This statistic depicts the year-on-year growth rate of the gross domestic product of Xinjiang Uygur Autonomous Region in China from 2000 to 2023. In 2023, Xinjiang's GDP value grew by 6.8 percent from the previous year.

Clarifying the relationship between economic development and human well-being is conducive to promoting high-quality economic development. This study focused on 16 prefecture-level cities in the Qinghai-Xizang Plateau region. The critic weighting method assessed the 2007–2018 human well-being index (HWI). The Tapio decoupling model allowed the study of the human well-being decoupling state. Finally, the drivers of decoupling between economic development and human well-being were analyzed using the Logarithmic Mean Divisia Index method. The results indicated that (1) almost all cities in the study region had an upward 2007–2018 HWI trend, but there were significant differences in growth magnitude and change trend. (2) Economic development and human well-being in the study region in 2007–2018 had expansion negative decoupling, thus, human well-being increased with economic growth, but not as fast as gross domestic product. 9 cities in 2007 showed weak decoupling, expansion connection, and expansion negative decoupling, increasing to 13 cities by 2018, indicating that human well-being development gradually improved from 2007 to 2018. (3) For most cities, the economic scale effect was the most influential factor in the decoupling of economic development and human well-being. Therefore, this study provided policy recommendations for decoupling economic development and human well-being.

Population: Natural Growth Rate: Xinjiang data was reported at 0.093 % in 2023. This records an increase from the previous number of 0.077 % for 2022. Population: Natural Growth Rate: Xinjiang data is updated yearly, averaging 1.086 % from Dec 2000 (Median) to 2023, with 24 observations. The data reached an all-time high of 1.217 % in 2000 and a record low of 0.056 % in 2021. Population: Natural Growth Rate: Xinjiang 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: Natural Growth Rate: By Region.

CN:(GDP) Gross Domestic ProductIndex: PY=100: TI: Scientific Research and Development, Technical Service: Xinjiang: Urumqi data was reported at 106.300 Prev Year=100 in 2018. This records an increase from the previous number of 98.500 Prev Year=100 for 2017. CN:(GDP) Gross Domestic ProductIndex: PY=100: TI: Scientific Research and Development, Technical Service: Xinjiang: Urumqi data is updated yearly, averaging 110.800 Prev Year=100 from Dec 2010 (Median) to 2018, with 9 observations. The data reached an all-time high of 122.900 Prev Year=100 in 2011 and a record low of 92.900 Prev Year=100 in 2010. CN:(GDP) Gross Domestic ProductIndex: PY=100: TI: Scientific Research and Development, Technical Service: Xinjiang: Urumqi data remains active status in CEIC and is reported by Urumqi Municipal Bureau of Statistics. The data is categorized under China Premium Database’s National Accounts – Table CN.AE: Gross Domestic Product: Prefecture Level City: Index: TI: Scientific Research and Development, Technical Service.

Major decoupling states in the Qinghai-Xizang Plateau region in the IAC, MOP, MOS, and RAC dimensions from 2007–2018.

As one of the regions with the richest plant resources in China, Xizang has more than 5000 species of higher plants, of which more than 90% are distributed in forest areas. These forests not only provide abundant timber resources for national economic development, but also contain diverse wild plant resources. Although economic and traffic conditions have limited the investigation and development of wild plant resources, in recent years, medical workers in Xizang, together with scientific research departments and local people, have compiled Common Chinese Herbal Medicines in Xizang, which includes more than 320 kinds of medicinal plants. At the same time, the Tibetan Plateau Comprehensive Scientific Expedition of the Chinese Academy of Sciences paid attention to the excavation and analysis of Tibetan medicine, especially in the collection of oil plants. The forestry team focused on studying the uses of major tree species and the growth status of economic trees. This data set is the digital collation result of the data of the first scientific expedition to Xizang in the Scientific Expedition Series on the Xizang Plateau, which aims to collect relevant information about important economic plants in Xizang and help people understand the importance of Tibetan forests as gene banks in preserving germplasm resources. The dataset is stored in Excel format and contains 10 worksheets, covering the growth characteristics and climatic conditions of varieties such as walnuts, tea trees, apples, etc. After strict data entry and quality control, the data is ensured to be accurate and reliable, providing a solid basis for future scientific research.

