This dataset is based on the Tibet Statistical Yearbook and Qinghai Statistical Yearbook (2020). The two books contain statistical data on the economic and social development of the Tibet Autonomous Region and Qinghai Province since 2019, mainly from 1951 to 2020. Extract the agricultural aspects, from the basic situation of rural areas and agriculture, the basic situation of rural areas, rural employees, the total output value of agriculture, forestry, animal husbandry and fishery in sub-regional cities, the sown area of main crops, the output of main agricultural products, the output per unit area of main agricultural products, and the sown area of crops It is an important statistical data for people from all walks of life at home and abroad to understand the Qinghai-Tibet Plateau and the Qinghai-Tibet Plateau.
TANG Yawei TANG Yawei
The dataset includes climate suitability zonation, climate and soil suitability zonation and climate and soil terrain suitability zonation dataset of 8 forages. The dataset can provide important data support for artificial grassland construction. Based on the climate index model and maximum entropy model, the climate suitability index of each pasture was constructed by using the temperature, precipitation data of the last 40 years and elevation data, and considering the soil type, soil organic matter content and topographic factors, the planting zonation of eight pasture species was established in Qinghai. Eight forages are important forage resources in alpine areas. The accuracy of climate suitability index was ensured by field investigation, and the practicability of dataset of pasture planting zonation was ensured by comprehensive consideration of climate factors and soil topographic factors. Artificial grassland planting is not only the main means of ecological restoration of degraded grassland, but also an important part of grassland production structure adjustment. Reasonable and scientific grass planting is the foundation. The dataset of forage planting zonation has an important application prospect in the implementation of major ecological projects and the scientific management of grassland.
ZHOU Huakun , SU Wenjiang , ZHOU Bingrong , SHI Mingming , ZHAO Huifang
The data set records the statistical table of groundwater level dynamic changes in various monitoring areas of Qinghai Province from 2015 to 2018. The data are recorded from the Department of natural resources of Qinghai Province, and the data set contains four data tables, which are: the statistical table of groundwater level dynamic change in each monitoring area of Qinghai Province in 2015, the statistical table of groundwater level dynamic change in each monitoring area of Qinghai Province in 2016, the statistical table of groundwater level dynamic change in each monitoring area of Qinghai Province in 2017, and the statistical table of groundwater level dynamic change in each monitoring area of Qinghai Province in 2018 The data table has the same structure and contains 7 fields Field 1: "geographic location" Field 2: "basic balance area (km2)" Field 3: "percentage of monitoring area (%)" Field 4: "weak descent area (km2)" Field 5: "percentage (%) of monitored area" Field 6: "strong uplift area (km2)" Field 7: "percentage (%) of monitored area"
Department of Natural Resources of Qinghai Province
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 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
1. The data content includes: year, month, day, hour, longitude, latitude, altitude, meridional (UQ) and latitudinal (VQ) components of water vapor flux; 2. Data source and processing method: GPS meteorological sounding data of voyages in the eastern Indian Ocean, and calculate water vapor flux through relative humidity, wind field, air pressure and altitude; 3. Data quality description: vertical continuous observation with 1 second vertical resolution; 4. Data application achievements and prospects: Study on the changes of water vapor transport in the tropical Indian Ocean;
LIU Zhaofei, YAO Zhijun
The data includes ten typical hydropower stations in Datong River Basin of Qinghai-Tibet Plateau in July 2020, including Duolong Hydropower Station, Gousikou Hydropower Station, Jinxing Hydropower Station, Kasuoxia Hydropower Station, Liancheng Hydropower Station, Nazixia Hydropower Station, Stone Gorge Hydropower Station, Tianwanggou Hydropower Station, Tiemai Hydropower Station and Xueyitan Hydropower Station. Data are helpful to study the distribution and use of hydropower stations in Datong River Basin. The data were taken by the expedition team through aerial photography using DJI UAV RTK and Royal Series, and spliced by DJI mapping software. The aerial image data has high definition, which can obviously observe the water level difference between upstream and downstream of the hydropower station and the topographic distribution around the hydropower station. The data can be applied to the research field of hydropower stations in Qinghai-Tibet Plateau, providing relevant analysis data.
FU Bin
This data set contains experimentally measured soil nutrient data collected in typical small watersheds in Sichuan Province, Tibet Autonomous Region and Qinghai Province. The data comes from the survey of grassland, cultivated land, and woodland in Minhe County, Menyuan County and the east area of Qinghai Lake in the second Qinghai-Tibet Plateau scientific expedition, and recorded detailed soil parameters (including organic carbon, ph, soil Cation exchange capacity, water content, etc.) can provide important values for tracing the source of soil water erosion in small watershed areas and understanding the soil environment.
SU Zhengan
The data set records the output information of main crops in Qinghai Province from 1978 to 2016, mainly including grain, oil, fruit, meat and eggs and main industrial products, aluminum, crude oil, steel, cement and power generation. The data set contains three data tables (1. The data table of main industrial and agricultural products per capita has 17 fields; 2. The data table of crop production by counties has 13 fields; 3. The data table of main industrial and agricultural products per capita and main agricultural products. There are 6 fields in total). The data comes from: "Qinghai Social and Economic Statistical Yearbook" and "Qinghai Statistical Yearbook", with the same precision as the statistical yearbook extracted from the data. This data set is of great value for studying food security and agricultural production in Qinghai Province.
