Projecting population distribution under depopulation conditions in Japan: scenario analysis for future socio-ecological systems

Projecting population distribution under depopulation conditions in Japan: scenario analysis for future socio-ecological systems
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DOI:
10.1007/s11625-020-00835-5
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发表时间:
2020-08-06
影响因子:
6
通讯作者:
Takeuchi, Kazuhiko
Takeuchi, Kazuhiko
中科院分区:
环境科学与生态学2区
文献类型:
--
作者:
Hori, Keiko;Saito, Osamu;Takeuchi, Kazuhiko

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本研究根据日本目前的人口减少趋势,开发了未来人口分布的预测模型,并将该模型应用于假设人口密集和分散的情景分析。该模型能够在两个层面上描述人口迁移。首先,使用群分量法预测城市人口,其次,使用重力模型以500 m网格分辨率预测城市内人口的空间分布。根据日本的人口减少背景和国家空间战略,紧凑的情景预测形成中等规模的区域城市地区(位于日本各地的人口中心)和人口集中在城市内的高密度人口地区。与此同时,分散情景预测形成更多但更小的区域城市地区和人口分散到低密度地区。2050年的模拟人口分布显示了人口密度和年龄结构的空间变化,以及2015年有人居住但到2050年将成为零人口地区的大量地区。对未来土地利用图和模拟人口分布图的叠加分析有助于确定应管理农田和森林种植园等自然资本但到2050年将出现重大人口损失的地区。
This study develops a projection model of future population distribution on the basis of Japan's current depopulation trend and applies this model to scenario analyses that assume population compactification and dispersion. The model enables a description of population migration at two levels. First, municipal populations are projected using the cohort-component method, and second, the spatial distribution of populations within municipalities is projected at a 500 m grid resolution with the use of the gravity model. Based on the Japanese depopulation context and the country's National Spatial Strategy, the compact scenario predicts the formation of medium-scale regional urban areas (population centers located across Japan) and the concentration of people on high-density population areas within municipalities. Meanwhile, the dispersed scenario predicts the formation of more but smaller regional urban areas and the dispersion of the population to low-density areas. The simulated population distribution for 2050 reveals spatial change in population density and age structure, as well as an abundance of areas that were inhabited in 2015 but will be zero population areas by 2050. Overlay analysis of future land use maps and the simulated population distribution maps can contribute toward identifying areas where natural capital such as farmland and forest plantation should be managed but where there will be significant population loss by 2050.