Population: Household Registration: Natural Growth Rate: Xinjiang: Turpan data was reported at 1.610 ‰ in 2018. This records a decrease from the previous number of 8.520 ‰ for 2017. Population: Household Registration: Natural Growth Rate: Xinjiang: Turpan data is updated yearly, averaging 5.830 ‰ from Dec 2015 (Median) to 2018, with 4 observations. The data reached an all-time high of 8.760 ‰ in 2016 and a record low of 1.610 ‰ in 2018. Population: Household Registration: Natural Growth Rate: Xinjiang: Turpan data remains active status in CEIC and is reported by Turpan Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GE: Population: Prefecture Level City: Household Registration: Natural Growth Rate.

(1) Human well-being on the Qinghai Tibet Plateau based on the human development index: the human well-being on the Qinghai Tibet Plateau (Qinghai and Xizang provinces) is measured quantitatively using the comprehensive human development index, an objective well-being assessment indicator. Referring to the functional structure framework of human welfare in China in the new era, the functional structure of human groups is divided into basic functions, harmonious functions, development functions and sustainable functions. On the basis of the four functions, functional indicators and specific indicator systems are further designed, that is, health, education, integration of urban and rural areas, living standards and coping with climate change account for 1/5 of the five functional indicators, and the secondary indicators are also set with equal rights. This data can reflect the comprehensive development level of human beings in Qinghai and Xizang to a certain extent, and has certain reference significance for the future development planning of the Qinghai Tibet Plateau. (2) Regional Social Relations Comprehensive Index: Based on data collected from the 2010-2019 China Regional Economic Statistical Yearbook, China Urban Statistical Yearbook, China Civil Affairs Statistical Yearbook, Provincial (Autonomous Region) Statistical Yearbook and Statistical Bulletin, relevant City Statistical Bulletin, etc., a regional social relations evaluation index system was constructed on the basis of regional social relations analysis in provincial-level areas of the Qinghai Tibet Plateau. The weights of various indicators were determined, and the regional social relations comprehensive index of 37 prefecture level cities on the Qinghai Tibet Plateau was calculated. Based on this data, obtain a spatiotemporal distribution map of regional social relations at the prefecture level on the Qinghai Tibet Plateau. (3) Human economic well-being related data: Based on data from the China Statistical Yearbook of six provinces in the Qinghai Tibet Plateau region from 2000 to 2017, and considering the complexity of human well-being, 18 indicators were selected to construct a human economic well-being indicator system suitable for evaluating the Qinghai Tibet Plateau region from four aspects: income and consumption, production materials, living materials, and resource acquisition capacity; Based on data from 17 prefecture level cities in the Qinghai Tibet Plateau region from 2007 to 2018, including the China Urban Statistical Yearbook, provincial (autonomous region) statistical yearbooks and bulletins, and relevant urban statistical bulletins, and considering the actual situation of typical cities in the Qinghai Tibet Plateau region, 22 indicators were selected to construct a human welfare index system from five aspects: income and consumption, means of production, means of livelihood, resource acquisition ability, and physical health. This indicator helps to better understand the actual conditions of basic living conditions such as economy, material resources, and means of production of residents in various regions of the Qinghai Tibet Plateau. (4) Habitat quality of the Qinghai Tibet Plateau: This dataset is based on the InVEST model and uses land use data, road data, and terrain data to calculate the habitat quality of the Qinghai Tibet Plateau from 2000 to 2020. The data span is 20 years, with data provided every 5 years and a resolution of 1000m. Among them, the land use data is sourced from the global 30 meter land cover fine classification product（ http://data.casearth.cn/sdo/list ）. The DEM data is sourced from the National Qinghai Tibet Plateau Science Data Center（ http://data.tpdc.ac.cn ）. The road data is sourced from the OpenStreetMap website（ http://openstreetmap.org/ ）. (5) Educational welfare: Based on the education statistical data of various provinces from 2013 to 2021 released on the official website of the Ministry of Education of the People's Republic of China, the compilation of science and technology statistical data of higher education institutions, the Statistical Yearbook of China's Disability Affairs, the Statistical Yearbook of China's Education Funds, relevant research reports, and other publicly available data, the entropy weight method is selected to objectively determine the weights of each evaluation indicator. The natural breakpoint method is used to grade the various educational welfare evaluation data obtained in 2013 and 2021, and to draw educational welfare evaluation maps and comprehensive educational welfare evaluation maps of various levels and types of schools. This provides a more accurate understanding of the spatiotemporal pattern of various educational welfare and comprehensive educational welfare on the Qinghai Tibet Plateau, and provides scientific basis and decision-making reference for relevant departments. (6) Human welfare in the Dadu River Basin: Based on meteorological data from

