The data are a digitized permafrost map along the Qinghai-Tibet Highway (1:600,000) (Boliang Tong, et al. 1983), which was compiled by Boliang Tong, shude Li, Jueying bu, and Guoqing Qiu from the Cold and Arid Regions Environmental and Engineering Research Institute of the Chinese Academy of Sciences (originally called the Lanzhou Institute of Glaciology and Cryopedology, Chinese Academy of Sciences) in 1981. The map aims to reflect the basic laws of permafrost distribution along the highway and its relationship with the main natural environmental factors. The basic data for the compilation of the map include hydrogeological and engineering geological survey results and maps along the Qinghai-Tibet Highway(1:200000) (First Hydrogeological Engineering Geological Brigade of Qinghai Province, Institute of Geomechanics of the Academy of Geological Science), the cryopedological research results of the Institute of Glaciology and Cryopedology of Chinese Academy of Sciences since 1960 in nine locations along the Qinghai-Tibet Highway (West Datan, Kunlun pass basin, Qingshuihe, Fenghuohe, Tuotuohe, the Sangma Basin, Buquhe, Tumengela, and Liangdaohe) and drilling data of the Golmud-Lhasa oil pipeline and aerial topographic data of the work area. Taking the 1:200000 topographic map as the working base map, a permafrost map was compiled, which was then downscaled to a 1:600000 map to ensure the accuracy of the map. To make up for the lack of data in a larger area along the line, the characteristics and principles of the frozen soils found in the nine frozen soil research points along the highway were applied to areas with the same geologic and geographical conditions; meanwhile, aerial photographs were used as supplements to the freeze-thaw geology and frozen soil characteristics. The permafrost map along the Qinghai-Tibet Highway (1:600,000) includes the annual average temperature contour map along the Qinghai-Tibet Highway (1:7,200,000) and the permafrost map along the Qinghai-Tibet Highway (1:600,000). The permafrost map along the Qinghai-Tibet Highway also contains information on permafrost types, lithology, frozen soil phenomena, types of through-melting zones, classification of frozen soil engineering, and geological structural fractures. These data contain only digitized permafrost information. The spatial coverage is from Daxitan on the Qinghai-Tibet Highway in the north to Sangxiong in the south and is nearly 800 kilometers long and 40-50 kilometers wide. The data set includes a vectorized and a scanned map of the permafrost map along the Qinghai-Tibet Highway. The attribute information of the map is as follows. A-1; Continuous permafrost; >0°C; remained as a frozen soil layer and isolation layer A-2; Continuous permafrost; 0~-0.5°C; 0-25 m A-3; Continuous permafrost; -0.5~-1.5°C; 25-60 m A-4; Continuous permafrost; -1.5~-3.5°C; 60-120 m A-5;Continuous permafrost;<-3.5°C;>120 m B-1; Island permafrost ground; Seasonal Frozen Ground; B-2; Continuous permafrost; >0°C; remained as a frozen soil layer and isolation layer B-3; Island permafrost extent; 0~-0.5°C; 0-25 m B-4; Island permafrost extent; -0.5~-1.5°C; 25-60 m B-5; Island permafrost extent; -1.5~-3.5°C; 60-120 m
TONG Boliang, LI Shude, BO Jueying, QIU Guoqing
The data set records the population of ethnic minorities in Qinghai province from 1952 to 2019. The data is divided by the total population of ethnic minorities, Tibetan, Hui, Tu, Salar, Mongolian and other ethnic groups, and the proportion of the total population in the province. The data are collected from qinghai Statistical Yearbook released by Qinghai Provincial Bureau of Statistics. The dataset contains 22 data tables, which are: Population of ethnic minorities in the province, 1952-1998. XLS Population of ethnic minorities in the province, 1952-1999. XLS Population of ethnic minorities in The province, 1952-2000. XLS Population of ethnic minorities in the province, 1952-2001. XLS Population of ethnic minorities 1952-2002. XLS Population of ethnic minorities 1952-2003. XLS Population of ethnic minorities in main years 1952-2004. XLS Population of ethnic minorities in main years 1952-2006. XLS Population of ethnic minorities in main years 1952-2008. XLS Population of ethnic minorities in main years 1952-2009. XLS Population of ethnic minorities in main years 1982-2010. XLS Population of ethnic minorities in main years 1985-2007. XLS Population of ethnic minorities in main years 1990-2005. XLS Population of ethnic minorities in main