The data set include crop leaf stomatal conductance observed at four sample regions, that is the soil moisture control experimental field at Daman county, and the super station, and Shiqiao sample plots at Wuxing village in Zhangye city. 1) Objective Crop leaf stomatal conductance, a key biophysical parameter, was observed as model parameter or a priori knowledge for crop growth model, or evapotranspiration estimation. 2) Measuring instruments Leaf porometer. 3) Measuring site a. the soil moisture control experimental field at Daman county, Twelve soil water treatments are set. The crop leaf stomatal conductance for each treatment is measured on 17, 23 and 29 May, and 3, 9, 14 and 24 June, and 5 and 12 July. b. the Super Station The crop leaf stomatal conductance at the super station is measured on 22 and 28 May, 5, 11, 18, and 25 June, and 1, 8, 15, 22 and 31 July, 9, 15 and 22 August, and 3 and 11 September. c. the Shiqiao sample site The crop leaf stomatal conductance at the Shiqiao village is measured on 17, 22 and 28 May, 4, 11, 17 and 25 June, 1, 8, 15, 22, and 30 July, 8, 16 and 27 August, and 9 September. 4) Data processing The observational data was recorded in the sheets and reorganized in the EXCEL sheets. The time used in this dataset is in UTC+8 Time.
Xu Fengying, Wang Jing, Huang Yongsheng, LI Xin, MA Mingguo
1. Overview of data This data is based on the latest googleearth remote sensing image data to establish the spatial distribution database of crops in Ganzhou District of Zhangye City. 2. Data content Based on the spatial distribution of maize seed production focused by the project, the land use types in the study area are divided into 14 types (maize seed production land, spring wheat land, vegetable land, greenhouse land, intercropping land, rice land, water area, wetland, forest land, urban and rural industrial and mining residential land, roads, railways and unused land). 3. Space-time range The data range includes 19 villages and towns including Pingshanhu, Shajing, Wujiang River, Jingan, Mingyong, Sanzha, Ganjun, Xindun, Shangqin, Jiantan, Chengguan Town, Liangjiadun, Chang 'an, Dangzhai, Xiaoman, Longqu, Daman, Huazhai and Anyang. The data type is vector polygon and stored in Shape format. The data range covers Ganzhou District.
XU Zhongmin
The field experiments of water consumption and irrigation water productivity of corn and cotton were arranged in 2012 and 2013, and the field experiments of irrigation water productivity of corn and sunflower under different mulching and cultivation methods were arranged in 2014. The characteristics of water consumption and irrigation water demand of three crops under different soil conditions, as well as the relationship between key soil properties and crop yield and irrigation water productivity were obtained.
SU Yongzhong
According to the characteristics of the selected field and its surrounding area, a trime tube is arranged in the corn field, and 5 trime tubes are arranged in a direction perpendicular to the field path. When monitoring soil moisture content in the TDR vertical direction, the unit is every 10cm. Monitor down. Location: N 38 ° 52′27.6 ″ E 100 ° 21′14.0 ″ The submitted data includes the water content of the farmland and its surrounding soil (TDR monitoring) after three irrigations in a selected farmland in Yingke Irrigation District, encrypted monitoring after irrigation, one group every 3 hours within 24 hours, and 3 groups per day for the next 5 days. -10 days are two groups per day, and 10-15 days are one group per day.
HUANG Guanhua, JIANG Yao
The data set contains agricultural economic data of all counties and regions in the Tibetan Plateau in 1980-2015, and covering the total number of households and total population in rural areas, agricultural population, rural labor force, cultivated land, paddy field area, the dry land area, power of agricultural machinery, agricultural vehicles, mechanical ploughing area, irrigation area, consumption of chemical fertilizers electricity use, gross output value of agriculture, forestry, animal husbandry and fishery, the output of cattle, pig, sheep, meat, poultry, and fish, the sown area of grain, the output of grain, cotton, oil and all kinds of crops, and characteristic agricultural products and livestock production and other relevant data.The data came from the statistical yearbook of the provinces included in the Tibetan Plateau.The data are of good quality and can be used to analyze the socio-economic and agricultural development of qinghai-tibet plateau.
LV Changhe
This study takes the land resources in the Qinghai-Tibet Plateau as the evaluation object, and clarifies the current situation in the region suitable for agriculture, forestry, animal husbandry production and the quantity, quality and distribution of the reserve land resources. Through field investigations, collect relevant data from the study area, and combine relevant literature and expert experience to determine the evaluation factors (altitude, slope, annual precipitation, accumulated temperature, sunshine hours, soil effective depth, texture, erosion, vegetation type, NDVI). The grading and standardization are carried out, and the weights of each evaluation factor are determined by principal component analysis. The weighted index and model are used to determine the total score of the evaluation unit. Finally, the ArcGis natural discontinuity classification method is used to obtain the Qingshang Plateau. And the grades of farmland, forestry and grassland suitability drawings of the Qinghai-Tibet Plateau with a resolution of 90m were given. Finally, the results are verified and analyzed.
YAO Minglei
The data includes the county-level data of characteristic agriculture distribution in the Qinghai Tibet Plateau, which lays the foundation for the spatial distribution and development of characteristic agriculture in the Qinghai Tibet Plateau. The data comes from the planning documents of each province in the Tibetan Plateau region, such as the development plan of the characteristic agricultural products base of the Tibetan Plateau (2015-2020). The data is the distribution of characteristic agriculture at the county level, including four kinds of agricultural products: highland barley, yak, sheep and wolfberry. The spatialization of main agricultural products of characteristic agriculture at the county level is realized. The time range is set to 2015-2020, referring to the planning and construction time of characteristic agriculture in each province in the data source. The data can be applied to the research on the spatial distribution of characteristic agriculture and the development of characteristic agriculture in the future.