FAI: excl Rural Household: Real Estate Development: Xinjiang data was reported at 115,890.000 RMB mn in 2021. This records a decrease from the previous number of 126,088.780 RMB mn for 2020. FAI: excl Rural Household: Real Estate Development: Xinjiang data is updated yearly, averaging 10,207.630 RMB mn from Dec 1986 (Median) to 2021, with 36 observations. The data reached an all-time high of 126,088.780 RMB mn in 2020 and a record low of 51.000 RMB mn in 1987. FAI: excl Rural Household: Real Estate Development: Xinjiang data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Investment – Table CN.OD: Fixed Asset Investment: Annual: excl Rural Household: Real Estate Development.

Largest influences on the decoupling from 2007–2018.

Population: Household Registration: Natural Growth Rate: Xinjiang: Hami data was reported at 5.690 ‰ in 2018. This records an increase from the previous number of -2.040 ‰ for 2017. Population: Household Registration: Natural Growth Rate: Xinjiang: Hami data is updated yearly, averaging 4.635 ‰ from Dec 2015 (Median) to 2018, with 4 observations. The data reached an all-time high of 6.480 ‰ in 2016 and a record low of -2.040 ‰ in 2017. Population: Household Registration: Natural Growth Rate: Xinjiang: Hami data remains active status in CEIC and is reported by Hami Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GE: Population: Prefecture Level City: Household Registration: Natural Growth Rate.

Energy-based economic development brings about some environmental problems, and as China’s economy shifts from rapid growth to high-quality development, the implementation of environmental regulation is crucial to achieving environmental protection and high-quality economic development. Based on the panel data of 14 prefectures and cities from 2000 to 2018 in Xinjiang, this study explored the impact of environmental regulation on high-quality economic development by constructing a comprehensive evaluation index system and using entropy method and Tobit regression model. The results show that 1) overall, each 1% increase in environmental regulation is associated with a 0.037% rise in high-quality economic development level; 2) regionally, each 1% increase in environmental regulation is associated with a 0.119% rise in high-quality economic development level in northern Xinjiang, but the effect on the southern Xinjiang is not significant; 3) each 1% increase in environmental regulation, the level of high-quality economic development decreased by 0.034% from 2000 to 2010 and increased by 0.061% from 2011 to 2018. In general, this study adds to the theoretical and empirical study on the influence of environmental regulation on high-quality economic development while providing a methodology for other economies to assess the relationship between the two.

Land Area Developed: Year to Date: Xinjiang data was reported at 4,997.128 sq m th in Dec 2010. This records an increase from the previous number of 4,465.285 sq m th for Nov 2010. Land Area Developed: Year to Date: Xinjiang data is updated monthly, averaging 1,615.600 sq m th from Apr 1999 (Median) to Dec 2010, with 127 observations. The data reached an all-time high of 7,136.500 sq m th in Dec 2005 and a record low of 0.000 sq m th in Feb 2010. Land Area Developed: Year to Date: Xinjiang data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Real Estate Sector – Table CN.RKD: Land Purchase and Development.

