Brief Introduction: Pan-third-polar environmental change and green silk road construction
Number of Datasets: 636
The data set includes altitude data and temperature characteristics from 1988 to 1994 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 10 fields. Field 1: Year Interpretation: Year of the data Field 2: Location Field 3: Altitude Unit: meter Field 4: Extreme maximum temperature date Field 5: Extreme maximum temperature Unit: °C Field 6: Extreme minimum temperature date Field 7: Extreme minimum temperature Unit: °C Field 8: Annual average temperature Unit: °C Field 9: Average temperature in January Unit: °C Field 10: Average temperature in July Unit: °C
2020-05-28 723 10 View Details
The data set includes data on precipitation, hail days and gale days in Tibet from 1989 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 7 fields. Field 1: Year Interpretation: Year of the data Field 2: Location Field 3: Annual precipitation Unit: mm Field 4: Precipitation during May to October Unit: mm Field 5: Precipitation during November to the next April Unit: mm Field 6: Hail day Field 7: Gale day
2020-05-28 523 6 View Details
The data set contains sequence data of the area composition of the water system basins 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 4 fields. Field 1: Year Interpretation: Year of the data Field 2: Basin Field 3: Area Unit: Square kilometers Field 4: Proportion Unit: %
2020-05-28 574 10 View Details
The data set includes data on lakes with areas greater than 200 square kilometers 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 has 5 fields. Field 1: Year Field 2: Lake Name Field 3: Lake elevation Unit: meter Field 4: Lake area Unit: square kilometer Field 5: Lake Type
2020-05-28 402 9 View Details
The data set contains data on the natural resources in Tibet from 1988 to 1994. The data were derived from the Tibet Society and Economics Statistical Yearbook and Tibet Statistical Yearbook. The accuracy of the data is consistent with that of the statistical yearbooks. The table contains 37 fields. Field 1: Year Field 2: Total surface area of the whole region, unit: 10,000 square kilometres. Field 3: Cultivated land area, unit: 10,000 mu (1 mu=0.0667 hectares) Field 4: Paddy field area, unit: 10,000 mu (1 mu=0.0667 hectares) Field 5: Forest area, unit: 10,000 mu (1 mu=0.0667 hectares) Field 6: Forest coverage proportion, unit: % Field 7: Forest stocks, unit: 100 million cubic metres Field 8: Grassland area, unit: 100 million mu (1 mu=0.0667 hectares) Field 9: Grassland available area, unit: 100 million mu (1 mu=0.0667 hectares) Field 10: Total annual runoff of rivers, unit: 100 million cubic metres. Field 11: Hydraulic resource reserves, unit: 10,000 kilowatt Field 12: Hydraulic potential exploitation amount, unit: 10,000 kilowatt Field 13: Length of the national boundary, unit: kilometres Field 14: Iron mine reserve amount, unit: 100 million tons Field 15: Chromite reserve amount, unit: 10,000 tons Field 16: Copper (ore), unit: 100 million tons Field 17: Borate ore reserve amount, unit: 10,000 tons Field 18: Salt reserve amount, unit: 100 million tons Field 19: Graphite reserve amount, unit: 10,000 tons Field 20: Gypsum reserve amount, unit: 100 million tons Field 21: Coal reserve amount, unit: 10,000 tons Field 22: Peat reserve amount, unit: 10,000 tons Field 23: Geothermal reserve amount, unit: 10,000 cubic metres / day and night Field 24: Species number of national key protected animals Field 25: Species number of class 1 national key protected animals Field 26: Species number of class 2 national key protected animals Field 27: Species number of national key protected plants Field 28: Species number of class 1 national key protected plants Field 29: Species number of class 2 national key protected plants Field 30: Species number of class 3 national key protected plants Field 31: Number of nature reserves Field 32: Number of national nature reserves Field 33: Number of local nature reserves Field 34: Total area of nature reserves, unit: 10,000 mu Field 35: Proportion of nature reserves to the total area of the region Field 36: Annual average precipitation, unit: mm Field 37: Annual sunshine duration, unit: hour
2020-05-28 371 7 View Details
Among the different regions in China, Tibet contains the largest number of natural ecosystem types. It is an ideal scientific research base and a natural laboratory for the geosciences, biology and other related disciplines. To better protect this precious natural heritage, to develop and utilize the natural resources rationally and to carry out scientific research, 13 national and autonomous regional nature reserves were established in the Tibetan Autonomous Region in 1984, covering an area of 326,000 square kilometres. These reserves account for 49.3% of the total area of nature reserves in China. By the end of 2012, Tibet had established 47 nature reserves of various types, including 9 national reserves, 14 provincial reserves, 3 municipal reserves, and 21 prefectural reserves, with a total area of 412,200 square kilometres. These reserves accounted for 34.35% of the land area of the Tibetan Autonomous Region and include 22 different types of ecological function reserves. The data were extracted from the Chinese Nature Reserve Specimen Information Sharing Infrastructure. Serial number: unified number of nature reserves Name of the nature reserves Administrative region: administrative region of the nature reserves Area (hectare) Primary protection objects Type: Type of nature reserves Class: Class of the nature reserves Established time: The date the nature reserves were established Responsible authority
2020-05-28 485 16 View Details
This is the groundwater level observation data set of Selincuo Lake. It can be used in Climatology, Environmental Change, Hydrologic Process in cold regions and other disciplinary areas. The data is observed from June 20, 2017 to August 18, 2017. It is measured by automatic water gauge and a piece of data is recorded every 60 minutes. The data includes the water pressure and water temperature of the groundwater level observation point on the west bank of Selincuo Lake. The original data is precise, with the pressure accurate to 0.001kP and the water temperature 0.001℃. The original data forms a continuous time series after quality control. And the daily mean index data is obtained through calculation. The data is stored as an excel file.
