In 2022, the total permanent resident population of Tibet autonomous region in China amounted to around **** million inhabitants. Tibet autonomous region is located in Western China.

Population: Registered: Tibet data was reported at 3.159 Person th in 2023. This records an increase from the previous number of 3.080 Person th for 2022. Population: Registered: Tibet data is updated yearly, averaging 2.592 Person th from Dec 1990 (Median) to 2023, with 28 observations. The data reached an all-time high of 2,691.210 Person th in 2010 and a record low of 2.191 Person th in 1996. Population: Registered: Tibet data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GA: Population: Sample Survey: By Region.

Population: Census: Tibet: Lhasa data was reported at 867.891 Person th in 12-01-2020. This records an increase from the previous number of 559.423 Person th for 12-01-2010. Population: Census: Tibet: Lhasa data is updated decadal, averaging 559.423 Person th from Dec 2000 (Median) to 12-01-2020, with 3 observations. The data reached an all-time high of 867.891 Person th in 12-01-2020 and a record low of 474.499 Person th in 12-01-2000. Population: Census: Tibet: Lhasa data remains active status in CEIC and is reported by Lhasa Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GE: Population: Prefecture Level City: By Census.

The Qinghai-Tibet Plateau has a fragile ecological environment, spanning a geographical range of 25°59′43.74″N–39°59′20.01″N and 73°29′56.26″E–104°25′20.95″E, with significant internal population regional differentiation. This study constructs a spatialized population dataset based on the Tibetan Empire period, the first era of unified governance on the plateau. First, population quantity data were obtained from historical literature and records. Second, using land use as a restrictive factor, the weights of elevation, slope, rivers, ancient settlements, post stations, and other factors were determined through the expert scoring method and Analytic Hierarchy Process to construct impact coefficients. Finally, a 1km×1km gridded population distribution model was developed using ArcGIS software to calculate population density. After verification, the error in population distribution for the Tuyuhun and Bailan regions is around 20%. There are two main reasons for the error: records of population during the Tibetan Empire period are characterized by uncertainties, with possible practices such as underreporting, undercounting, and overreporting; the number of documented ancient settlements remains incomplete, as only those ancient sites with explicit historical records have been spatially represented, thereby affecting the accuracy of population distribution. The spatialized population dataset of the Qinghai-Tibet Plateau during the Tibetan Empire period contains population density data (234 MB) and a population density distribution map (6.90 MB).

Population: Average Household Size: Tibet data was reported at 3.270 Person in 2021. This records an increase from the previous number of 3.192 Person for 2020. Population: Average Household Size: Tibet data is updated yearly, averaging 4.600 Person from Dec 1982 (Median) to 2021, with 29 observations. The data reached an all-time high of 6.790 Person in 1999 and a record low of 3.192 Person in 2020. Population: Average Household Size: Tibet data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GA: Population: No of Person per Household.

This point shapefile represents the district locations, with 2000 population census data, in the Autonomous region of Tibet (Xizang) for 2000. These data are represented at 1:1,000,000 scale. This layer is part of the China 2000 township population census dataset.

Tibetan, one of the largest indigenous populations living in the high-altitude region of the Tibetan Plateau (TP), has developed a suite of physiological adaptation strategies to cope with the extreme highland environment in TP. Here, we reported genome-wide SNP data from 48 Kham-speaking Nagqu Tibetans and analyzed it with published data from 1,067 individuals in 167 modern and ancient populations to characterize the detailed Tibetan subgroup history and population substructure. Overall, the patterns of allele sharing and haplotype sharing suggested (1) the relatively genetic homogeny between the studied Nagqu Tibetans and ancient Nepalese as well as present-day core Tibetans from Lhasa, Nagqu, and Shigatse; and (2) the close relationship between our studied Kham-speaking Nagqu Tibetans and Kham-speaking Chamdo Tibetans. The fitted qpAdm models showed that the studied Nagqu Tibetans could be fitted as having the main ancestry from late Neolithic upper Yellow River millet farmers and deeply diverged lineages from Southern East Asians (represented by Upper Paleolithic Guangxi_Longlin and Laos_Hoabinhian), and a non-neglectable western Steppe herder-related ancestry (∼3%). We further scanned the candidate genomic regions of natural selection for our newly generated Nagqu Tibetans and the published core Tibetans via FST, iHS, and XP-EHH tests. The genes overlapping with these regions were associated with essential human biological functions such as immune response, enzyme activity, signal transduction, skin development, and energy metabolism. Together, our results shed light on the admixture and evolutionary history of Nagqu Tibetan populations.