years 2000-2011. XLS Population of ethnic minorities in main years 2006-2013. XLS Population of ethnic minorities in main years 2006-2014. XLS Population of ethnic minorities in main years 2006-2015. XLS Population of ethnic minorities in main years 2006-2016. XLS Population of ethnic minorities in main years 2006-2019. XLS Population of ethnic minorities in main years 2005-2012. XLS Population of ethnic minorities, 2006-2017. XLS Population of ethnic minorities, 2006-2018. XLS data table structure is the same. For example, the data table of the population of ethnic minorities in the province from 1952 to 1998 has 8 fields: Field 1: ethnic group Field 2:1952 Field 3:1978 Field 4:1982 Field 5:1990 Field 6:1996 Field 7:1997 Field 8:1998
Qinghai Provincial Bureau of Statistics
The dataset is the ground verification point dataset of land cover and vegetation type in the Hoh Xil (in the northwest of Qinghai Province) which collected during August 2018. In the dataset, the homogeneous patches are considered as the main targets of this collection. They are easy to be recognized out and distinguished from other vegetation types. And these samples have high representativeness comparing with other land surface features. In each sample, the geographical references, longitude and latitude (degree, minute, second), time (24h) and elevation (0.1m) are recorded firstly according to GPS positioning. Vegetation types, constructive species, characteristics, land types and features, landmarks, etc. are recorded into the property table manually for checking in laboratory. At last, each sample place has been taken at least 1 photography. In this dataset, 90% or more samples have been taken 2 or more in field landscape photographs for land use type and vegetation classification examination. We have carefully examined the position accuracy of each sample in Google Earth. After 2 rounds of checking and examination, the accuracy and reliability of the property of each sample have been guaranteed.
WANG Xufeng
The dataset is the ground verification point dataset of land cover and vegetation type in the Source Region of Yellow River (in the north of Zaling Lake, Qinghai Province) which collected during August 2018. In the dataset, the homogeneous patches are considered as the main targets of this collection. They are easy to be recognized out and distinguished from other vegetation types. And these samples have high representativeness comparing with other land surface features. In each sample, the geographical references, longitude and latitude (degree, minute, second), time (24h) and elevation (0.1m) are recorded firstly according to GPS positioning. Vegetation types, constructive species, characteristics, land types and features, landmarks, etc. are recorded into the property table manually for checking in laboratory. At last, each sample place has been taken at least 1 photography. In this dataset, 90% or more samples have been taken 2 or more in field landscape photographs for land use type and vegetation classification examination. We have carefully examined the position accuracy of each sample in Google Earth. After 2 rounds of checking and examination, the accuracy and reliability of the property of each sample have been guaranteed.
WANG Xufeng
The dataset is the ground verification point dataset of land cover and vegetation type in the Source Region of the Yangtze River (in the south of Qinghai Province) which collected during August 2018. In the dataset, the homogeneous patches are considered as the main targets of this collection. They are easy to be recognized out and distinguished from other vegetation types. And these samples have high representativeness comparing with other land surface features. In each sample, the geographical references, longitude and latitude (degree, minute, second), time (24h) and elevation (0.1m) are recorded firstly according to GPS positioning. Vegetation types, constructive species, characteristics, land types and features, landmarks, etc. are recorded into the property table manually for checking in laboratory. At last, each sample place has been taken at least 1 photography. In this dataset, 90% or more samples have been taken 2 or more in field landscape photographs for land use type and vegetation classification examination. We have carefully examined the position accuracy of each sample in Google Earth. After 2 rounds of checking and examination, the accuracy and reliability of the property of each sample have been guaranteed.