SHI Wenjiao
The content of this data set is the measurements of body weight and body size (body height, body length, chest circumference, tube circumference) of 11 representative yak populations in Qinghai pastoral area at 2018. All the metadata comes from the work of body weight monitoring of yaks in Qinghai pastoral area at 2018, by the Northwest Institute of Plateau Biology, Chinese Academy of Sciences and Qinghai Academy of Animal Husbandry and Veterinary Sciences. The data set is named by “Monitoring Data Set of Body Weights of Traditional Grazing Yaks in Qinghai Pastoral Area (2018)”, consisting of 11 worksheets. The names and contents of worksheets are as follows: 1. Haiyan-Halejing (167 yaks in halejing Mongolian Town, Haiyan County, Haibei Tibetan Autonomous Prefecture); 2. Qilian-Mole (69 yaks in Mole Town, Qilian County, Haibei Tibetan Autonomous Prefecture); 3. Qilian-Yeniugou (42 yaks in Yeniugou Town, Qilian County, Haibei Tibetan Autonomous Prefecture); 4. Qilian-Yanglong (104 yaks in Yanglong Town, Qilian County, Haibei Tibetan Autonomous Prefecture); 5. Qilian-Ebao (28 yaks in Ebao Town, Qilian County, Haibei Tibetan Autonomous Prefecture); 6. Tianjun-Xinyuan (38 yaks in Xinyuan Town, Tianjun County, Haixi Mongolian and Tibetan Autonomous Prefecture); 7. Tianjun-Longmen (100 yaks in Longmen Town, Tianjun County, Haixi Mongolian and Tibetan Autonomous Prefecture); 8. Gande-Ganlong (36 yaks in Ganglong Town, Gande County, Guoluo Tibetan Autonomous Prefecture); 9. Guinan-Taxiu (70 yaks in Taxiu Town, Guinan County, Hainan Tibetan Autonomous Prefecture); 10. Henan-Kesheng (73 yaks in Kesheng Town, Henan Mongolian Autonomous Country, Huangnan Tibetan Autonomous Prefecture); 11. Ledu-Dala (50 yaks in Dala Town, Ledu District, Haidong City). This data set comprehensively evaluates the growth performance of yaks grazing in alpine meadow under the current ecological environment through the measurement of weight and body size data in the representative areas of Qinghai pastoral area. The data set can be compared with the growth characteristics of representative populations of Qinghai yaks measured in 1981 and 2008 recorded in 1983 and 2013, and the degradation index of growth performance of yaks grazing in Qinghai pastoral area can be obtained, which is helpful to assess the impact of ecological environment changes on the growth and production performance of grazing livestock.
JIA Gongxue, YANG Qien, Tianwei XU
The data set was obtained from UAV aerial photography during the field investigation of the Qinghai Tibet Plateau in August 2020. The data size is 10.1 GB, including more than 11600 aerial photos. The shooting sites mainly include Lhasa, Shannan, Shigatse and other areas along the road, residential areas and surrounding areas. The aerial photos mainly reflect the local land use / cover type, facility agriculture distribution, grassland coverage and other information. The aerial photos have longitude, latitude and altitude information, which can provide better verification information for land use / cover remote sensing interpretation, and can also be used for vegetation coverage estimation, and provide better reference information for land use research in the study area.
LV Changhe, LIU Yaqun
The Tibetan Plateau in China covers six provinces including Tibet, Qinghai, Xinjiang, Yunnan, Gansu and Sichuan, including Tibet and Qinghai, as well as parts of Xinjiang, Yunnan, Gansu and Sichuan. The research on water and soil resources matching aims to reveal the equilibrium and abundance of water resources and land resources in a certain regional scale. The higher the level of consistency between regional water resources and the allocation of cultivated land resources, the higher the matching degree, and the superior the basic conditions of agricultural production. The general agricultural water resource measurement method based on the unit area of cultivated land is used to reflect the quantitative relationship between the water supply of agricultural production in the study area and the spatial suitability of cultivated land resources. The Excel file of the data set contains the generalized agricultural soil and water resource matching coefficient data of the Tibetan Plateau municipal administrative region in China from 2008 to 2015, the vector data is the boundary data of the Tibetan Plateau municipal administrative region in China in 2004, and the raster data pixel value is the generalized agricultural soil and water resource matching coefficient of the year in the region.
DONG Qianjin, DONG Lingxiao
The data set of agricultural activity intensity of the Qinghai Tibet Plateau is based on the County-Level Agricultural statistical data, including the annual cultivated land area, agricultural, forestry, animal husbandry and fishery labor force, total power of agricultural machinery, rural power consumption, effective irrigation area, pesticide use, fertilizer use, total output of grain crops, and total output value of agricultural, forestry, animal husbandry and fishery. The agricultural input index and output index are taken as the first level indicators, and the unit cultivated land area is constructed The intensity index system of agricultural activity is composed of 10 indexes, such as total power of agricultural machinery, fertilizer application amount per unit cultivated area and labor productivity. Entropy method was used to determine the weight of each index, and the input-output index of county-level agriculture in the Qinghai Tibet Plateau was obtained by AHP. The basic data comes from the statistical data released by the National Bureau of statistics, and the original data has been approved and corrected, with high reliability. The input-output index, input-output index and input-output index of county level in the Qinghai Tibet Plateau from 1980s to 2015 included in the data set reflect the spatiotemporal variation characteristics of the intensity of agricultural production activities in the Qinghai Tibet Plateau to a certain extent, and provide data support and theoretical reference for the local agricultural development.
LIU Yujie
In order to study the relationship between the spread of cyanine and human activities, we will resequence the cyanine varieties from the Qinghai Tibet Plateau and its surrounding areas, as well as Pakistan, India, Nepal, Germany, Japan and other places. At the same time, we will cluster the gene families, and make statistics of unique, shared genes and gene families. In addition, we will also carry out the analysis of gene family expansion and contraction, and system development Tree construction, genome-wide replication events and other analysis. The aim is to analyze the molecular basis of adaptation of traditional species of cyanine to the plateau under the dual pressures of human activities and regional climate. Therefore, this study is helpful to reveal the adaptive mechanism of cyanine to adapt to the plateau ecological environment and the influence of artificial domestication and human selection on its genetic differentiation in the process of evolution.