A. Allele frequencies of the 12 X-STR loci in in the Highlander Tibetans population residing in Nagqu city in the north of the Tibet Autonomous Region (TAR) in China (n = 549). B. Fisher Exact test for population differentiation per locous between allelic frequencies of male and female sample in the Highlander Tibetans population residing in Nagqu city in the north of the Tibet Autonomous Region (TAR) in China (n = 549). (XLSX)

This data set includes the urban distribution, urban population and built-up areas of the Qinghai Tibet Plateau from 2000 to 2015. The urban distribution data is the county-level vector boundary in 2015, and the urban population and built-up area data years are 2000, 2005, 2010 and 2015. Among them, the data of urban distribution and built-up areas are from the research team of Kuang Wenhui, Professor of Institute of geography and resources, Chinese Academy of Sciences, and the data of urban population are from the census data of each year, the statistical yearbook of each province in the Qinghai Tibet Plateau, etc. The data quality is excellent, which can be used to analyze the population growth trend, urban expansion and the impact of human activities on the surrounding environment of cities and towns in the Qinghai Tibet Plateau.

Tibetan, one of the largest indigenous populations living in the high-altitude region of the Tibetan Plateau (TP), has developed a suite of physiological adaptation strategies to cope with the extreme highland environment in TP. Here, we reported genome-wide SNP data from 48 Kham-speaking Nagqu Tibetans and analyzed it with published data from 1,067 individuals in 167 modern and ancient populations to characterize the detailed Tibetan subgroup history and population substructure. Overall, the patterns of allele sharing and haplotype sharing suggested (1) the relatively genetic homogeny between the studied Nagqu Tibetans and ancient Nepalese as well as present-day core Tibetans from Lhasa, Nagqu, and Shigatse; and (2) the close relationship between our studied Kham-speaking Nagqu Tibetans and Kham-speaking Chamdo Tibetans. The fitted qpAdm models showed that the studied Nagqu Tibetans could be fitted as having the main ancestry from late Neolithic upper Yellow River millet farmers and deeply diverged lineages from Southern East Asians (represented by Upper Paleolithic Guangxi_Longlin and Laos_Hoabinhian), and a non-neglectable western Steppe herder-related ancestry (∼3%). We further scanned the candidate genomic regions of natural selection for our newly generated Nagqu Tibetans and the published core Tibetans via FST, iHS, and XP-EHH tests. The genes overlapping with these regions were associated with essential human biological functions such as immune response, enzyme activity, signal transduction, skin development, and energy metabolism. Together, our results shed light on the admixture and evolutionary history of Nagqu Tibetan populations.

Forensic parameters of the 12 X-STR loci in Tibetans population residing in Nagqu city in the north of the Tibet Autonomous Region (TAR) in China (n = 549).

131 (ten thousand persons) in 2020. Urban population refers to all people residing in cities and towns, while rural population refers to population other than urban population.

Population: Census: Tibet: Xigaze data was reported at 798.153 Person th in 12-01-2020. This records an increase from the previous number of 703.292 Person th for 12-01-2010. Population: Census: Tibet: Xigaze data is updated decadal, averaging 703.292 Person th from Dec 2000 (Median) to 12-01-2020, with 3 observations. The data reached an all-time high of 798.153 Person th in 12-01-2020 and a record low of 635.200 Person th in 12-01-2000. Population: Census: Tibet: Xigaze data remains active status in CEIC and is reported by Xigaze Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GE: Population: Prefecture Level City: By Census.

This line shapefile represents rivers in the Autonomous region of Tibet (Xizang) for 2000. These data are represented at 1:1,000,000 scale. This layer is part of the China 2000 township population census dataset.

