State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, 100875, China.
School of Natural Resources, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China.
Sci Data. 2022 Mar 31;9(1):137. doi: 10.1038/s41597-022-01209-5.
Urbanization level is an important indicator of socioeconomic development, and projecting its dynamics is fundamental for studies related to global socioeconomic and climate change. This paper aims to update the projections of global urbanization from 2015 to 2100 under the Shared Socioeconomic Pathways by using the logistic fitting model and iteratively identifying reference countries. Based on historical urbanization level database from the World Urbanization Prospects, projected urbanization levels and uncertainties are provided for 204 countries and areas every five years. The 2010-2100 year-by-year projected urbanization levels and uncertainties based on the annual historical data from the World Bank (WB) for 188 of countries and areas are also provided. The projections based on the two datasets were compared and the latter were validated using the historical values of the WB for the years 2010-2018. The updated dataset of urbanization level is relevant for understanding future socioeconomic development, its implications for climate change and policy planning.
城市化水平是社会经济发展的重要指标，预测其动态变化对于研究全球社会经济和气候变化至关重要。本文旨在利用逻辑斯蒂拟合模型和迭代识别参照国，根据《世界城市化展望》中的历史城市化水平数据库，更新 2015 年至 2100 年全球城市化的预测结果。为 204 个国家和地区提供每五年一次的城市化水平预测值和不确定性。根据世界银行（WB）188 个国家和地区的年度历史数据，还提供了基于逐年历史数据的 2010-2100 年的城市化水平预测值和不确定性。比较了基于这两个数据集的预测结果，并使用 WB 2010-2018 年的历史值对后者进行了验证。更新后的城市化水平数据集有助于了解未来的社会经济发展及其对气候变化和政策规划的影响。