DUAN Yuanwen
In order to explore how and when turnip was successfully domesticated the Qinghai-Tibet Plateau and what is the relationship between turnip domestication and early human settlement on the Qinghai-Tibetan Plateau and human migration along the ancient Silk Road, the whole genome De Novo sequencing of a self-bred F1 variety on Qinghai-Xizang Plateau was conducted, with the assembled genome size of 409.69 Mb,Contig N50 was 1.21 Mb in June 2018 using Pacbio sequencing. Those data will provide a genetic basis for elucidating the relationship between plant disperse and human activities. As we know, traditional turnip landrace is influenced by human domestication and nature selection. Hopefully, the study will help to understand the impacts of human selection on turnip genetic differentiation, and the adaptation mechanism of turnip in the Qinghai-Tibetan Plateau.
DUAN Yuanwen
By archaeological investigation and excavation in Tibetan Plateau and Hexi corridor, we discovered more than 40 Neolithic and Bronze Age sites, including Zongri, Sanjiaocheng, Huoshiliang, Ganggangwa, Yigediwonan, Shaguoliang, Guandi, Maolinshan, Dongjicuona, Nuomuhong, Qugong, Liding and so on. In this dataset, there are some basic informations about these sites, such as location, longitude, latitude, altitude, material culture and so on. On this Basis, we identified animal remains, plant fossil, selected some samples for radiocarbon dating, optically stimulated luminescence dating, stable carbon, nitrogen isotopes, polle, fungal sporen and environmental proxies. This dataset provide important basic data for understanding when and how prehistoric human lived in the Tibetan Plateau during the Neolithic and Bronze Age.
YANG Xiaoyan, Lü Hongliang, LIU Xiangjun, HOU Guangliang
The dataset recorded the output statistics of major crops in Qinghai province from 2007 to 2020, including wheat, highland barley, potato (fold grain), oil crops, wolfberry, vegetables and edible fungi, covering the period from 2007 to 2020. The dataset contains 13 data tables, which are: Crop yield (2007), crop yield (2008), crop yield (2009), crop yield (2010), crop yield (2011), crop yield (2012), crop yield (2013), crop yield (2014), crop yield (2015), Crop output (2016), crop output (2017), crop output (2018) Output of major crop products in Qinghai Province (2015-2020).xls. The data table structure is similar. For example, the crop yield (2007) data table has 4 fields: Field 1: Indicator name Field 2: Year 2006 Field 3: Year 2007 Field 4: increase or decrease
AGRICULTURAL AND RURAL Department of Qinghai Province
The data set is mainly included the population, arable land and animal husbandry data of Qinghai Province and Tibet Autonomous Region in the past 100 years. The data mainly comes from historical documents and modern statistics. The data quality is more reliable. It mainly provides arguments for the majority of researchers in the development of agriculture and animal husbandry on the Qinghai-Tibet Plateau.
LIU Fenggui
As the roof of the world, the water tower of Asia and the third pole of the world, the Qinghai Tibet Plateau is an important ecological security barrier for China and even Asia. With the rapid development of social economy, human activities have increased significantly, and the impact on the ecological environment is growing. In this paper, eight factors including cultivated land, construction land, National Road, provincial road, railway, expressway, GDP and population density were selected as the threat factors, and the attributes of the threat factors were determined based on the expert scoring method to evaluate the habitat quality of the Qinghai Tibet Plateau, so as to obtain six data sets of the habitat quality of the agricultural and pastoral areas of the Qinghai Tibet Plateau in 1990, 1995, 2000, 2005, 2010 and 2015. The production of habitat quality data sets will help to explore the habitat quality of the Qinghai Tibet Plateau and provide effective support for the government to formulate sustainable development policies of the Qinghai Tibet Plateau.
LIU Shiliang, LIU Yixuan, SUN Yongxiu, LI Mingqi
The data of farmland distribution on the Qinghai-Tibet Plateau were extracted on the basis of the land use dataset in China (2015). The dataset is mainly based on landsat 8 remote sensing images, which are generated by manual visual interpretation. The land use types mainly include the cultivated land, which is divided into two categories, including paddy land (1) and dry land (2). The spatial resolution of the data is 30m, and the time is 2015. The projection coordinate system is D_Krasovsky_1940_Albers. And the central meridian was 105°E and the two standard latitudes of the projection system were 25°N and 47°N, respectively. The data are stored in TIFF format, named “farmland distribution”, and the data volume is 4.39GB. The data were saved in compressed file format, named “30 m grid data of farmland distribution in agricultural and pastoral areas of the Qinghai-Tibet Plateau in 2015”. The data can be opened by ArcGIS, QGIS, ENVI, and ERDAS software, which can provide reference for farmland ecosystem management on the QTP.
LIU Shiliang, SUN Yongxiu, LI Mingqi
Through the bioinformatics analysis after Hi-C sequencing, most of the sequences in the preliminary assembled genome sketch can be located on the chromosome, and the sequence and direction of these sequences on the chromosome can be determined, which lays an important foundation for obtaining high-quality sequence map. Therefore, by using this technology, the research team can divide the sequence in the sketch of the genome sequence of Aralia racemosa into groups with the same chromosome number as the species, and determine the order and orientation of all sequences in each group. After that, we can combine the data of reference genome, EST sequence, related species and genetic map of Aralia racemosa The accuracy of grouping and the order and direction between sequences were evaluated.