The data set contains series data of populations of major cities and counties on the Tibetan Plateau from 1970 to 2006. It is used to study social and economic changes on the Tibetan Plateau. The table has six fields. Field 1: Year Interpretation: Year of the data Field 2: Province Interpretation: The province from which the data were obtained Field 3: City/Prefecture Interpretation: The city or prefecture from which the data were obtained Field 4: County Interpretation: The name of the county Field 5: Population (10,000) Interpretation: Population Field 6: Data Sources Interpretation: Source of Data Extraction The data comes from the statistical yearbook and county annals of Tibet Autonomous Region, Qinghai, Sichuan, Gansu, Yunnan and Xinjiang. Some are listed as follows: [1] Gansu Yearbook Editorial Committee. Gansu Yearbook [J]. Beijing: China Statistics Press, 1984, 1988-2009 [2] Statistical Bureau of Yunnan Province. Yunnan Statistical Yearbook [J]. Beijing: China Statistics Press, 1988-2009 [3] Statistical Bureau of Sichuan Province, Sichuan Survey Team. Sichuan Statistical Yearbook [J]. Beijing: China Statistics Press, 1987-1991, 1996-2009 [4] Statistical Bureau of Xinjiang Uighur Autonomous Region . Xinjiang Statistical Yearbook [J]. Beijing: China Statistics Press, 1989-1996, 1998-2009 [5] Statistical Bureau of Tibetan Autonomous Region. Tibet Statistical Yearbook [J]. Beijing: China Statistics Press, 1986-2009 [6] Statistical Bureau of Qinghai Province. Qinghai Statistical Yearbook [J]. Beijing: China Statistics Press, 1986-1994, 1996-2008. [7] County Annals Editorial Committee of Huzhu Tu Autonomous County. County Annals of Huzhu Tu Autonomous County [J]. Qinghai: Qinghai People's Publishing House, 1993 [8] Haiyan County Annals Editorial Committee. Haiyan County Annals[J]. Gansu: Gansu Cultural Publishing House, 1994 [9] Menyuan County Annals Editorial Committee. Menyuan County Annals[J]. Gansu: Gansu People's Publishing House, 1993 [10] Guinan County Annals Editorial Committee. Guinan County Annals [J]. Shanxi: Shanxi People's Publishing House, 1996 [11] Guide County Annals Editorial Committee. Guide County Annals[J]. Shanxi: Shanxi People's Publishing House, 1995 [12] Jianzha County Annals Editorial Committee. Jianzha County Annals [J]. Gansu: Gansu People's Publishing House, 2003 [13] Dari County Annals Editorial Committee. Dari County Annals [J]. Shanxi: Shanxi People's Publishing House, 1993 [14] Golmud City Annals Editorial Committee. Golmud City Annals [J]. Beijing: Fangzhi Publishing House, 2005 [15] Delingha City Annals Editorial Committee. Delingha City Annals [J]. Beijing: Fangzhi Publishing House, 2004 [16] Tianjun County Annals Editorial Committee. Tianjun County Annals [J]. Gansu: Gansu Cultural Publishing House, 1995 [17] Naidong County Annals Editorial Committee. Naidong County Annals [J]. Beijing: China Tibetology Press, 2006 [18] Gulang County Annals Editorial Committee. Gulang County Annals [J]. Gansu: Gansu People's Publishing House, 1996 [19] County Annals Editorial Committee of Akesai Kazak Autonomous County. County Annals of Akesai Kazakh Autonomous County [J]. Gansu: Gansu People's Publishing House, 1993 [20] Minxian County Annals Editorial Committee. Minxian County Annals [J]. Gansu: Gansu People's Publishing House, 1995 [21] Dangchang County Annals Editorial Committee. Dangchang County Annals [J]. Gansu: Gansu Cultural Publishing House, 1995 [22] Dangchang County Annals Editorial Committee. Dangchang County Annals(Sequel) (1985-2005) [J]. Gansu: Gansu Cultural Publishing House, 2006 [23] Wenxian County Annals Editorial Committee. Wenxian County Annals[J]. Gansu: Gansu Cultural Publishing House, 1997 [24] Kangle County Annals Editorial Committee. Kangle County Annals [J]. Shanghai: Sanlian Bookstore. 1995 [25] County Annals Editorial Committee of Jishishan (Baoan, Dongxiang, Sala) Autonomous County. County Annals of Jishishan (Baoan, Dongxiang, Sala) Autonomous County[J], Gansu: Gansu Cultural Publishing House, 1998 [26] Luqu County Annals Editorial Committee. Luqu County Annals [J]. Gansu: Gansu People's Publishing House, 2006 [27] Zhouqu County Annals Editorial Committee. Zhouqu County Annals [J]. Shanghai: Sanlian Bookstore. 1996 [28] Xiahe County Annals Editorial Committee. Xiahe County Annals [J]. Gansu: Gansu Cultural Publishing House, 1999 [29] Zhuoni County Annals Editorial Committee. Zhuoni County Annals [J]. Gansu: Gansu Nationality Publishing House, 1994 [30] Diebu County Annals Editorial Committee. Diebu County Annals [J]. Gansu: Lanzhou University Press, 1998 [31] Pengxian County Annals Editorial Committee. Pengxian County Annals [J]. Sichuan: Sichuan People's Publishing House, 1989 [32] Guanxian County Annals Editorial Committee. Guanxian County Annals [J]. Sichuan: Sichuan People's Publishing House, 1991 [33] Wenjiang County Annals Editorial Committee. Wenjiang County Annals [J]. Sichuan: Sichuan People's Publishing House, 1990 [34] Shifang County