WANG Xufeng
The data set records the statistics of precipitation in major areas of Qinghai Province from 2001 to 2020, and the data is divided by month and year. The data are collected from qinghai Statistical Yearbook released by Qinghai Provincial Bureau of Statistics. The dataset contains 20 data tables, all of which have the same structure. For example, the data table for 2020 has 11 fields: Field 1: month Field 2: region Field 3: Xining Field 4: Haidong Field 5: Haibei Field 6: South Yellow Field 7: Hainan Field 8: Golo Field 9: Yushu Field 10: Hersey Field 11: Golmud City
Qinghai Provincial Bureau of Statistics
This data set contains demographic structure and quantity statistics of Qinghai from 1952 to 2016. 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. Table 1: The table of rural grassroots organizations contains 10 fields. Field 1: Year of the data Field 2: Number of townships and towns Field 3: Number of townships Field 4: Number of towns Field 5: Number of villagers’ committees Field 6: Number of households in rural areas, unit: 10,000 Field 7: Population of rural areas, unit: 10,000 Field 8: Number of workers in rural areas, unit: 10,000 Field 9: Number of male workers, unit: 10,000 Field 10: Number of female workers, unit: 10,000 Table 2: The table of demographic statistics in Qinghai contains 8 fields. Field 1: Year of the data Field 2: Total population Field 3: Male population, unit: 10,000 Field 4: Female population, unit: 10,000 Field 5: Urban population, unit: 10,000 Field 6: Rural population, unit: 10,000 Field 7: Agricultural population, unit: 10,000 Field 8: Non-agricultural population, unit: 10,000 Table 3: The table describing the structure of rural workers contains 9 fields. Field 1: Year of the data Field 2: Number of workers in agricultural, forestry, animal husbandry and fishery sectors, unit: 10,000 Field 3: Number of workers in industry, unit: 10,000 Field 4: Number of workers in the construction sector, unit: 10,000 Field 5: Number of workers in the transportation, storage industry and post trade sectors, unit: 10,000 Field 6: Number of workers in the information industry, unit: 10,000 Field 7: Number of workers in commerce, unit: 10,000 Field 8: Number of workers in the accommodation and catering industry, unit: 10,000 Field 9: Number of workers in other industries Table 4: The table of demographic statistics for each county contains 9 fields. Field 1: Districts and counties Field 2: Year Field 3: Year-end total household number Field 4: Rural household number Field 5: Year-end total population Field 6: Rural total population Field 7: Year-end workers Field 8: Rural workers Field 9: Agriculture, forestry, animal husbandry and fishery
Qinghai Provincial Bureau of Statistics
The data set recorded the sequence data of penned livestock number, full-grown livestock number, and outputs of meat, eggs, milk, wool and woolen products from 1978 to 2016.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 set contains three tables: livestock feeding status, main livestock products output, and number of full-grown livestock. Table 1: The table of livestock feeding status contains 7 fields. Field 1: Year Interpretation: Year of the data Field 2: Year-end penned large livestock Interpretation: Number of year-end penned large livestock Unit: 10,000 Field 3: Cattle Interpretation: Number of year-end penned cattle Unit: 10,000 Field 4: Horse Interpretation: Number of year-end penned horses Unit: 10,000 Field 5: Goat Interpretation: Number of year-end penned goats Unit: 10,000 Field 6: Sheep Interpretation: Number of year-end penned sheep Unit: 10,000 Field 7: Pig Interpretation: Number of year-end penned pigs Unit: 10,000 Table 2: The table of full-grown livestock number contains 5 fields. Field 1: Year