DUAN Yuanwen
The data on the consumption and trade of agricultural products for the period 1992-2016 in the five Central Asian countries are derived from the Food and Agriculture Organization of the United Nations (FAO) food statistics database. The main elements include: crop types and yields, crop sown area, breed species and scale, animal product output, dietary structure, population, policy technology, total import and export amount and amount, etc. It can be used to support the development and utilization of agricultural water and soil resources in Central Asia, and the measurement and management of the "virtual water" and "virtual soil" resources contained in agricultural products. It provides the basic data support for the agricultural products trade complementation and agricultural cooperation decision making between China and the five Central Asian countries, and guarantees and promotes the construction of the Silk Road economic belt.
YANG Yonghui, HE Li
Based on the calculated ecological environmental risk of agriculture and animal husbandry in 1985, 1990, 1995, 2000, 2010 and 2015 on the Tibetan Plateau, the fuzzy weighted Markov chain model was used to predict the ecological environmental risk without the meteorological factors.The meteorological factors data extracted from future climate model (rcp4.5) was superimposed with ecological environmental risk of agriculture and animal husbandry without the meteorological factors. The resulting risk of agriculture and animal husbandry development in 2030, 2050 and 2070 can provide scientific basis for the future development planning of agricultural and animal husbandry on the Tibetan Plateau.
LU Hongwei
Based on the ecological environmental risk data of the development of agriculture and animal husbandry in 2030, 2050 and 2070 in the Qinghai Tibet Plateau, the risk values of agriculture and animal husbandry in the six typical years of 198519901995200002010 and 2015 are calculated, and the predicted value of ecological environmental risk in 203020502070 is calculated by using the fuzzy weighted Markov chain model. The grid map of meteorological factors extracted from ArcGIS and the future climate model (rcp4.5) was superimposed to obtain the data of agricultural and animal husbandry ecological environment risk in the Tibetan Plateau in 203020502070.
LU Hongwei
By archaeological investigation and excavation in Tibetan Plateau, we discovered 14 historic period sites, including Meinuo, Sariguo, Rongwaguo, Kaze, Jiha, Yarigei, Bami, Barongbadang, Qingtu, Labu ,Maisong Petroglyph, Gala, Yezere 1 and Yezere 4 . In this dataset, there are some basic informations about these sites, such as location, longitude, latitude, altitude, material culture and so on. On this Basis, we identified animal remains, plant macrofossil, selected some samples for radiocarbon dating and stable carbon and nitrogen isotopes. This dataset provide important basic data for understanding when and how prehistoric human lived in the Tibetan Plateau during the historic period.
DONG Guanghui , HOU Guangliang
The data set records one belt, one road, 65 countries, 1961-2009 years of agricultural machinery (tractor) quantity and other relevant data. Agricultural machinery refers to the number of wheeled and tracked tractors (excluding horticultural tractors) used in agriculture at the end of a specified calendar year or the first quarter of the following year. Data source: Food and Agriculture Organization, electronic files and web site. Agricultural machinery reduces labor intensity, reduces hard labor, alleviates labor shortage, improves productivity and timeliness of agricultural activities, improves effective utilization of resources, increases market access, and helps reduce climate related hazards. In the future, agricultural machinery will play a greater role in ensuring the environmental sustainability of agriculture. The data set contains two data tables: Agricultural Machinery (tractors per 100 square kilometers of arable land), agricultural machinery (number of tractors).
XU Xinliang
The matching and zoning of water and land resources in Central Asian countries under the background of climate change can provide support for the development of water and land resources and agricultural production in Central Asian countries, and is of great significance to the social stability of the core region of the Silk Road Economic Belt. Based on the collected meteorological, water resources, land use and remote sensing data, the present situation of water and land resources development and utilization in Central Asia is analyzed. Based on the evaluating the characteristics and shortages of agricultural soil and water resources, using the DPSIR model and the theory of supply and demand, we constructed the index structure framework (SDCSL) of the study area, and the principal component analysis and cluster analysis are used to divide the regional of water and land resources utilization. Finally, we discussed the measures and ways to achieve the effective matching of agricultural water and land resources in different regions, so as to provide scientific reference and theoretical basis for the effective matching and sustainable development of regional agricultural water and land resources.
YAO Haijiao, LI Li, Food and Agriculture Organization of the United Nations（FAO）
The data include the data of cattle stock at the end of the year of Tibetan Plateau . The spatial area is divided by counties on the Tibetan Plateau. The time resolution is 5 years, and the time coverage is 2000, 2005, 2010.This data is obtained through statistics and collection of relevant literature, historical database records and other materials, and other data are acquired through purchase.The data can be used to analyze the agricultural production and meat price changes of each county on the Tibetan Plateau. In addition, the development differences of each county on the Tibetan Plateau can also be analyzed by comparing the data of the counties.
YANG Fei
The alpine and anoxic environment of the Qinghai Tibet Plateau is a major challenge for human survival and life. When human beings boarded the Qinghai Tibet Plateau and adapted to the extreme environment of the plateau has always been a hot issue in the academic circles. At present, in the study of prehistoric culture of the Qinghai Tibet Plateau, except the northeast, most areas of the Qinghai Tibet Plateau have not established archaeological cultural sequences. Yajiang river basin is one of the areas with dense distribution of human activity relics, but there are few archaeological excavations and studies, and the activity history of the ancients in this area is not clear. Based on the systematic dating of cultural archaeological sites in Linzhi Area, Southeast Tibet, 33 carbon fourteenth age data were obtained.
YANG Xiaoyan, WANG Yanren
Research on the spatial distribution and dynamic change of soil and water heat in Central Asian countries under the background of climate change can provide support for the development of water and soil resources and agricultural production in Central Asian countries, which is of great significance for the social stability of the core region of the "Silk Road Economic Belt". Based on meteorological, water resources, land use and remote sensing data, this paper analyzes the current situation of water and soil resources development and utilization in Central Asia, and introduces the water and heat product index as the water and heat factor, and uses linear trend analysis and partial correlation analysis to study the spatial and temporal variation characteristics of water and soil heat resources in Central Asia in 1995, 2005 and 2015 Equivalent coefficient is used to evaluate the matching characteristics and shortage degree of agricultural water and soil resources. The data set adopts Albers projection, including the spatial distribution of annual precipitation resources, heat resources and cultivated land resources in Central Asia. This data set is intended to provide basic data for the follow-up analysis of agricultural resources, natural regionalization and vulnerability of water, soil and heat resources in Central Asia.