The qinghai-tibet plateau is one of the most challenging environment for human survival, is known as the "third pole" of the earth.At an average altitude of 4000 meters, 4000 m (only for sea level by about 60%.Plateau of oxygen for human survival is a strong selection pressure, most of the plateau non-adaptive individuals exposed to plateau hypoxia environment will cause the red blood cells (red blood cells increased disease) increase in the number and the backlog of red blood cells, Hematocrit (HCT) levels.Plateau Tibetan genetic background of the single, high altitude environment for a long time to adapt to the related genes on the plateau has the effect that is choosing, result in different altitude gradient in the relevant single nucleotide polymorphisms (SNPS) chain stable genetic differences, suitable for the research of high altitude adaptation between phenotype and genotype.This research adopts the methods of DNA microarray (DNA Array), compared with 150 cases of the Tibetan plateau and the Tibetan male genome-wide microarray data in east asians, each sample to obtain about 700000 loci (including nuclear genome, mitochondrial DNA and Y chromosome) classification results, analysis of the differences between SNPs, genes and signaling pathways, and detection of plateau Tibetan men in order to adapt to high altitude hypoxia environment characteristics of adaptive evolution at the molecular level.This data can help in Tibetan population genetic adaptation from the nuclear genome aspects, through the comparison of data with the plateau surrounding population, can be more comprehensive understanding of the plateau native men of adaptive evolution.For the study of human and biological evolution, to explore the molecular of high and low altitude population level difference, the different geographical environment of human kinship and low oxygen to supply a basis for the choice of the function of genes of genetic reference data.

In terms of Chinese language, this study crawls the news obtained from the People's Daily website using festival names as search terms as initial data, and manually reviews and removes the news items that contain festival names but have nothing to do with the festival. The data collection time is April 22, 2022. Tibetan language aspect, this study used hainan Tibetan autonomous prefecture in qinghai province of Tibetan information technology research center development cloud hid ཡ ོ ང ས ་ འ ཛ ི ན search engine (https://www.yongzin.com) is similar to Chinese, this study took up in table 1 festival called search word search results, but considering the precision of results, This study selected the People's Daily online Tibetan edition (http://tibet.people.com.cn/), China's Tibet network (http://tb.tibet.cn/), the voice of China Tibet net (http://www.vtibet.cn/), hidden to the sun (http://ti.zangd Iyg.com/), Tibet, China news network (http://tb.chinatibetnews.com/) as a crawler to climb in the white list of web sites, namely all the Tibetan news corpora are from the website.Four Tibetan students whose native language is Tibetan and four Han students whose native language is Chinese were recruited to annotate the news data. Before the formal annotation, in order to ensure the annotation effect, this study conducted unified training for the annotators. The annotation software used was YEDDA[31], and the annotated entities included Tibetan festival ontology, Tibetan festival related events, Tibetan festival related articles and Tibetan festival related places.