Interpretation: Year of the data Field 2: Number of full-grown large livestock Unit: 10,000 Field 3: Number of full-grown goats Unit: 10,000 Field 4: Number of full-grown pigs Unit: 10,000 Field 5: Number of full-grown poultry Unit: 10,000 Table 3: The table of main livestock products output contains 14 fields. Field 1: Year Interpretation: Year of the data Field 2: Total output of meat Interpretation: Total output of meat Unit: ton Field 3: Pork Interpretation: Pork output Unit: ton Field 4: Beef Interpretation: Beef output Unit: ton Field 5: Mutton Interpretation: Mutton output Unit: ton Field 6: Other kinds of meat Interpretation: Output of other kinds of meat Unit: ton Field 7: Milk Interpretation: Output of milk Unit: ton Field 8: Cow milk Interpretation: Output of cow milk Unit: ton Field 9: Wool Interpretation: Output of wool Unit: ton Field 10: Sheep wool Interpretation: Output of sheep wool Unit: ton Field 11: Cashmere Interpretation: Output of cashmere Unit: ton Field 12: Cattle hair and villus Interpretation: Output of cattle hair and villus Unit: ton Field 13: Honey Interpretation: Output of honey Unit: ton Field 14: Poultry eggs Interpretation: Output of poultry eggs Unit: ton
Qinghai Provincial Bureau of Statistics
"The dataset records average sunshine hours in major areas of Qinghai province from 1998 to 2020. The data are divided by month and year scale. The data are collected from qinghai Statistical Yearbook released by Qinghai Provincial Bureau of Statistics. The dataset contains 23 data tables, all of which have the same structure. For example, the 2001 data table has 9 fields: Field 1: month Field 2: Xining Field 3: Safe Field 4: Door source Field 5: Chabcha Field 6: Colleagues Field 7: Taibu Field 8: Gu Gu Field 9: Delingha"
Qinghai Provincial Bureau of Statistics
From April 2020 to August 2020, sub project 3 collected 51 ear tissue samples of Qinghai fine wool sheep distributed in Haiyan County, Haixi Mongolian and Tibetan Autonomous Prefecture, Qinghai Province, 50 blood samples of Oula sheep in Tongde County, Hainan Tibetan Autonomous Prefecture, 50 blood samples of yak in Tongde County, Hainan Tibetan Autonomous Prefecture, 60 blood samples of Haidong donkey in Datong Hui and Tu Autonomous County, Xining City, and tissue samples A total of 211 copies. At the same time, the information of body length, body height, weight, age and gender, as well as the data of economic traits such as litter size, wool fineness and wool length were recorded. The individual photos were taken, and the information of feeding mode and epidemic situation were obtained through questionnaire survey.
TIAN Fei
The dataset records the average temperature in major areas of Qinghai Province from 1998 to 2020, and the data are divided by monthly and annual average indicators. The data are collected from qinghai Statistical Yearbook released by Qinghai Provincial Bureau of Statistics. The dataset contains 20 data tables with the same structure. For example, the data table for 2020 has 11 fields: Field 1: month Field 2: region Field 3: Xining Field 4: Haidong Field 5: Haibei Field 6: South Yellow Field 7: Hainan Field 8: Golo Field 9: Yushu Field 10: Hersey Field 11: Golmud City
Qinghai Provincial Bureau of Statistics
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: ‰
Qinghai Provincial Bureau of Statistics
