Hybrid gridded demographic data for China, 1979-2100

中国 气候学 地理 环境科学 气象学 地质学 考古
作者
Zhao Liu,Si Gao,Yidan Chen,Wenjia Cai
出处
期刊:CERN European Organization for Nuclear Research - Zenodo 被引量:1
标识
DOI:10.5281/zenodo.4554571
摘要

This is a hybrid gridded dataset of demographic data for China from 1979 to 2100, given as 21 five-year age groups of population divided by gender every year at a 0.5-degree grid resolution. The historical period (1979-2020) part of this dataset combines the NASA SEDAC Gridded Population of the World version 4 (GPWv4, UN WPP-Adjusted Population Count) with gridded population from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP, Histsoc gridded population data). The projection (2010-2100) part of this dataset is resampled directly from Chen et al.’s data published in Scientific Data. This dataset includes 31 provincial administrative districts of China, including 22 provinces, 5 autonomous regions, and 4 municipalities directly under the control of the central government (Taiwan, Hong Kong, and Macao were excluded due to missing data). Method - demographic fractions by age and gender in 1979-2020 Age- and gender-specific demographic data by grid cell for each province in China are derived by combining historical demographic data in 1979-2020 with the national population census data provided by the National Statistics Bureau of China. To combine the national population census data with the historical demographics, we constructed the provincial fractions of demographic in each age groups and each gender according to the fourth, fifth and sixth national population census, which cover the year of 1979-1990, 1991-2000 and 2001-2020, respectively. The provincial fractions can be computed as: \(\begin{align*} \begin{split} f_{year,province,age,gender}= \left \{ \begin{array}{lr} POP_{1990,province,age,gender}^{4^{th}census}/POP_{1990,province}^{4^{th}census} & 1979\le\mathrm{year}\le1990\\ POP_{2000,province,age,gender}^{5^{th}census}/POP_{2000,province}^{5^{th}census} & 1991\le\mathrm{year}\le2000\\ POP_{2010,province,age,gender}^{6^{th}census}/POP_{2010,province}^{6^{th}census}, & 2001\le\mathrm{year}\le2020 \end{array} \right. \end{split} \end{align*}\) Where: - \( f_{\mathrm{year,province,age,gender}}\)is the fraction of population for a given age, a given gender in each province from the national census from 1979-2020. - \(\mathrm{PO}\mathrm{P}_{\mathrm{year,province,age,gender}}^{X^{\mathrm{th}}\mathrm{census} }\) is the total population for a given age, a given gender in each province from the Xth national census. - \(\mathrm{PO}\mathrm{P}_{\mathrm{year,province}}^{X^{\mathrm{th}}\mathrm{census} }\) is the total population for all ages and both genders in each province from the Xth national census. Method - demographic totals by age and gender in 1979-2020 The yearly grid population for 1979-1999 are from ISIMIP Histsoc gridded population data, and for 2000-2020 are from the GPWv4 demographic data adjusted by the UN WPP (UN WPP-Adjusted Population Count, v4.11, https://beta.sedac.ciesin.columbia.edu/data/set/gpw-v4-population-count-adjusted-to-2015-unwpp-country-totals-rev11), which combines the spatial distribution of demographics from GPWv4 with the temporal trends from the UN WPP to improve accuracy. These two gridded time series are simply joined at the cut-over date to give a single dataset - historical demographic data covering 1979-2020. Next, historical demographic data are mapped onto the grid scale to obtain provincial data by using gridded provincial code lookup data and name lookup table. The age- and gender-specific fraction were multiplied by the historical demographic data at the provincial level to obtain the total population by age and gender for per grid cell for china in 1979-2020. Method - demographic totals and fractions by age and gender in 2010-2100 The grid population count data in 2010-2100 under different shared socioeconomic pathway (SSP) scenarios are drawn from Chen et al. published in Scientific Data with a resolution of 1km (~ 0.008333 degree). We resampled the data to 0.5 degree by aggregating the population count together to obtain the future population data per cell. This previously published dataset also provided age- and gender-specific population of each provinces, so we calculated the fraction of each age and gender group at provincial level. Then, we multiply the fractions with grid population count to get the total population per age group per cell for each gender. Note that the projected population data from Chen’s dataset covers 2010-2020, while the historical population in our dataset also covers 2010-2020. The two datasets of that same period may vary because the original population data come from different sources and are calculated based on different methods. Disclaimer This dataset is a hybrid of different datasets with independent methodologies. Spatial or temporal consistency across dataset boundaries cannot be guaranteed.

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
大湖玩家完成签到,获得积分10
1秒前
1秒前
hj完成签到,获得积分10
1秒前
1秒前
酷波er应助Time采纳,获得10
2秒前
nora应助跳跃的翼采纳,获得20
3秒前
完美世界应助Zxc采纳,获得10
3秒前
王哈哈完成签到,获得积分10
3秒前
田様应助可靠的紫雪采纳,获得10
4秒前
天明发布了新的文献求助10
4秒前
浮游应助科研通管家采纳,获得10
4秒前
加缪应助科研通管家采纳,获得100
5秒前
Jasper应助科研通管家采纳,获得10
5秒前
浮游应助科研通管家采纳,获得10
5秒前
上官若男应助科研通管家采纳,获得30
5秒前
浮游应助科研通管家采纳,获得10
5秒前
laber应助科研通管家采纳,获得50
5秒前
6秒前
Akim应助科研通管家采纳,获得10
6秒前
zhaojiantgu发布了新的文献求助10
6秒前
加缪应助科研通管家采纳,获得100
6秒前
今后应助科研通管家采纳,获得10
6秒前
小马甲应助科研通管家采纳,获得10
6秒前
小二郎应助科研通管家采纳,获得10
6秒前
科研通AI5应助科研通管家采纳,获得10
6秒前
科研通AI6应助科研通管家采纳,获得150
6秒前
大模型应助科研通管家采纳,获得10
6秒前
aa应助科研通管家采纳,获得30
6秒前
6秒前
6秒前
6秒前
7秒前
佟杰发布了新的文献求助20
7秒前
量子星尘发布了新的文献求助150
8秒前
LIUUU完成签到,获得积分10
9秒前
9秒前
xzs完成签到,获得积分10
9秒前
9秒前
娃娃哈发布了新的文献求助10
10秒前
在水一方应助ningoz采纳,获得10
10秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Acute Mountain Sickness 2000
Handbook of Milkfat Fractionation Technology and Application, by Kerry E. Kaylegian and Robert C. Lindsay, AOCS Press, 1995 1000
A novel angiographic index for predicting the efficacy of drug-coated balloons in small vessels 500
Textbook of Neonatal Resuscitation ® 500
The Affinity Designer Manual - Version 2: A Step-by-Step Beginner's Guide 500
Affinity Designer Essentials: A Complete Guide to Vector Art: Your Ultimate Handbook for High-Quality Vector Graphics 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 内科学 生物化学 物理 计算机科学 纳米技术 遗传学 基因 复合材料 化学工程 物理化学 病理 催化作用 免疫学 量子力学
热门帖子
关注 科研通微信公众号,转发送积分 5070231
求助须知:如何正确求助?哪些是违规求助? 4291424
关于积分的说明 13370277
捐赠科研通 4111739
什么是DOI,文献DOI怎么找? 2251660
邀请新用户注册赠送积分活动 1256787
关于科研通互助平台的介绍 1189405