SU Zhengan
The Aerial photography dataset of typical small watersheds in Qinghai Province (Aerial photography dataset of typical small watersheds in Qinghai Province) is derived from the second Qinghai-Tibet Plateau scientific investigation in July 2020, using DJI drones to conduct surveys on small watersheds in Minhe County, Qinghai Province and Qinghai Province. Aerial photography of the surface sample zone in the east of the lake, including orthophoto (including three bands of red, green and blue), multi-spectrum, and point cloud data. All files in this dataset can be directly opened, viewed and processed with ArcGIS and ENVI software.
SU Zhengan
The data set is the vegetation sample survey photos of Qilian County in Qinghai Province during the second comprehensive scientific expedition to the Qinghai-Tibet Plateau. Iincluding the survey photos of 28 sample points in Qilian County in 2020. The photos of each sample point are placed in a separate In a folder, the folder is named the sample number. The photos of each sample point include photos of the landscape around the sample point, photos of the plant community in the sample square and close-up photos of the dominant species. The vegetation in the sample can be observed The status of the community, the status of the soil surface and the slope of the surrounding sampling area, human interference, etc. The photos are all original images, in jpg format, taken with a mobile phone or camera, and the specific latitude and longitude information of the sampling points are in a separate Excel table in the compressed package In, you can compare and view.
SHANG Zhanhuan
In 2017, 27 surface sediments were collected in Qinghai Lake by gravity sampler, and the top 1cm was taken as the surface layer, which was freeze-dried and ground into powder after being taken back to the laboratory. Before testing the content of organic carbon and nitrogen, 1mol / L hydrochloric acid should be used to stir the reaction for more than 10 hours, so that the carbonate is completely removed, then dried and ground, and the organic carbon and nitrogen are tested on the element analyzer. The total inorganic carbon content is the carbonate content of the whole rock powder sample measured by infrared spectrum, which is then calculated as the total inorganic carbon content. The contents of organic carbon and inorganic carbon constitute the total carbon content of the lake, and they are close to each other, indicating that the inorganic carbon burial flux and organic carbon burial flux of Qinghai Lake are similar.
MENG Xianqiang
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 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 data set records the current situation of land use in Qinghai Province. The data is divided by cultivated land, garden land, woodland, grassland, residential land, industrial and mining land, transportation land, water conservancy facilities land and unused land. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of 8 data tables Land use status 2002.xls Land use status in 2003.xls Land use status 2004.xls Land use status 2006.xls Land use status 2007.xls Land use status in 2008.xls Land use status in 2009.xls The structure of 2012. XLS data table is the same. For example, there are four fields in the data table of land use status in 2002 Field 1: area at the beginning of the year Field 2: area reduced during the year Field 3: area increased during the year Field 4: year end area
Qinghai Provincial Bureau of Statistics
The data set records the monthly water quality monitoring and evaluation data of Huangshui river monitoring section from January 2008 to June 2020. The data set consists of 146 Excel / PDF data files. They are water quality assessment.xls in January 2008, water quality assessment.xls in February 2008 Water quality assessment of national control section of Huangshui River in June 2020.xls. Data monitoring points include: Jintan and zhamalong section of Huangshui mainstream; Xiaoxia bridge section; Minhe bridge section. The detection indicators include: water environment function zoning category, water quality category, main pollution indicators, water quality status, water quality status in last month, and water quality status in the same period of last year. The data table has the same structure and contains 7 fields Field 1: section name Field 2: water environment function zoning category 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 last year
Department of Ecology and Environment of Qinghai Province
The data set records the main economic indicators of key enterprise groups in Qinghai Province from 2001 to 2008, and the data is divided by year. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains eight data tables, each of which has the same structure. For example, the 2001 data table has 15 fields: Field 1: indicator name Field 2: number of groups Field 3: total assets Field 4: accumulated depreciation Field 5: R & D expenses Field 6: minority shareholders' equity at the end of the year Field 7: year end number of employees Field 8: employees on duty Field 9: total profit Field 10: Investment completion amount of fixed assets Field 11: investment income Field 12: Equity Field 13: main business income Field 14: operating cost Field 15: other practitioners
Qinghai Provincial Bureau of Statistics
The data set records the dynamic statistical data of groundwater level in the monitoring area of Ping'an district (Ping'an County) of Xining city from 2014 to 2018. The data is collected from the Department of natural resources of Qinghai Province, and the data set contains five data tables, which are: the groundwater level dynamic of Haidong monitoring area in 2014, the groundwater level dynamic statistical table of Ping'an monitoring area in 2015, the groundwater level dynamic statistical table of Ping'an monitoring area in 2016, the groundwater level dynamic statistical table of Ping'an monitoring area in 2017, and the groundwater level dynamic statistical table of Ping'an monitoring area in 2018 Sketch Map. The data table has the same structure and contains four fields Field 1: year Field 2: n16 Field 3: n34 Field 4: N46
Department of Natural Resources of Qinghai Province
The data set records the statistical data of land use status in Huangnan Prefecture of Qinghai Province from 2003 to 2012, which is divided by industry, region, affiliation and registration type. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of 9 data tables Land use status in Huangnan Prefecture, 2003.xls Land use status of Huangnan Prefecture, 2006.xls Land use status in Huangnan Prefecture, 2008 1.xls Land use status in Huangnan Prefecture, 2008 2.xls Land use status of Huangnan Prefecture, 2012.xls Land use status in Huangnan Prefecture, 2004.xls Land use status of Huangnan Prefecture, 2006.xls Land use status of Huangnan Prefecture 2007.xls Current situation of land use in Huangnan Prefecture The data table structure is the same. For example, there are four fields in the data table of land use status in Huangnan Prefecture in 2003 Field 1: area at the beginning of the year Field 2: area reduced during the year Field 3: area increased during the year Field 4: year end area
Qinghai Provincial Bureau of Statistics
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