Population China

We have shared the data "19 Population density of China at the town level" at the Data Released channel of BCL.

Projecting 1 km-grid population distributions from 2020 to 2100 globally under shared socioeconomic pathways

Spatially explicit population grid can play an important role in climate change, resource management, sustainable development and other felds. Several gridded datasets already exist, but global data, especially high-resolution data on future populations are largely lacking. Based on the WorldPop dataset, we present a global gridded population dataset covering 248 countries or areas at 30 arcseconds (approximately 1km) spatial resolution with 5-year intervals for the period 2020–2100 by implementing Random Forest (RF) algorithm. Our dataset is quantitatively consistent with the Shared Socioeconomic Pathways’ (SSPs) national population. The spatially explicit population dataset we predicted in this research is validated by comparing it with the WorldPop dataset both at the subnational and grid level. 3569 provinces (almost all provinces on the globe) and more than 480 thousand grids are taken into verifcation, and the results show that our dataset can serve as an input for predictive research in various felds.
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Wang et al 2022 SciData_PopulationProjec
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Scenario Analysis for China's Future Population Structure

Human activities have now become a major driver of global environmental change. As the world's most populous country, China should make more contributions to the world's sustainable development and climate change. On September 22, 2020, President Xi Jinping proposed China's "Two Carbon Development Goals", which will set the direction for China's future development. Cities are the most concentrated areas of human production and life, so we believe that the key to China's low-carbon transition lies in cities. Further, cities are for people, so human needs determine the energy consumption of the city. People of different age structures and social backgrounds have different needs for urban management services and energy use, which in turn affects future urban management and urban construction. It is worthwhile to explore how to determine the future demographic structure and then make a judgment on the future social needs to realize the future low-carbon development of China.

The full report is also available online at the EFC website: https://www.efchina.org/Reports-zh/report-lccp-20230309-zh

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中国未来人口结构情景分析 技术报告 20230316.pdf
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2025-2060中国年龄结构预测结果(省级).xlsx
Microsoft Excel Table 244.7 KB
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2025-2060中国收入结构预测结果(省级).xlsx
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Population Scenario Analysis for China

当前,人类活动已成为全球环境变化的主要驱动力,合理预测中国人口的发 展趋势,对于预测和理解中国未来的城镇化格局,调节中国城市能源供给平衡, 控制能源排放,实现中国城市低碳转型等都具有十分重要的指导意义。在此背景 下,能源基金会于 2019 年支持清华大学建筑学院龙瀛团队,开展“中国未来城 市人口分布情景分析”研究,对中国的城市人口,在省域、县域等层面上的分布 进行分析与预测。

我们对现有的人口预测研究进行了梳理,发现目前的相关研究多以历史梳 理、现状分析为主,在情景分析、空间尺度和精度上都略有不足。在此基础上, 我们将城市区位、聚集度等多种情景条件引入,在公里网格尺度上对未来中国的 人口分布进行了多情景下的预测。该研究的方法可以简要概括为两步:以线性回 归为核心的市辖区层面上的人口总量与城镇化率预测;以土地利用变化和 LandScan 人口耦合数据为核心的公里网格尺度的人口判定。我们最终获得了多种 情景下的中国未来人口公里网格分布地图。研究发现,未来的中国大城市依然存 在很大的人口增长压力,而中西部城市将是中国未来城镇化的主要战场。

The full report is also available online at the EFC website: https://www.efchina.org/Reports-zh/report-lccp-20210207-3-zh

The data we produced are available online at figshare: https://figshare.com/articles/figure/___Data_of_Population_Scenario_Analysis_for_China/22277677/2

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中国未来城市人口分布情景分析.pdf
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Metropolitan regions of China

We delineate metropolitan regions of China using the population census in 2000 and 2010, respectively. The benchmark used here is 1000 persons per square kilometer. The first map is for the whole China, and the other three are for the three main urban agglomerations (in the same scale for cross comparison). Note that commuting is not considered in the study due to data limitation.

Data source: the population census of China in 2000 and 2010, in the township scale

Population at the township level of China (2000-2010)

In the township scale for the whole China

Data source: the population census of China in 2000 and 2010

We have released the township level population data in 2010 at the Data Released channel (Data 19).

Welcome repost and cite:

  • Wu, K., Long, Y., Mao, Q., & Liu, X. (2015). Mushrooming Jiedaos, Growing Cities: An Alternative Perspective on Urbanizing China. Environment and Planning A, 47, 1-2.
  • Mao Q, Long Y, & Wu K. (2015). Spatio-Temporal Changes of Population Density and Exploration on Urbanization Pattern in China: 2000-2010. City Planning Review, 39(2): 38-43. [毛其智, 龙瀛, 吴康. 2015. 中国人口密度时空演变与城镇化空间格局初探——从2000年到2010年. 城市规划, 39(2):38-43.]
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Mao et al 2016 CCPR_Population.pdf
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毛其智等 2015 城市规划_人口密度.pdf
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Mushrooming Jiedaos in China

Understanding urbanizing China from the administrative view

With more than 15 million new urban residents entering its cities every year, China is witnessing one of the greatest socioeconomic and environmental transformations in human history. In addition to these ongoing changes, urbanization in China often involves a significant political dimension, as the government would purposely accord city status to settlements, regardless of their developmental level: Largely rural settlements could be turned into “cities” overnight by administrative power. Nevertheless, city status would often translate into real urban growth, as it is closely linked to the land use quota, provision of public services, as well as local governments’ power in China. While socioeconomic and environmental aspects of Chinese cities have been analyzed extensively with aggregated statistics and remote sensing data (Deng et al, 2012; Liu et al, 2012), little is known about the shifting political geography of Chinese cities, i.e., where new city status are being granted. It is this lacuna that our project aims to fill.

We focus on the basic building block of a city proper in China: Jiedao (sub-districts). Jiedao’s counterparts in the rural area are Xiang (township) and Zhen (town), and all three are termed as township-level administrative units. We geocoded the 41,871 towship-level units based the Population Census of China, and estimated the spatial extent of individual units with Voronoi diagrams for the years of 2000 and 2010.

The end product is the first ever map of “mushrooming” Jiedaos in China. The total number of Jiedaos has grown from 5,510 to 6,923 – a 25% increase – during 2000-2010. Most new city-propers are created around major urban regions along the economically more developed eastern coast (e.g., Yangtze River Delta, Pearl River Delta, Shandong Peninsula, and Beijing-Tianjin-Hebei (BTH)). Other regions with noticeable growth are Central Henan in Central China, as well as the Chengdu-Chongqing corridor in West China. As Zhens are often turned into Jiedaos and considered as “next in pipeline” for city status, we also map out the distribution of Zhens. Again, regions in East and Central China (e.g., Shandong and Henan) feature predominantly, revealing the potential for future urban expansion.

As city status often translates into real urban growth, we conjecture that the uneven geography of mushrooming Jiedaos would entrench the already huge East-West divide in China.

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Wu et al 2015 EPA_Jiedaos.pdf
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