This data set records the altitude elevation of the main tourist attractions in Qinghai Province from 2002 to 2020. The data are based on the main tourist attractions in Qinghai Province, such as thar temple, Qinghai Lake, Qutan temple, kambula National Forest Park, the former residence of the 10th Panchen Lama, Mengda Tianchi, longbaotan black necked Crane nature reserve, the source of the Yangtze River, Chaerhan Salt Lake, bird island, Huzhu Beishan National Forest Park, the source of the Yellow River and a Nimaqing mountain, Jinyintan grassland scenery, bukadaban peak, Kunlun mountain pass, BeiChan temple, Qinghai Museum, Laoye Mountain, Huzhu Beishan National Forest Park, Jiezi mosque, Wendu temple, xiazong temple, Xiaqiong temple, Youning temple, Riyue mountain, Daotang River, Longyang Gorge, Qinghai Lake Resort, Yuhuangge, Chaka Salt Lake, atomic City, Lijiaxia gorge, Nanzong temple, Longwu temple Maixiu forest farm, Tubo burial tomb, Dulan international hunting ground and Hoh Xil no man's land. The data are compiled from the statistical yearbook of Qinghai Province issued by Qinghai Provincial Bureau of statistics. The dataset contains 19 data tables: The elevation of the main tourist attractions in the province was in 2002 xls The elevation of the main tourist attractions in the province was in 2003 xls The elevation of the main tourist attractions in the province was in 2004 xls The elevation of the main tourist attractions in the province was in 2006 xls The elevation of the main tourist attractions in the province was in 2007 xls The elevation of the main tourist attractions was in 2007 xls The elevation of the main tourist attractions in 2008 xls The elevation of main tourist attractions was in 2009 xls The elevation of main tourist attractions was in 2010 xls Elevation of main tourist attractions in 2011 xls Elevation of main tourist attractions in 2012 xls Elevation of main tourist attractions in 2013 xls Elevation of main tourist attractions in 2015 xls Elevation of main tourist attractions in 2016 xls Elevation of main tourist attractions in 2017 xls The elevation of the main tourist attractions will be in 2019 xls Elevation of main tourist attractions in Qinghai Province (2019) xls Elevation of main tourist attractions in Qinghai Province (2020) xls The elevation of the main tourist attractions in Qinghai Province (2020) is 1 xls , the data table structure is the same. For example, there are three fields in the elevation (2003) data table of major tourist attractions in the province: Field 1: name of tourist attraction Field 2: altitude (m) Field 3: geographic location
Qinghai Provincial Bureau of Statistics
The data set includes data of land and natural resources in Qinghai from 1984 to 2012. The data were derived from the Qinghai Society and Economics Statistical Yearbook and the Qinghai Statistical Yearbook. P.S: The land use data have not been updated in the yearbook since 2008. The 2008 data have been cited; therefore. The accuracy of the data is consistent with that of the statistical yearbook. There are two tables, one for natural resources data of every year, and the other is for land use data in different regions. “The land and natural resources in Qinghai” table contains the following information: Year, land, total land area, mountain, basin, river valley, Gobi desert, hilly land; cultivated land area, irrigated land; total grassland area, usable grassland, winter and spring grassland, summer and autumn grassland; forest area, forest coverage ratio, sparse forestland, shrub land, wood stocks; annual total surface runoff, Yellow River Basin, Yangtze River Basin, hydraulic theoretical reserves, installed capacity, annual power generation; coal reserves, iron ore reserves, asbestos reserves, pool salt, magnesium salt, potassium salt, boron, gold ore, lead ore, zinc ore, antimony ore, and limestone for cement. The “Land use in different regions” table includes the following information for each prefecture from 2003 to 2012: Year, region name, total area, cultivated land, garden land, forestland, grassplot, residential land use and industrial and mining land use, land for transportation, land for water conservancy facilities, and unused land.