Population: Household Registration: Natural Growth Rate: Xinjiang: Urumqi data was reported at 3.360 ‰ in 2018. This records an increase from the previous number of -2.490 ‰ for 2017. Population: Household Registration: Natural Growth Rate: Xinjiang: Urumqi data is updated yearly, averaging 6.000 ‰ from Dec 2010 (Median) to 2018, with 9 observations. The data reached an all-time high of 7.590 ‰ in 2014 and a record low of -2.490 ‰ in 2017. Population: Household Registration: Natural Growth Rate: Xinjiang: Urumqi data remains active status in CEIC and is reported by Urumqi Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GE: Population: Prefecture Level City: Household Registration: Natural Growth Rate.

With the rapid economic development of Xinjiang Uygur Autonomous Region (Xinjiang), energy consumption became the primary source of carbon emissions. The growth trend in energy consumption and coal-dominated energy structure are unlikely to change significantly in the short term, meaning that carbon emissions are expected to continue rising. To clarify the changes in energy-related carbon emissions in Xinjiang over the past 15 years, this paper integrates DMSP/OLS and NPP/VIIRS data to generate long-term nighttime light remote sensing data from 2005 to 2020. The data is used to analyze the distribution characteristics of carbon emissions, spatial autocorrelation, frequency of changes, and the standard deviation ellipse. The results show that: (1) From 2005 to 2020, the total carbon emissions in Xinjiang continued to grow, with noticeable urban additions although the growth rate fluctuated. In spatial distribution, non-carbon emission areas were mainly located in the northwest; low-carbon emission areas mostly small and medium-sized towns; and high-carbon emission areas were concentrated around the provincial capital and urban agglomerations. (2) There were significant regional differences in carbon emissions, with clear spatial clustering of energy consumption. The clustering stabilized, showing distinct "high-high" and "low-low" patterns. (3) Carbon emissions in central urban areas remained stable, while higher frequencies of change were seen in the peripheral areas of provincial capitals and key cities. The center of carbon emissions shifted towards southeast but later showed a trend of moving northwest. (4) Temporal and spatial variations in carbon emissions were closely linked to energy consumption intensity, population size, and economic growth. These findings provided a basis for formulating differentiated carbon emission targets and strategies, optimizing energy structures, and promoting industrial transformation to achieve low-carbon economic development in Xinjiang.

Xinjiang: FAI: excl Rural Household: TI: SG: Research and Experimental Development data was reported at 418.090 RMB mn in 2017. This records an increase from the previous number of 117.030 RMB mn for 2016. Xinjiang: FAI: excl Rural Household: TI: SG: Research and Experimental Development data is updated yearly, averaging 120.530 RMB mn from Dec 2004 (Median) to 2017, with 14 observations. The data reached an all-time high of 418.090 RMB mn in 2017 and a record low of 0.750 RMB mn in 2011. Xinjiang: FAI: excl Rural Household: TI: SG: Research and Experimental Development data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Investment – Table CN.OD: Fixed Asset Investment: Annual: Xinjiang.

