Spatial distribution dataset of biomass resources and energy technology potential in China (2015-2100)

This data integrates a variety of current natural geographic map data, and combines land suitability evaluation, crop growth model, scenario analysis and other methods to generate China's biomass resources and energy technology potential on a 1km grid scale from 2015 to 2100, with a temporal resolution of 5 years and a spatial resolution of 1km. The data set includes 3 categories and 11 types of biomass resources (the residues include dry land agricultural residues, paddy field agricultural residues, forest residues, shrub residues, orchard residues and grassland residues, the wastes include livestock manure, MSW and COD, and the energy crops include sweet sorghum and switchgrass), fully covering the types of biomass that can be used as resources. The data format is raster data (. tiff), which can be opened using ArcGIS, R/Python and other programming languages. Biomass is a dependent resource for negative carbon technology in China's carbon neutral technology system in the future. The biomass data developed in this research has three advantages: wide coverage (nationwide), fine spatial resolution (1km grid), and wide time span (2015-2100). It can provide detailed quantitative data for China to formulate low-carbon emission reduction strategies and deploy biomass energy technology strategies.

0 2022-09-20

Universal Thermal Climate Index (UTCI) dataset of urban areas in China (2012-2021)

Monthly average daytime as well as nighttime data of the Universal Thermal Climate Index (UTCI) for 354 cities in China. The time range of the data is from January 2012 to December 2021, with a temporal resolution of month-by-month. The spatial resolution is 1 km. The data is mainly based on the MYD07 atmosphere profile dataset and MYD11 land surface temperature dataset provided by MODIS, and incorporates the wind speed provided by ERA5 reanalysis data. The urban boundary is demarcated according to the 2018 data provided by Global Urban Boundary-GUB dataset. All the data are resampled to 1 km, in order to maintain the uniform spatial resolution. With the rapid urbanization and global warming, the data are useful for studying the spatiotemporal patterns of urban thermal comfortable and related analysis.

0 2022-08-24

A dataset of crop production in Tibet's One River and Two Rivers Region, Southeast Tibet, and Hengduan Mountains in East Sichuan and Tibet in 2020

This data comes from a random questionnaire survey conducted in the one-river-two-river region of Tibet, southeastern Tibet, and Hengduan mountainous area of eastern Sichuan and Tibet during July-August 2020. The data set mainly includes agricultural waste utilization data (straw utilization and livestock and poultry wastes). Utilization methods), straw utilization methods mainly include returning to the field, fuel, feed and compost, and livestock and poultry manure utilization methods mainly include fuel and fertilizer. The interviewees were mainly adults who were familiar with the family situation. In some villages, the output was calculated in small groups. The questionnaire design is based on the principles of scientificity, applicability, feasibility, typicality and specificity, and the "Household Questionnaire" is designed for the above areas. In order to ensure the reliability and validity of the questionnaire design content, the questionnaire was pre-investigated before the formal investigation, and there were problems in further modifying and improving the questionnaire. Before the official start of the questionnaire, the investigators were given the explanation of the content of the questionnaire and the training of investigation skills.

0 2022-08-24

Geo risk index along the " Belt and Road Initiative" (2017)

"One belt, one road" along the lines of risk rating, credit risk rating and Moodie's national sovereignty rating reflects the structure of sovereign risk in every country. The rating of Moodie's national sovereignty is from the highest Aaa to the lowest C level, and there are twenty-one levels. Data source: organized by the author. Data quality is good. The rating level is divided into two parts, including investment level and speculation level. AAA level is the highest, which is the sovereign rating of excellent level. It means the highest credit quality and the lowest credit risk. The interest payment has sufficient guarantee and the principal is safe. The factors that guarantee the repayment of principal and interest are predictable even if they change. The distribution position is stable. C is the lowest rating, indicating that it cannot be used for real investment.

0 2022-08-16

Agricultural management data set of farmland in one river and two rivers region, Southeast Tibet and Hengduan Mountain Area in East Sichuan and Tibet (2020)

This data set is based on the field survey data on farmland production, operation and management in Tibet's one river and two rivers region, Southeast Tibet, Sichuan Tibet East Hengduan Mountain Area in 2020. Sample selection: for the areas of one river and two rivers in Tibet, Southeast Tibet, and Hengduan Mountain Area in East Sichuan and Tibet, first, the typical sampling method is used to determine the sample counties, sample towns, and sample villages; Then, according to the basic situation of farmers, one sample Township and one sample village are selected from each county. Finally, one farmer is randomly selected from each sample village by using the random sampling method. The data set records the basic information of the investigated land, the basic information of the interviewed farmers, including education level, consumption level and other information, agricultural planting area, etc. The data set is the data obtained through field investigation and interview, which can be used to analyze the basic situation of agricultural planting on the Qinghai Tibet Plateau, and provide a theoretical basis for further improving the countermeasures and suggestions of government support policies.

0 2022-08-08

Qinghai-Tibet Plateau Agricultural Management Historical Dataset (1959-2019)

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.