2020-05-28 703 1 View Details
This database is based on the theory of emergy analysis for 17 typical countries along the “Belt and Road” during 2008-2014. These countries are include Kazakhstan, Kyrgyzstan, Tajikistan, Uzbekistan, Turkmenistan, Mongolia, Russia, Pakistan, Bangladesh, Afghanistan, Nepal, Thailand, Myanmar, Ukraine, Moldova, Belarus and Azerbaijan. The basic data sources of this database mainly include detailed information, goods and services on environmental resource flows, natural capital stocks and human production activities. The data in database is calculated and evaluated based on the solar emergy. The database consists of three tables, which are the emergy analysis table of main resource flow, comprehensive emergy analysis table of the main resource category and the system emergy indicators analysis table. The emergy transformities used in this database is updated and calculated according to the emergy baseline (12.0E+24seJ/y) given by Pro. Brown in 2016. Based on the basic data in the database, it can effectively calculate the emergy-based sustainability index system, and give the reasons for the analysis results, the solution and future planning direction for the study country. It is of great significance to the development of the national ecological economic system and provide a scientific basis for the government to improve the sustainable development status of the national ecological economic system.
2020-05-28 406 7 View Details
This dataset is the boundary vector data of the provincial-level administrative units in the Qinghai-Tibet Plateau in 2015. The data is in the Shapefile format and includes provincial administrative units such as Tibet Autonomous Region, Qinghai Province, Gansu Province, Yunnan Province, Xinjiang Uygur Autonomous Region, and Sichuan Province. The administrative boundary within the plateau can be used for the geographical background research of the urbanization and ecological environment interaction stress of the Qinghai-Tibet Plateau. It is the basic geographic data for the statistics of the urbanization indicators of the provincial, forest, and population sectors of the Qinghai-Tibet Plateau. The data is obtained by means of data capture and collected through the administrative interface data acquisition API interface provided by the high-tech map. The data set uses the geographic coordinate system of WGS84.
2020-05-28 664 26 View Details
This dataset is the boundary vector data of county-level administrative units in Tibetan Plateau in 2015. The data is in Shapefile format and includes provincial administrative units such as Tibet Autonomous Region, Qinghai Province, Gansu Province, Yunnan Province, Xinjiang Uygur Autonomous Region, and Sichuan Province. The county-level administrative unit boundary within the plateau can be used for the geographical background research of the urbanization and ecological environment interaction stress of the Qinghai-Tibet Plateau. It is the basic geographic data for the statistics of the urbanization indicators of the county-level units of the Qinghai-Tibet Plateau. The data is obtained by means of data capture and collected through the administrative interface data acquisition API interface provided by the high-tech map. The data set uses the geographic coordinate system of WGS84.
2020-05-28 873 51 View Details
The dataset is clipped from the Chinese lake map by the vector boundary of the Qinghai-Tibet Plateau. The lake database is obtained by on-the-spot investigation, remote-sensing interpretation, which consist the area over 10-square-kilometer lakes. The lake code is based on lake classification. The Chinese Lake Code currently uses 8 digits. The first and second digits indicate the province where the lake is located; The third, fourth and fifth digits represent the sequence of the lake in the province; The sixth digit is on behalf of the lake surface area; The seventh number means the amount of water in the lake, that is, the volume of the lake.
