• •

### 1990~2010年中国人口收缩区分布的时空格局演变 ——基于不同测度指标的分析

1. 1. 中国科学院地理科学与资源研究所/中国科学院区域可持续发展分析与模拟重点实验室,北京100101
2. 中国科学院大学,北京100049
• 收稿日期:2018-03-05 修回日期:2018-09-18 出版日期:2019-10-10 发布日期:2019-10-10
• 通讯作者: 刘盛和 E-mail:liush@igsnrr.ac.cn
• 作者简介:刘振（1990-）,男,山东滨州人,博士,主要从事城市地理和人口地理研究。E-mail:lzhgeog@sina.cn
• 基金资助:
国家自然科学基金项目(41771180);国家自然科学基金项目(71433008)

### Temporal-spatial Pattern of Regional Population Shrinkage in China in 1990-2010: A Multi-indicators Measurement

Liu Zhen1,2, Qi Honggang1,2, Qi Wei1, Liu Shenghe1,2()

1. 1. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences/Key Laboratory of Regional Sustainable Development Modeling, Chinese Academy of Sciences, Beijing 100101, China
2. University of Chinese Academy of Sciences, Beijing 100049, China
• Received:2018-03-05 Revised:2018-09-18 Online:2019-10-10 Published:2019-10-10
• Contact: Liu Shenghe E-mail:liush@igsnrr.ac.cn
• Supported by:
National Natural Science Foundation of China(41771180);National Natural Science Foundation of China(71433008)

Abstract:

Regional population shrinkage is becoming an important issue affecting the sustainable development of regional economy and society in the worldwide, and also arousing increasing attention in China. However, though some related studies in view of population distribution existed, few of them have directly addressed this phenomenon. Against this background, this article aims to investigate regional population shrinkage in China by employing multi-indicators. Specifically, we discussed the existing definitions of population shrinkage, and then based on the spatial population data of 1990, 2000 and 2010 in prefecture-level and county-level, applied both the single indicators, including total population and labor, and the integrated indicator which includes not only total population and labor but also birth rate and aging, to analyze the changes of population shrinking units in number and spatial distribution, and compared the differences in the measurement indicators. The main findings are as follows: 1) Both the single indicators, namely total population and labor, showed that population shrinkage units have increased significantly in number: 27.4% and 38.6% of the units decreased their total population while 21.4% and 25.2% of the units decreased their labor in prefecture-level and county-level from 2000 to 2010, respectively; moreover, many units also show an aggravation trend in the shrinking degree; 2) The population shrinking units have been expanding rapidly in the Central and the Western regions, especially in Sichuan-Chongqing- Guizhou region, the middle reaches of the Yangtze River region and the Northeast region. In contrast, the coastal region has only increased some shrinking units in the northern of Jiangsu Province and the western of Fujian Province; 3) The single indicators were effective in identifying the absolute population shrinkage, and we argued that the total population is more suitable than the labor, because total population shrinking came first in most of the units and then followed by labor shrinking; 4) The integrated indicator was more effective in evaluating the comprehensive status of population development in one region, and then it can identify the units which were relatively shrinking their population, that is, their overall situation is worse than the national average level though they still increased their total population. The results showed that the units with a relative shrinking population have a high proportion, which was about 20% in the county level in both periods, while that type of units in prefecture-level was nearly doubled to about 25% from 1990-2000 to 2000-2010. 5) Regional population shrinkage was more obvious in county-level than in prefecture-level, but the difference has been narrowed, given the fact that the differences in percentages, shrinking degrees, and spatial distributions of the shrinking units were very close in the period from 2000 to 2010. Based on the above findings, this article argues that regional population shrinkage needs further attention by scholars and governments.

• K901.3