ZHOU Hongfei, YAO Haijiao, LI Li, Food and Agriculture Organization of the United Nations（FAO）
The data set records the cereal yield of of 1961-2016 countries along 65 countries along the belt and road. Data sources: Food and Agriculture Organization, electronic files and web site.The data are collected by the Food and Agriculture Organization (FAO) of the United Nations through annual questionnaires and are supplemented with information from official secondary data sources. The secondary sources cover official country data from websites of national ministries, national publications and related country data reported by various international organizations.Data on agricultural land in different climates may not be comparable. For example, permanent pastures are quite different in nature and intensity in African countries and dry Middle Eastern countries. The dataset contains 2 tables：Cereal production (metric tons),Cereal yield (kg per hectare).
XU Xinliang
In this study, the cultivated land, forest land and grassland of the Qinghai Tibet Plateau in 2015 were taken as the evaluation objects to analyze the terrain, climate, soil and vegetation factors (terrain: altitude, slope; climate: sunshine hours, ≥ 0 ℃ accumulated temperature, annual average precipitation; soil: soil texture, soil erosion intensity, soil layer thickness; vegetation: vegetation type, NDVI) that have significant impact on land sensitivity and establish agriculture Land sensitivity evaluation index system. Using AHP method to determine the weight of evaluation factors, according to the ArcGIS Jerks classification method to get the sensitivity level of cultivated land, forest land and grassland, output 250m resolution of the Qinghai Tibet Plateau agricultural land sensitivity map, and verify the results.
YAO Minglei
The data of Land Resources Productivity for “B&R” includes: 1. Areas of cultivated land resources in regions and countries along the “B&R”; 2. Data on grain planting area and total grain output in regions and countries along the “B&R”; 3. Major crops (rice, wheat, corn) in regions and countries along the route Planting area and production data; 4. Areas of grassland resources in the region and along the country; 5. Number of livestock (bovine, sheep) in the region and along the country. Source: Cultivated land and population data from the World Bank database; food, crop, grassland, and livestock data are from FAO. Data application: According to the data provided, the basic characteristics analysis of land resources and the analysis of land resource output can be carried out in the Belt and Road region and the countries along the route, so that the land resource productivity evaluation analysis can be carried out.
YANG Yanzhao
The data set recorded the sown area and cropping structure of crops in Qinghai province from 1952 to 2020, divided by major years and regions such as Xining, Haidong, Haibei, Huangnan, Hainan, Guoluo, Yushu and Haixi. The data are collected from qinghai Statistical Yearbook released by Qinghai Provincial Bureau of Statistics. The dataset contains 39 data tables, which are: Main crops sown area and planting structure 2000-2003. XLS Main crop planting structure 2000-2001. XLS Main crop planting structure 2001-2002. XLS Total sown area of crops in main years 1978-2004. XLS Total sown area of crops in main years 1978-2008. XLS Total sown area of crops in main years 1978-2009. XLS Total sown area of crops in main years 1978-2010. XLS Total sown area of crops in main years 1978-2011. XLS Total sown area of crops in main years 1978-2013. XLS Total sown area of crops in main years 1978-2014. XLS Total sown area of crops in main years 1978-2015. XLS Total sown area of crops in main years 1978-2016. XLS Total sown area of crops in main years 1978-2017. XLS Total sown area of crops in main years 1978-2006. XLS Total sown area of crops in main years 1978-2007. XLS Total area sown to crops in main years 1995-2005. XLS Total sown area of crops in main years 1978-2012. XLS Total sown area of crops in main years 1978-2020.xls Main year crop sown area 1978-2018.xLS Crop sown area and multiple cropping index of main years 1952-1998. XLS Crop sown area and multiple cropping index of main years 1952-1999. XLS Crop sown area and multiple cropping index of main years 1952-2000. XLS Planting area and planting structure of crops 2000-2007. XLS Planting area and planting structure of crops 2000-2005. XLS Planting area and planting structure of crops 2000-2006. XLS Crop sown area and planting structure 2004. XLS Planting area and planting structure of crops 2005-2009.xLS Planting area and planting structure of crops 2006-2010. XLS Sown area and planting structure of crops 2007-2011. XLS Crop sown area and planting structure 2008.xls Crop sown area and planting structure 2009-2012. XLS Crop sown area and planting structure 2009-2013. XLS The sown area and planting structure of crops 2010-2014. XLS Sown area and planting structure of crops 2011-2015. XLS Crop sown area and planting structure 2012-2016. XLS Crop sown area and planting structure 2013-2017.xLS Crop sown area and planting structure 2013-2018.xLS Sown area and planting structure of crops 2015-2020.xLS The data table structure is similar. For example, there are 6 fields in the data table from 2000 to 2007: Field 1: Total sown area of crops Field 2: Food crops Field 3: Cash crop Field 4: Vegetables Field 5: melons and fruits Field 6: Other
Qinghai Provincial Bureau of Statistics
This data set includes the social, economic, resource and other relevant index data of Gansu, Qinghai, Sichuan, Tibet, Xinjiang and Yunnan in the Qinghai Tibet Plateau from 2000 to 2015. The data are derived from Gansu statistical yearbook, Qinghai statistical yearbook, Sichuan statistical yearbook, Xizang statistical yearbook, Xinjiang statistical yearbook, Yunnan statistical Yearbook China county (city) socio economic statistical yearbook And China economic network, guotai'an, etc. The statistical scale is county-level unit scale, including 26 county-level units such as Yumen City, Aksai Kazak Autonomous Region and Subei Mongolian Autonomous County in Gansu Province, 41 county-level units such as Delingha City, Ulan county and Tianjun County in Qinghai Province, 46 counties such as Shiqu County, Ruoergai County and ABA County in Sichuan Province, and 78 counties such as Ritu County, Gaize county and bango County in Tibet, 14 counties including Wuqia County, aktao county and Shache County in Xinjiang Province, and 9 counties including Deqin County, Zhongdian county and Fugong County in Yunnan Province; Variables include County GDP, added value of primary industry, added value of secondary industry, added value of tertiary industry, total industrial output value of Industrial Enterprises above Designated Size, total retail sales of social consumer goods, balance of residents' savings deposits, grain output, total sown area of crops, number of students in ordinary middle schools and land area. The data set can be used to evaluate the social, economic and resource status of the Qinghai Tibet Plateau.
