsha River Basin of Yunnan Province (2018)

    1.The data content: Monthly mean flow statistics data of white river station at the jinsha river basin of yunnan province, 2018. 2. Data sources and processing methods: Australia Unidata ultrasonic velocity sensor automatic measuring river flow velocity in the the white river hydrology section , using the water level data recorded by the HOBO water level meter and the corresponding hydrological section area data,, volume and velocity relationship formula, flow data is calculated. 3.Data quality description: automatic continuous access to data 4.Data application results and prospects: provide data support for snow - runoff model simulation

    2020-06-01 377 8 View Details