2020-05-28 562 28 View Details
This dataset is the population index, which includes the dataset of Qinghai Province and Tibet Autonomous Region. It can be used for the coupling coordination relationship between urbanization and eco-environment in Qinghai-Tibet Plateau. The time span in Tibet Autonomous Region is 1995-2016. Permanent residents is based on the population census and the annual population change sampling survey. In addition to the total permanent population, the data were also calculated by gender and urban and rural areas. The time span is from 1952 to 2015 in Qinghai Province, and the indices are resident population, birth, death and natural increase. All data is from the statistical yearbook.
2020-05-28 655 21 View Details
This data contains part of the economic indicators of Qinghai province and Tibet Autonomous Region. The data statistics based on provinces can be used to construct the evaluation index system for the coupling coordination relationship between urbanization and eco-environment on the Tibetan Plateau. The data of the Tibet Autonomous Region contains seven indicators, including the gross domestic product (GDP), the primary, secondary and tertiary industries, industry, construction industry, and the per capita GDP, the time span is 1951-2016. The time span of the data set of Qinghai province is from 1952 to 2015, besides the above seven indicators, there is one more indicator of Qinghai province called agriculture forwdtry animal husbandry and fishery. All data are derived from the statistical yearbook, which is calculated at current prices. The gross domestic product (GDP) for 2005-2008 has been revised based on data from the second economic census.
2020-05-28 659 20 View Details
The remote sensing monitoring database of land use status in China is a multi-temporal land use status database covering the land area of China, which has been established after many years of accumulation under the support of the National Science and Technology Support Plan and the Key Direction Project of the Knowledge Innovation Project of the Chinese Academy of Sciences. It is the most accurate remote sensing monitoring data product of land use in China at present, which has played an important role in the national land resources survey, hydrology and ecological research. This data set covers the six western provinces in China: Xinjiang, Tibet, Qinghai, Yunnan, Sichuan and Gansu. Based on Landsat TM/ETM remote sensing images in the late 1970s、1980s、1995、2000、2005、2010、2015， 1KM raster data are generated by using the professional software and manual visual interpretation on the basis of vector data. The land use types include six primary land types which are cultivated land, forest land, grassland, water area, residential land and unused land, and 25 secondary types.
2020-05-28 1926 114 View Details
This data set is based on the evaluation of existing land cover data and the evidence theory，including a 1:100,000 land use map for the year 20 2000、a 1:1,000,000 vegetation map、a 1:1,000,000 swamp-wetland map, a glacier map and a Moderate-Resolution Imaging Spectroradiometer land cover map for China in 2001 (MODIS2001) were merged，Finally, the decision is made based on the principle of maximum trust, and a new 1KM land cover data of China in 2000 with IGBP classification system is produced. The new land cover data not only maintain the overall accuracy of China's land use data, but also supplement the information of vegetation types and vegetation seasons in China's vegetation map, update China's wetland map, add the latest information of China's glacier map, and make the classification system more general.
2020-05-28 1382 61 View Details
A multi-layer soil particle-size distribution dataset (sand, silt and clay content), based on USDA (United States Department of Agriculture) standard for regional land and climate modelling in China. was developed The 1:1,000,000 scale soil map of China and 8595 soil profiles from the Second National Soil Survey served as the starting point for this work. We reclassified the inconsistent soil profiles into the proper soil type of the map as much as possible because the soil classification names of the map units and profiles were not quite the same. The sand, silt and clay maps were derived using the polygon linkage method, which linked soil profiles and map polygons considering the distance between them, the sample sizes of the profiles, and soil classification information. For comparison, a soil type linkage was also generated by linking the map units and soil profiles with the same soil type. The quality of the derived soil fractions was reliable. Overall, the map polygon linkage offered better results than the soil type linkage or the Harmonized World Soil Database. The dataset, with a 1-km resolution, can be applied to land and climate modelling at a regional scale. Data characteristics： projection：projection Coverage: China Resolution: 0.00833 (about 1 km) Data format: FLT, TIFF Value range: 0%-100% Document describing： Floating point raster files include: Sand1. FLT, clay1. FLT -- surface (0-30cm) sand, clay content. Sand2. FLT, clay2. FLT -- content of sand and clay in the bottom layer (30-100cm). PSD. HDR -- header file: Ncols - the number of columns Nrows- rows Xllcorner - latitude in the lower left corner Yllcorner - longitude of the lower left corner Cellsize - cellsize NODATA_value - a null value byteorder - LSBFIRST, Least Significant Bit First TIFF raster files include: Sand1. Tif, clay1. Tif - surface (0-30cm) sand, clay content. Sand2. Tif, clay2. Tif - bottom layer (30-100cm) sand, clay content.