CHEN Yizhong
The basic principle of ancient recipe analysis based on carbon and nitrogen stable isotope analysis method is you are what you eat, that is, the chemical composition of animal tissues and organs is closely related to their diet. Through the detection of isotope ratio of relevant elements, the food structure of ancient people and animals can be directly revealed Then it discusses the research means of people's livelihood and livestock domestication. The collagen of human and animal bones from shilinggang site in Nujiang, Yunnan Province in the southwest of Qinghai Tibet Plateau was analyzed by carbon and nitrogen stable isotopes.
DONG Guanghui , REN Lele
This dataset was captured during the field investigation of the Qinghai-Tibet Plateau in June 2021 using uav aerial photography. The data volume is 3.4 GB and includes more than 330 aerial photographs. The shooting locations mainly include roads, residential areas and their surrounding areas in Lhasa Nyingchi of Tibet, Dali and Nujiang of Yunnan province, Ganzi, Aba and Liangshan of Sichuan Province. These aerial photographs mainly reflect local land use/cover type, the distribution of facility agriculture land, vegetation coverage. Aerial photographs have spatial location information such as longitude, latitude and altitude, which can not only provide basic verification information for land use classification, but also provide reference for remote sensing image inversion of large-scale regional vegetation coverage by calculating vegetation coverage.
LV Changhe, ZHANG Zemin
The data set records the basic situation of agricultural and pastoral areas in Qinghai Province, including the number of townships, villagers' committees, community infrastructure, etc. the statistical data covers the period from 2014 to 2018. The data are divided into 8 states, cities and 43 counties and districts according to Xining City, Haidong region, Haibei Prefecture, Huangnan Prefecture, Hainan prefecture, Guoluo Prefecture, Yushu prefecture and Haixi Prefecture. The data set contains 10 data tables, which are: basic information of agricultural and pastoral areas (Table 1) (2014), basic information of agricultural and pastoral areas (Table 2) (2014), basic information of agricultural and pastoral areas (Table 1) (2015), basic information of agricultural and pastoral areas (table 2) (2015), basic information of agricultural and pastoral areas (Table 1) (2016), basic information of agricultural and pastoral areas (Table 2) (2016), Basic information of agricultural and pastoral areas (Table 1) (2017), basic information of agricultural and pastoral areas (Table 2) (2017), basic information of agricultural and pastoral areas (Table 1) (2018), basic information of agricultural and pastoral areas (Table 2) (2018). The data table structure is similar. For example, the basic information of agricultural and pastoral areas (Table I) (2014) data table has three fields: Field 1: number of villages and towns Field 2: Village Committee (PCs.) Field 3: rural community infrastructure (PCs.)
AGRICULTURAL AND RURAL Department of Qinghai Province
The ecological resource consumption data set of Tibet includes the ecological resource consumption data of 2000-2019 at the provincial, city and county levels. According to the actual situation of Tibet, ecological resource consumption mainly refers to the amount of ecological resources consumed in agricultural and animal husbandry production activities. The calculation of ecological resource consumption is based on grain production data, livestock stock data and livestock product production data, combined with the evaluation method of human appropriation the net primary productivity (HANPP), convert biomass data into carbon content data, and then calculate the ecological resource consumption. Ecological resource consumption data is the basic data for the study of ecological pressure and ecological carrying capacity, which can directly reveal the pressure of human agricultural and animal husbandry production activities on the ecosystem.
YAN Huiming
The data set recorded the statistical data of crop sown area in Qinghai Province, covering the period from 1978 to 2020. Data is broken down by major years. The dataset contains 13 data tables, which are: Sown area of crops (2006), sown area of crops (2007), sown area of crops (2008), sown area of crops (2009), sown area of crops (2010), sown area of crops (2011), sown area of crops (2012), sown area of crops (2012), sown area of crops (2012), The sown area of crops (2013), the sown area of crops (2014), the sown area of crops (2015), the sown area of crops (2016), the sown area of crops (2017), the sown area of crops (2018), the sown area of crops (1978-2020). The data table structure is similar. For example, the sown area of crops (1978-2020) data table has 5 fields: Field 1: Year Field 2: Food crops Field 3: Wheat Field 4: miscellaneous grains Field 5: Roots
AGRICULTURAL AND RURAL Department of Qinghai Province
The data set records the statistical data of grassland type area and livestock carrying capacity in Haidong area of Qinghai Province in 1988 and 2012. The data are classified and counted according to the grassland group code, such as: I represents Alpine dry grassland, II represents mountain dry grassland, III represents Alpine desert, B represents medium grass group, J represents shrub group, etc, For specific grassland group type codes and their corresponding meanings, see "description of grassland group type codes in Qinghai Province. PDF" in the data set. The data are compiled from the grassland station of Qinghai Province and the grassland resources statistics of Qinghai Province issued in 1988 and 2012. The data set contains three data tables, which are: statistical data of grassland area and livestock carrying capacity of various types in Haidong area (1988), statistical data of grassland area and livestock carrying capacity in Haidong area (2012) and description of grassland group code in Qinghai Province. The data table structure is similar. For example, there are 8 fields in the statistical data (2012) of grassland type, area and livestock carrying capacity in Haidong area: Field 1: type code Field 2: grassland type name Field 3: grassland area Field 4: available area of grassland Field 5: average unit yield of fresh grass Field 6: average unit yield of edible fresh grass Field 7: stocking capacity Field 8: grassland type, etc
AGRICULTURAL AND RURAL Department of Qinghai Province
1) Data content: the data are the ancient DNA data generated by studying the cultural layer of Klu lding site in Nyingchi region, Tibetan Plateau, including the hiseqx metagenomics data of 10 ancient DNA samples from 4 layers. It can be used to preliminarily analyze the changes of species composition recorded by ancient DNA in the sediments, and reveal the process of local agricultural development. 2) Data source and processing method: the research group has its ownership. the data were obtained by using pair-end library building and Illumina hiseqx sequencing platform. 3) Data quality: 20.3 MB, Q30 > 85%. 4) Application: The data will be used to explore the potential of the ancient DNA from archaeological sediments in revealing the development of ancient agriculture on the Tibetan Plateau.