Indigenous populations of the Tibetan plateau have attracted much attention for their good performance at extreme high altitude. Most genetic studies of Tibetan adaptations have used genetic variation data at the genome scale, while genetic inferences about their demography and population structure are largely based on uniparental markers. To provide genome-wide information on population structure, we analyzed new and published data of 338 individuals from indigenous populations across the plateau in conjunction with worldwide genetic variation data. We found a clear signal of genetic stratification across the east-west axis within Tibetan samples. Samples from more eastern locations tend to have higher genetic affinity with lowland East Asians, which can be explained by more gene flow from lowland East Asia onto the plateau. Our findings corroborate a previous report of admixture signals in Tibetans, which were based on a subset of the samples analyzed here, but add evidence for isolation by distance in a broader geospatial context.

To investigate the paternal genetic structure of Tibetans, 447 male samples were collected from Ngari (n=211), Chamdo (n=119), and Nyingchi (n=117). Firstly, SNP genotyping was performed to allocate samples into haplogroups. To further evaluate the genetic diversity of the major Y-chromosomal haplogroup in Tibetan populations from Lhasa, eight commonly used Y-chromosomal STR (short tandem repeat) loci (DYS19, DYS388, DYS389I, DYS389II, DYS390, DYS391, DYS392, and DYS393) were genotyped using fluorescence-labeled primers with an ABI 3130XL Genetic Analyzer (Applied Biosystems, USA). The results indicated that haplogroup D displayed highest frequency in these three Tibetan populations (Ngari 54.50%, Nyingchi 64.10%, Chamdo 67.23%). Among haplogroup D, D-P47 showed the highest frequency (Ngari 29.39%, Nyingchi 51.28%, Chamdo 55.46%). Differently, D-N1 showed the highest frequency in Ngari (21.33%), followed by Nyingchi (11.97%) and Chamdo (10.92%). Haplogroup O-M117 is the second frequent haplogroup in these three populations, with the highest frequency in Ngari (29.86%), followed by Nyingchi (26.50%) and Chamdo (15.97%). Compared with the other two populations, Ngari Tibetans have higher frequencies of western Eurasian haplogroups, including R-M17 (1.42%), R-M343 (1.42%), and J, probably reflecting more genetic contribution from the west into Ngari. In combination with the data from Lhasa that deposited in 2019 and 2020, our Y chromosome data of Tibetans from different locations on the Tibetan Plateau will be very helpful to understanding the paternal genetic structure of Tibetans. Moreover, the genetic history of Tibetans can also be dissected by phylogeographic and coalescent analyses.

The average altitude of the Tibetan Plateau is more than 4000 meters. The harsh environment such as high cold and low oxygen poses a huge challenge to human survival. However, since the late Paleolithic period, Tibetan people in the plateau have reached the Plateau, and in the Neolithic period, people began to permanently settled on the high-altitude areas on a large scale. The history of population migration in this process has become the focus of different fields. In order to analyze the genetic structure of Tibetan population from the perspective of the whole genome and trace back the history of human settlement on the plateau, we obtained the whole genome variation data of 20 Tibetan individuals. The SNP typing of 20 samples was carried out by DNA array method, and about 700000 loci (including nuclear genome, mitochondrial DNA and Y chromosome) of each sample were obtained. Based on the above data, relevant biological information analysis (mainly including chip site quality control analysis, Y chromosome and mitochondrial DNA haplotype analysis) was carried out. This data is helpful to analyze the genetic structure of Tibetan population from the perspective of nuclear genome, Y chromosome and mitochondrial DNA. By comparing with the data of people around the plateau, we can trace the migration and settlement history of the plateau population comprehensively.