Updating global urbanization projections under the Shared Socioeconomic Pathways

被引：42

作者：

Chen, Shiyin ^{[1
]}

Huang, Qingxu ^{[1
,2
]}

Muttarak, Raya ^{[3
,4
,5
]}

Fang, Jiayi ^{[6
]}

Liu, Tao ^{[7
]}

He, Chunyang ^{[1
,2
]}

Liu, Ziwen ^{[1
,2
]}

Zhu, Lei ^{[8
]}

机构：

[1] Beijing Normal Univ, State Key Lab Earth Surface Proc & Resource Ecol, Beijing 100875, Peoples R China

[2] Beijing Normal Univ, Sch Nat Resources, Fac Geog Sci, Beijing 100875, Peoples R China

[3] Int Inst Appl Syst Anal IIASA, Laxenburg, Austria

[4] Univ Vienna, Wittgenstein Ctr Demog & Global Human Capital IIA, OeAW, Vienna, Austria

[5] Univ Bologna, Dept Stat Sci, Bologna, Italy

[6] East China Normal Univ, Sch Geog Sci, Key Lab Geog Informat Sci, Minist Educ, Shanghai 200241, Peoples R China

[7] Peking Univ, Coll Urban & Environm Sci, Beijing, Peoples R China

[8] Tsinghua Univ, Dept Earth Syst Sci, Minist Educ, Key Lab Earth Syst Modeling, Beijing 100084, Peoples R China

来源：

SCIENTIFIC DATA | 2022年 / 9卷 / 01期

基金：

国家重点研发计划; 中国国家自然科学基金;

关键词：

BIODIVERSITY; GROWTH;

D O I：

10.1038/s41597-022-01209-5

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

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.

引用

页数：10

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