2020-05-28 1816 116 View Details
Snow cover dataset is produced by snow and cloud identification method based on optical instrument observation data, covering the time from 1989 to 2018 (two periods, from January to April and from October to December) and the region of Qinghai-Tibet Plateau (17°N-41°N, 65°E-106°E) with daily product, which takes equal latitude and longitude projection with 0.01°×0.01° spatial resolution, and characterizes whether the ground under clear sky or transparent thin cloud is covered by snow. The input data sources include AVHRR L1 data of NOAA and MetOp serials of satellites, and L1 data corresponding to AVHRR channels taken from TERRA/MODIS. Decision Tree algorithm (DT) with dynamic thresholds is employed independent of cloud mask and its cloud detection emphasizes on reserving snow, particularly under transparency cirrus. It considers a variety of methods for different situations, such as ice-cloud over the water-cloud, snow in forest and sand, thin snow or melting snow, etc. Besides those, setting dynamic threshold based on land-surface type, DEM and season variation, deleting false snow in low latitude forest covered by heavy aerosol or soot, referring to maximum monthly snowlines and minimum snow surface brightness temperature, and optimizing discrimination program, these techniques all contribute to DT. DT discriminates most snow and cloud under normal circumstances, but underestimates snow on the Qinghai-Tibet Plateau in October. Daily product achieves about 95% average coincidence rate of snow and non-snow identification compared to ground-based snow depth observation in years. The dataset is stored in the standard HDF4 files each having two SDSs of snow cover and quality code with the dimensions of 4100-column and 2400-line. Complete attribute descriptions is written in them.
2020-05-28 1718 56 View Details
This data set contains information on natural disasters in Tibet of nearly 50 years, including the time, place and the consequences of natural disasters such as drought, snows disasters, frost hazards, hail, floods, gales, and lightning disasters. Tibet is located on the southwest border of China and is the main body of the Tibetan Plateau. Due to the influence of the westerly winds, weather and strong warm and wet air currents from the Indian Ocean, the dry and wet seasons are obvious. In addition, the mountains and forests are numerous, and the terrain is complex in Tibet, which makes Tibet among those regions in China having the highest frequencies of natural disasters. The main meteorological disasters that cause significant damage to the production of agriculture and animal husbandry in Tibet are snows disasters, frost hazards, hail, floods and gales. According to incomplete statistics, the average annual disaster area from 1982 to 2000 was 28,440 hectares, of which the disaster area in 1983 was the largest, 203,700 hectares, followed by 1995 with a disaster area of 133,300 hectares. From the proportions of various disaster areas in the total area affected by the disasters, the proportion under drought is the largest, reaching 38%, followed by that under diseases and insect pests, which was 25%. Tibet is sparsely populated, and the ecological environment is very fragile. Traditional farming and animal husbandry production basically relies on people. Various meteorological disasters have caused heavy losses to the lives and property of the Tibetan people. Snow disasters topped the list of various meteorological disasters in Tibet. Tibet is one of the five largest pastoral areas in the country, and livestock is the most important source of production and livelihood for herdsmen. Snow disasters often cause large numbers of livestock death, significant property losses to herdsmen and threat to their lives. The data are extracted from the Tibet Volume of Chinese Meteorological Disaster Dictionary, with manual entry, summarizing and proofreading.
2020-05-27 670 34 View Details
The data set records the per capita GNI s of 1960-2017 countries along 65 countries along the belt and road. GNI per capita is gross national income divided by midyear population. GNI (formerly GNP) is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. Data sources:World Bank national accounts data, and OECD National Accounts data files. The data set contains 5 tables：GNI per capita (constant 2010 US$),GNI per capita (constant LCU),GNI per capita (current LCU),GNI per capita growth (annual %).
2020-05-27 403 4 View Details
The data set records the per capita electricity consumption of 1971-2014 countries along 65 countries along the belt and road. Data sources: IEA,http://www.iea.org/stats/index.asp.Data on electric power production and consumption are collected from national energy agencies by the International Energy Agency (IEA) and adjusted by the IEA to meet international definitions. Data are reported as net consumption as opposed to gross consumption. Net consumption excludes the energy consumed by the generating units. For all countries except the United States, total electric power consumption is equal total net electricity generation plus electricity imports minus electricity exports minus electricity distribution losses.
2020-05-27 440 2 View Details