YANG Xiaoyan
The population, grain, grain sown area and year-end data sets are extracted from the provincial and prefecture level statistical yearbooks of Qinghai, Tibet, Xinjiang, Gansu, Sichuan and Yunnan for many consecutive years. The missing data are interpolated as follows: 1. To ensure the accuracy of county data, Some counties and cities have been merged in this data (there may be errors in dividing and imputing the data for 20 years according to the proportion, but there will certainly be no problem in the merger, and the county area is small, so it is merged). 2. Xiahe County and cooperative city are merged into Xiahe County (cooperative city was separated from Xiahe County in 1998). 3. Gucheng district and Yulong County are merged into Gucheng district (Lijiang County was divided into Gucheng district and Yulong County in 2003). 4. The inner city district, East City District, West City District The four districts in Chengbei district have been merged into the district directly under the central government of Xining City (because the population of the four districts is given separately or the sum is given, and the total area of the four districts is only 487 square kilometers, they are merged). 5. For some missing data, curve fitting has been carried out in combination with similar years, and R2 is between 0.85-0.99. 6. In order to ensure the accuracy of the data, change maps have been prepared County by county
ZHANG Lu
The data set records the basic situation data of Township animal husbandry and veterinary extension institutions in Qinghai Province, and the statistical data covers the period from 2012 to 2017. The data are divided according to the number of stations, total number of employees, Technical Title Status, operation status, annual total income, annual total expenditure and other items. The data set contains five data tables, which are: basic information of Township animal husbandry and veterinary extension institutions (2012), basic information of Township animal husbandry and veterinary extension institutions (2014), basic information of Township animal husbandry and veterinary extension institutions (2015), basic information of Township animal husbandry and veterinary extension institutions (2016) and basic information of Township animal husbandry and veterinary extension institutions (2017). The data table structure is similar. For example, the data sheet of basic information of Township animal husbandry and veterinary extension institutions (2012) has three fields: Field 1: indicator name Field 2: Calculation Field 3: quantity
AGRICULTURAL AND RURAL Department of Qinghai Province
The data set records the statistical data of grain and oil crop sowing area in Qinghai Province, covering the period from 2015 to 2018. The data are divided by Xining City, Haidong City, Huangnan Prefecture, Hainan prefecture and other projects. The data set contains four data tables, which are: Statistics of grain and oil crop area of the whole province (2015), statistics of grain and oil crop area of the whole province (2016), statistics of grain and oil crop area of the whole province (2017) and statistics of grain and oil crop area of the whole province (2018). The data table structure is similar. For example, the statistical data sheet of grain and oil crop area in the province (2015) has three fields: Field 1: food crops Field 2: oil crops Field 3: other crops
AGRICULTURAL AND RURAL Department of Qinghai Province
The data set of economic, population, and urbanization growth and change in Qilian mountain area includes the social and economic development indicators of 1949-2020 long-term time series of 5 prefecture-level cities and 14 districts and counties in the Qilian mountain basin, such as the added value of the tertiary industry, population scale, etc. They are the subsets of economic, population, and urbanization growth changes of prefecture-level cities in Qilian mountain and the subsets of county-level economic, population, and urbanization growth changes in Qilian mountain. The data comes from Gansu statistical yearbook, Wuwei statistical bulletin of national economic and social development, Zhangye statistical bulletin of national economic and social development, Jiuquan statistical bulletin of national economic and social development, Jinchang statistical bulletin of national economic and social development, Jiayuguan statistical bulletin of national economic and social development, and social development of Ejina Banner. Since the data source is the publicly released provincial and Municipal Statistical Yearbook, the data has not been cross verified, and the consistency and accuracy of the data need to be verified in the process of data analysis and application. The data set is a macro data set reflecting the growth and change of economy, population, and urbanization in Qilian mountain. It has complete coverage and long-time series. It can provide basic information for the social and economic development and change of Qilian mountain.