With the rapid economic development of Xinjiang Uygur Autonomous Region (Xinjiang), energy consumption became the primary source of carbon emissions. The growth trend in energy consumption and coal-dominated energy structure are unlikely to change significantly in the short term, meaning that carbon emissions are expected to continue rising. To clarify the changes in energy-related carbon emissions in Xinjiang over the past 15 years, this paper integrates DMSP/OLS and NPP/VIIRS data to generate long-term nighttime light remote sensing data from 2005 to 2020. The data is used to analyze the distribution characteristics of carbon emissions, spatial autocorrelation, frequency of changes, and the standard deviation ellipse. The results show that: (1) From 2005 to 2020, the total carbon emissions in Xinjiang continued to grow, with noticeable urban additions although the growth rate fluctuated. In spatial distribution, non-carbon emission areas were mainly located in the northwest; low-carbon emission areas mostly small and medium-sized towns; and high-carbon emission areas were concentrated around the provincial capital and urban agglomerations. (2) There were significant regional differences in carbon emissions, with clear spatial clustering of energy consumption. The clustering stabilized, showing distinct "high-high" and "low-low" patterns. (3) Carbon emissions in central urban areas remained stable, while higher frequencies of change were seen in the peripheral areas of provincial capitals and key cities. The center of carbon emissions shifted towards southeast but later showed a trend of moving northwest. (4) Temporal and spatial variations in carbon emissions were closely linked to energy consumption intensity, population size, and economic growth. These findings provided a basis for formulating differentiated carbon emission targets and strategies, optimizing energy structures, and promoting industrial transformation to achieve low-carbon economic development in Xinjiang.

Population: Household Registration: Birth Rate: Xinjiang: Urumqi data was reported at 11.990 ‰ in 2018. This records a decrease from the previous number of 12.870 ‰ for 2017. Population: Household Registration: Birth Rate: Xinjiang: Urumqi data is updated yearly, averaging 9.870 ‰ from Dec 2010 (Median) to 2018, with 9 observations. The data reached an all-time high of 12.870 ‰ in 2017 and a record low of 8.540 ‰ in 2011. Population: Household Registration: Birth Rate: Xinjiang: Urumqi data remains active status in CEIC and is reported by Urumqi Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GE: Population: Prefecture Level City: Household Registration: Natural Growth Rate.

R & D: Expenditure: Industrial Enterprise: Xinjiang data was reported at 8,110.010 RMB mn in 2023. This records an increase from the previous number of 6,411.902 RMB mn for 2022. R & D: Expenditure: Industrial Enterprise: Xinjiang data is updated yearly, averaging 2,233.515 RMB mn from Dec 1999 (Median) to 2023, with 25 observations. The data reached an all-time high of 8,110.010 RMB mn in 2023 and a record low of 148.776 RMB mn in 1999. R & D: Expenditure: Industrial Enterprise: Xinjiang data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Business and Economic Survey – Table CN.OS: Research and Development: Expenditure: Region.

Since the implementation of China’s Western Development Policy, Xinjiang has experienced rapid socio-economic development and significant changes in its land use patterns. As an important factor in agricultural production, farmland is of crucial for realizing the rural revitalization strategy. Based the theoretical mechanisms of farmland use transformation, this study selected five periods of land use and socioeconomic data from 2000, 2005, 2010, 2015, and 2018 to study the spatial and temporal evolutionary characteristics of farmland use transformation in Xinjiang since China’s Western Development Policy. We then explored the driving mechanisms using an optimal geographic detector model based on parameters. The results showed that (1) Xinjiang’s farmland use transitioned toward large scale and multifunctionality, and the transition characteristics are mainly of fluctuating growth type. The spatial transformation and functional transformation characteristics were generally consistent in spatial distribution. (2) There was a spatial agglomeration in the transformation, which was concentrated in the economic zone of the northern slope of Tianshan Mountain, the Yili River Valley and Kashgar region. The concentration of functional transformation of farmland has increased, but the spatial transformation of farmland has weakened. (3) The role of influencing factors on the transformation of farmland use differed with periods. Finally, the study concluded that the functional transformation of farmland in Xinjiang since China’s Western Development Policy is still at the stage of mainly production function. We suggest that the protection of farmland in Xinjiang in the New Western Development period should be achieved by promoting the transformation of the function of farmland. The findings of this study provide decision-making assistance for the management of farmland use in Xinjiang during the New Western Development period and are an effective tool for achieving the goals of sustainable farmland use and agricultural and rural modernization.