Qinghai Provincial Bureau of Statistics
The data set records the water quality evaluation results of the monitoring sections of the Yangtze River, Yellow River and Huangshui (2010-2012). The data is collected from Yushu ecological environment bureau. The data set contains 18 files, which are: water quality assessment of national control section of Yangtze River in April 2010, water quality assessment of national control section of Yangtze River in May 2010, water quality assessment of national control section of Yangtze River in September 2010, water quality assessment of national control section of Yangtze River in October 2010, etc. the data table structure is the same. There are seven fields in each data table Field 1: monitoring section Field 2: classification of water environment functional areas Field 3: water quality category Field 4: main pollution indicators Field 5: water quality status Field 6: water quality last month Field 7: water quality in the same period of last year
Ecological Environment Bureau of Yushu Prefecture
This data set records the statistical bulletin of national economic and social development of Guoluo Tibetan Autonomous Prefecture in Qinghai Province in 2019. The data is collected from the Statistics Bureau of Qinghai Province. The data set contains a word file, which is the statistical bulletin of national economic and social development of goluo Tibetan Autonomous Prefecture in Qinghai Province in 2019. The contents of the communique cover the total economic volume and structure of the whole Prefecture, the development of agriculture and animal husbandry, the development of industry, the investment in fixed assets, the trade and price situation, the financial situation, the development of transportation, posts and telecommunications and tourism, the environmental protection and forestry, the development of education, science and technology, the culture and health of the whole Prefecture The state of the enterprise, the state of the population, people's life and social security development, etc.
Qinghai Provincial Bureau of Statistics
This data set includes meteorological data observed by the carbon flux station in the Guoluo Army Ranch in Qinghai. The temporal coverage is from 2005 to 2009, and the temporal resolution is 1 day. Meteorological and carbon flux data observation methods: vorticity-related observation instruments were used for automatic recording; biomass observation method: harvest method, weighing in a 60-degree oven for 48 hours. Both carbon flux and meteorological data were automatically recorded by the instruments and manually checked. During the data observation process, the operation of the instrument and the selection of the observation objects were in strict accordance with professional requirements, and the data could be applied to plant leaf photosynthetic parameter simulation and productivity estimation. This data contains observation items as follows: Temperature °C Precipitation mm Wind speed m/s Soil temperature at 5 cm depth °C Photosynthetically active radiation µmol/m²s Total radiation W/m²
ZHAO Xinquan
The data set records the typical geological disasters in Qinghai Province from 2011 to 2018. The data set includes 10 data tables, which are: typical geological disasters in 2011, 2012, 2013, 2013, distribution, 2014, etc The data structure of typical geological disasters in 2018 is the same. Each data table has five fields, such as the typical geological disasters in 2011: Field 1: Location Field 2: disaster type Field 3: time of occurrence Field 4: scale Field 5: hazards and losses
ZHAO Hu
This data set records the statistical bulletin of national economic and social development of Haidong city in Qinghai Province in 2019. The data is collected from the Statistics Bureau of Qinghai Province. The data set contains a word file, which is the statistical bulletin of national economic and social development of Haidong in Qinghai Province in 2019. The Gazette covers the annual gross domestic product of the whole city, the completion of the regional public budget revenue, the household registration population and its changes throughout the year, the annual total consumption price index of the whole city, the planting and animal husbandry, the industrial and construction industries, the annual fixed assets investment of the whole City, the total retail sales of social consumer goods, and the total value of the total import and export of the whole city in the whole year. Information statistics and comparative data on the added value of wholesale and retail industry, cultural tourism, health and sports, residents' income, consumption and social security, environment and emergency management, etc.
Qinghai Provincial Bureau of Statistics
This data set contains time series data on the total planting area, planting area of various grain crops and cash crops, and planting area of vegetables from 1978 to 2016. 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. Table 1: The table of total crop planting area contains 9 fields. Field 1: Year of the data Field 2: The total planting area of crops, unit: 1000 hectares Field 3: Planting area of grain crops, unit: 1000 hectares Field 4: Planting area of wheat, unit: 1000 hectares Field 5: Planting area of coarse crops, unit: 1000 hectares Field 6: Planting area of tuber crops, unit: 1000 hectares Field 7: Planting area of cash crops, unit: 1000 hectares Field 8: Planting area of oil crops, unit: 1000 hectares Field 9: Planting area of vegetables, unit: 1000 hectares Table 2: The table of the planting area in each county contains 4 fields. Field 1: Districts and counties Field 2: Year of the data Field 3: Total planting area of crops, unit: hectare Field 4: Planting area of grain crops, unit: hectare
Qinghai Provincial Bureau of Statistics
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