WU Feng
This data set records the statistical data of origin identification and product certification of pollution-free agricultural products in Qinghai Province, covering the period from 2009 to 2017. The data are divided by items such as Huzhu County Vegetable Technology Service Center, Qinghai mutual Feng Agricultural Technology Co., Ltd., Wulan County Agricultural Technology Extension Station of Haixi Prefecture, Dulan County Agricultural Technology Extension Station, Ledu County Vegetable Technology Extension Center, Datong County Vegetable workstation, etc. The data set contains 9 data tables, which are: list of origin identification and product certification of pollution-free agricultural products in Qinghai Province (2009), list of origin identification and product certification of pollution-free agricultural products in Qinghai Province (2010), list of origin identification and product certification of pollution-free agricultural products in Qinghai Province (2011), List of origin identification and product certification of pollution-free agricultural products in Qinghai Province (2012), list of origin identification and product certification of pollution-free agricultural products in Qinghai Province (2013), list of origin identification and product certification of pollution-free agricultural products in Qinghai Province (2014), list of origin identification and product certification of pollution-free agricultural products in Qinghai Province (2015), List of origin identification and product certification of pollution-free agricultural products in Qinghai Province (2016), and list of origin identification and product certification of pollution-free agricultural products in Qinghai Province (2017). The data table structure is similar. For example, there are 6 fields in the data sheet of origin identification and product certification of pollution-free agricultural products in Qinghai Province (2009): Field 1: production unit Field 2: origin address Field 3: product name Field 4: origin scale Field 5: annual production Field 6: Certificate of origin number (validity period)
AGRICULTURAL AND RURAL Department of Qinghai Province
The data set records the statistical data of grain and oil crop production in Qinghai Province, covering the period from 2013 to 2018. The data are divided by Xining City, Haidong City, Huangnan Prefecture, Haibei Prefecture, Hainan prefecture, Haixi Prefecture, Guoluo Prefecture, Yushu prefecture, prison bureau, Sanjiangyuan and other projects. The data set contains six data tables, which are: Provincial Grain and oil crop production statistics (2013), provincial grain and oil crop production statistics (2014), provincial grain and oil crop production statistics (2015), provincial grain and oil crop production statistics (2016), provincial grain and oil crop production statistics (2017) and provincial grain and oil crop production statistics (2018). The data table structure is similar. For example, there are 8 fields in the statistical table of grain and oil crop production of the whole province (2013): Field 1: Wheat Field 2: highland barley Field 3: broad bean Field 4: Peas Field 5: Potato Field 6: Corn Field 7: Rapeseed Field 8: Flax
AGRICULTURAL AND RURAL Department of Qinghai Province
The data set records the statistical data of grassland type area and livestock carrying capacity in Golmud City, Qinghai Province in 1988 and 2012. The data are classified and counted according to the grassland group code, such as: I represents Alpine dry grassland, II represents mountain dry grassland, III represents Alpine desert, B represents medium grass group, J represents shrub group, etc, For specific grassland group type codes and their corresponding meanings, see "description of grassland group type codes in Qinghai Province. PDF" in the data set. The data are compiled from the grassland station of Qinghai Province and the grassland resources statistics of Qinghai Province issued in 1988 and 2012. The data set contains three data tables, which are: statistical data of grassland type area and livestock carrying capacity in Golmud City (1988), statistical data of grassland type area and livestock carrying capacity in Golmud City (2012) and code description of grassland type in Qinghai Province. The data table structure is similar. For example, there are 8 fields in the statistical data (2012) of grassland type, area and livestock carrying capacity in Golmud City: Field 1: type code Field 2: grassland type name Field 3: grassland area Field 4: available area of grassland Field 5: average unit yield of fresh grass Field 6: average unit yield of edible fresh grass Field 7: stocking capacity Field 8: grassland type grade
AGRICULTURAL AND RURAL Department of Qinghai Province
This data set records the statistical data of agricultural and animal husbandry scientific and technological talent resources in Qinghai Province, covering the period from 2011 to 2016. The data are divided by animal husbandry and veterinary, planting, fishery, agricultural machinery, land reclamation and other projects. The data set contains six data tables, which are: Statistics of scientific and technological human resources in agriculture and animal husbandry (applicable to extension institutions) (2011), statistics of scientific and technological human resources in agriculture and animal husbandry (applicable to extension institutions) (2012), statistics of scientific and technological human resources in agriculture and animal husbandry (applicable to extension institutions) (2013), statistics of scientific and technological human resources in agriculture and animal husbandry (applicable to extension institutions) (2014), Statistics of agricultural and animal husbandry scientific and technological human resources (applicable to extension institutions) (2015), statistics of agricultural and animal husbandry scientific and technological human resources (applicable to extension institutions) (2016). The data table structure is similar. For example, the statistical table of agricultural and animal husbandry scientific and technological talent resources (applicable to extension institutions) (2011) has five fields: Field 1: number of employees at the end of the year Field 2: number of scientific and technological talents Field 3: Qualification Field 4: Education Field 5: Gender
AGRICULTURAL AND RURAL Department of Qinghai Province
The data set records the agricultural production conditions in agricultural and pastoral areas of Qinghai Province, including agricultural mechanization, farmland water conservancy, mechanization project level, natural disasters, etc. The statistical data covers the period from 2014 to 2018. The data are divided into 8 states, cities and 43 counties and districts according to Xining City, Haidong region, Haibei Prefecture, Huangnan Prefecture, Hainan prefecture, Guoluo Prefecture, Yushu prefecture and Haixi Prefecture. The data set contains five data tables: agricultural production conditions in agricultural and pastoral areas (2014), agricultural production conditions in agricultural and pastoral areas (2015), agricultural production conditions in agricultural and pastoral areas (2016), agricultural production conditions in agricultural and pastoral areas (2017) and agricultural production conditions in agricultural and pastoral areas (2018). The data table has the same structure. For example, the data table of agricultural production conditions in agricultural and pastoral areas (2014) has 6 fields: Field 1: rainwater collection cellar Field 2: water saving irrigation machinery Field 3: agricultural water pumps Field 4: Combine Field 5: self propelled motorized windrower Field 6: motorized thresher
AGRICULTURAL AND RURAL Department of Qinghai Province
The data set records the statistical data of the total yield and variety composition of grain and oil crops in Qinghai Province in the main years, 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 consists of three data tables, namely, the total yield and variety composition of grain and oil crops in Main Years 1952-1998.xls, the total yield and variety composition of grain and oil crops in Main Years 1952-1999.xls, and the total yield and variety composition of grain and oil crops in Main Years 1952-2000.xls, with the same data table structure. For example, the data table in 2000 has four fields: Field 1: year Field 2: total grain production Field 3: species composition (%) Field 4: total oil production
Qinghai Provincial Bureau of Statistics
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