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
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
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 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
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
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 applying Supply-demand Balance Analysis, the water resource supply and demand of the whole river basin and each county or district were calculated and used to evaluate the vulnerability of the water resources system of the basin. The IPAT equation was used to set a future water resource demand scenario to establish the scenario by setting variables such as future population growth rate, economic growth rate, and unit GDP water consumption. By taking 2005 as the base year and using assorted forecasting data of population size and economic scale, the future water demand scenarios of various counties and cities from 2010 to 2050 were predicted. By applying the basic structure of the HBV conceptual hydrological model of the Swedish Hydrometeorological Institute, a model of the variation tendency of the basin under climate change was designed. The glacial melting scenario was used as the model input to construct the runoff scenario under climate change. According to the national regulations of the water resources allocation of the basin, a water distribution plan was set up to calculate the water supply comprehensively. Considering of the supply and demand situation, the water resource system vulnerability was evaluated by the water shortage rate. By calculating the (grain production) land pressure index of the major counties and cities in the basin, the balance of supply and demand of land resources under the climate change, glacial melt and population growth scenarios was analyzed, and the vulnerability of the agricultural system was evaluated. The Miami formula and HANPP model were used to calculate the human appropriation of net primary biomass and primary biomass in the major counties and cities for the future, and the vulnerability of ecosystems from the perspective of supply and demand balance was assessed.
YANG Linsheng, ZHONG Fanglei
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
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
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