0 2022-08-08

Information and Photos of Lichen Specimens on the Tibetan Plateau (2019-2020)

Through the scientific research work in 2019 and 2020, the second Tibetan Plateau Scientific Expedition and Research Task 5 Theme 3 Topic 4 Lichen Scientific Research Team (2019QZKK050304) has supplemented the collection of a large number of lichen collection gaps in the Tibetan Plateau region. 2019 scientific research conducted in-depth lichen biodiversity examination for the first time in the Ali region in northern Tibet, and in 2020, fieldwork and specimen collection will be conducted in the lichen collection gap areas of Hoh Xil and Sanjiangyuan. These expeditions have unveiled the mystery of lichen composition in the Tibetan Plateau region and filled the gaps in the domestic collection of this region. This dataset contains information on 10,283 lichen specimens collected from July 2019 to September 2020 in Tibet Autonomous Region, Qinghai Province, Sichuan Province, and Yunnan Province, including information on collection habitat, collection time, collector, latitude and longitude, altitude, and Latin scientific name. Contains 4,328 specimen photos, including lichen specimen No. 815 in 2019 with 2,425 photos and specimen No. 543 in 2020 with 1,903 photos. The physical specimens are stored in the Herbarium, Kunming Institute of Botany, CAS (KUN). Specimen collection information and field ecological photographs are synchronized between various databases, including the Biotracks database and the KUN herbarium database, to facilitate later research, collation and query by relevant personnel. The specimens are now sorted by time, region and genus name and stored separately in the KUN herbarium to facilitate subsequent studies, and the corresponding molecular materials are preserved or molecular sequences are obtained, laying a good material basis for subsequent taxonomic and systematics studies of the specimens. DNA extraction and systematic taxonomic studies of various groups are also being carried out.

0 2022-07-23

Microbial amplicon sequencing dataset for glacial ice and snow on the Tibetan Plateau (V1.0) (2016-2020)

The dataset contains microbial amplicon sequencing data from a total of 269 ice samples collected from 15 glaciers on the Tibetan Plateau from November 2016 to August 2020, including 24K Glacier (24K), Dongkemadi Glacier (DKMD), Dunde Glacier (DD), Jiemayangzong Glacier (JMYZ), Kuoqionggangri Glacier (KQGR), Laigu Glacier (LG), Palung 4 Glacier (PL4), Qiangtang 1 Glacier (QT), Qiangyong Glacier (QY), Quma Glacier (QM), Tanggula Glacier (TGL), Xiagangjiang Glacier (XGJ), Yala Glacier (YA), Zepugou Glacier (ZPG), ZhufengDongrongbu Glacier (ZF). The sampling areas ranged in latitude and longitude from 28.020°N to 38.100°N and 86.28°E to 95.651°E. The 16s rRNA gene was amplified by polymerase chain reaction (PCR) using 515F/907R (or 515F/806R) primers and sequenced with the Illumina Hiseq2500 sequencing platform to obtain raw data. The selected primer sequences were "515F_GTGYCAGCMGCCGCGGTAA; 907R_CCGTCAATTCMTTTRAGTTT" "515F_GTGCCAGCMGCCGCGG; 806R_ GGACTACHVGGGTWTCTAAT". The uploaded data include: sample number, sample description, sampling time, latitude and longitude coordinates, sample type, sequencing target, sequencing fragment, sequencing primer, sequencing platform, data format and other basic information. The sequencing data are stored in sequence file data format forward *.1.fq.gz and reverse *.2.fq.gz compressed files.

0 2022-07-22

A dataset of spatio-temporal change of physical and virtual water in Qilian Mountains (2012)

A dataset of spatio-temporal change of physical and virtual water in Qilian Mountains: Using the single-region input-output method, and the 2012 input-output table of Qilian Mountains, we developed a physical water-virtual water conversion model and explored the virtual water among different departments in Qilian Mountains in 2012. The law of water flow provides a theoretical basis for the optimal allocation of water resources in the natural-society complex system for the research on the optimal allocation of "mountains, waters, forests, fields, lakes, grass and sand" in the Qilian Mountains. It has been verified that this dataset has achieved the balance between the physical water consumption and the total virtual water consumption of various departments in the Qilian Mountains in 2012, indicating that the data is reliable. This data can provide a basis for the optimal allocation of water resources in the Qilian Mountains.

0 2022-07-12

30 m land cover classification product data set of Qilian Mountain Area in 2021 (V3.0)

This data set is a 30m land cover classification product in the Qilian Mountains in 2021. This product is based on the land cover classification product in 2021, based on the Landsat series data and strong geodetic data processing capability of Google Earth engine platform, and is produced by using the ideas and methods of change detection. The overall accuracy is better than 85%. This product is the continuation of land cover classification products from 1985 to 2020. Land cover classification products from 1985 to 2020 can also be downloaded from this website. Among them, the land use products from 1985 to 2015 are five years and one period, and the land use products from 2015 to 2021 are one year and one period.

0 2022-06-30