城市收缩的时空格局与影响因素：德国东部地区与中国东北地区的对比研究

doi:10.3969/j.issn.1004-9479.2024.08.20222417

摘要/Abstract

摘要：

随着城市收缩研究的深入，从城市实体地域尺度出发进行国家区域间的精准识别和影响因素对比分析，对减少基于行政地域识别的误差和借鉴国外成功经验具有重要意义。研究通过构建VANUI指数、计算夜间灯光DN值和WorldPop人口栅格数据的一元线性回归系数，对“夜间灯光DN值回归系数≥0或＜0，WorldPop人口栅格数据回归系数≥0或＜0”进行两两叠加，将德国东部地区和中国东北地区2000—2009年和2010—2018年两阶段的城市实体地域划分为绝对增长型、精明收缩型、消极增长型和绝对收缩型四类。基于分类结果，对比了两地区两阶段绝对收缩型和精明收缩型区域的时空分布和转变路径，并从人口增长、科技发展水平、医疗服务水平等方面构建面板回归模型对两地区两阶段城市收缩的影响因素进行了分析。结果表明：两地区绝对收缩型区域在时空分布和转变路径上具有较大的相似性；精明收缩型区域在时空分布上具有相似性，但在转变路径上具有差异性；两地区两阶段绝对收缩型区域均占比较少；两地区人口增长机制兼具异同点，并由于国情差异而具有不同内涵。总的来说，城市收缩区域具有短期内实现增长的可能性；应当给予重点关注和治理的是绝对收缩型区域，而精明收缩型区域应被视作城市收缩区域的良性发展模式；持续提升医疗养老服务水平和科研投入，稳步推进存量区域的人居环境改造和基础设施配套，合理管控增量开发，有助于缓解城市收缩现象。

关键词: 城市收缩, 人口, 德国东部地区, 中国东北地区, 城市实体地域

Abstract:

It is of great significance to carry out accurate identification of urban shrinkage and comparative analysis of its influencing factors in large national regions, to reduce the error based on administrative area identification. By constructing the VANUI index, calculating the one-dimensional linear regression coefficient of the DN value of night light and the WorldPop population grid data, and based on the overlay of the regression coefficient of the DN value of night light, and the regression coefficient of the WorldPop population grid data, the urban areas of East Germany and Northeast China in the two stages of 2000-2009 and 2010-2018 were divided into four types: absolute growth, smart shrinkage, negative growth and absolute shrinkage. This paper then studied and compared the spatio-temporal distribution and transformation path of the two stages of absolute shrinkage and smart shrinkage in the two regions, and constructed a panel regression model from population growth, scientific and technological development level, medical service level and other aspects to conduct a comparative analysis of the influencing factors of the two stages of urban shrinkage in the two regions. The results show that the absolute shrinkage areas in the two regions have a great similarity in spatiotemporal distribution and transformation path; the smart shrinkage areas are similar in spatiotemporal distribution, but different in transformation path; the absolute shrinkage areas in the two regions and two stages is relatively small; the mechanism of population growth in the two regions has both similarities and differences, and has different connotations due to differences in national conditions. This study shows that: (1)Urban shrinkage areas have the potential for short-term growth, and their development rights should be treated equally; (2)The absolute shrinking areas should be given special atten‐tion and governance, while the smart shrinking areas should be regarded as a reasonable development model for urban shrinking areas; (3)Continuously improving the level of medical, elderly care services and research investment, steadily promoting the transformation of living environment and infrastructure in existing areas, and reasonably controlling incremental development can help alleviate the phenomenon of urban shrinkage.

Key words: urban shrinkage, population, East Germany, Northeast China, urban area

梁源钊, 魏冶. 城市收缩的时空格局与影响因素：德国东部地区与中国东北地区的对比研究[J]. 世界地理研究, 2024, 33(8): 40-51.

Yuanzhao LIANG, Ye WEI. The spatiotemporal pattern and influencing factors of urban shrinkage: A comparative study of East Germany and Northeast China[J]. World Regional Studies, 2024, 33(8): 40-51.

图/表 8

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时段	类型	德国东部		中国东北
时段	类型	栅格数	占比/%	栅格数	占比/%
2000—2009年	消极增长型	154	7.91	217	3.20
	精明收缩型	962	49.44	2 636	38.40
	绝对收缩型	186	9.56	92	1.30
	绝对增长型	644	33.09	3 926	57.10
2010—2018年	消极增长型	103	2.03	486	5.70
	精明收缩型	2 084	41.02	3 084	36.20
	绝对收缩型	110	2.17	429	5.00
	绝对增长型	2 783	54.78	4 529	53.10

时段	类型	德国东部		中国东北
时段	类型	栅格数	占比/%	栅格数	占比/%
2000—2009年	消极增长型	154	7.91	217	3.20
	精明收缩型	962	49.44	2 636	38.40
	绝对收缩型	186	9.56	92	1.30
	绝对增长型	644	33.09	3 926	57.10
2010—2018年	消极增长型	103	2.03	486	5.70
	精明收缩型	2 084	41.02	3 084	36.20
	绝对收缩型	110	2.17	429	5.00
	绝对增长型	2 783	54.78	4 529	53.10

项	FE模型（2001—2009年）	双向固定效应模型（2001—2009年）	FE模型（2010—2017年）	双向固定效应模型（2010—2017年）
截距	0.403^**(18.119)	0.445^**(14.203)	0.281^**(12.760)	0.133(1.679)
人口机械迁移量/人	0.008(0.880)	－0.008(－0.797)	0.004(0.200)	－0.011(－0.837)
人口自然增长量/人	0.041(1.120)	0.057(1.022)	0.056^*(2.600)	0.203^**(3.472)
人口老龄化率/%	－0.141^**(－7.144)	－0.201^**(－3.615)	－0.028(－1.433)	0.098(1.286)
研发支出/百万欧元	－0.055^*(－2.194)	－0.079(－1.605)	0.211^**(4.172)	0.327^**(4.127)
医院数量/间	0.197^**(5.325)	0.175^**(2.756)	0.158^**(2.723)	0.205^**(4.581)
人均住房津贴/欧元	－0.001(－0.067)	0.014(0.957)	0.033(1.333)	－0.055(－1.698)
R ²	0.211	0.093	0.525	0.620
R ²(within)	0.908	0.661	0.625	－2.283
样本量	54	54	48	48
检验	F(6,42)=6.035×10¹⁴, p=0.000	F(6,39)=1.785×10¹⁴, p=0.000	F(6,36)=7.208×10¹⁵,p=0.000	F(6,29)=4.821×10¹⁵, p=0.000

项	FE模型（2001—2009年）	双向固定效应模型（2001—2009年）	FE模型（2010—2017年）	双向固定效应模型（2010—2017年）
截距	0.403^**(18.119)	0.445^**(14.203)	0.281^**(12.760)	0.133(1.679)
人口机械迁移量/人	0.008(0.880)	－0.008(－0.797)	0.004(0.200)	－0.011(－0.837)
人口自然增长量/人	0.041(1.120)	0.057(1.022)	0.056^*(2.600)	0.203^**(3.472)
人口老龄化率/%	－0.141^**(－7.144)	－0.201^**(－3.615)	－0.028(－1.433)	0.098(1.286)
研发支出/百万欧元	－0.055^*(－2.194)	－0.079(－1.605)	0.211^**(4.172)	0.327^**(4.127)
医院数量/间	0.197^**(5.325)	0.175^**(2.756)	0.158^**(2.723)	0.205^**(4.581)
人均住房津贴/欧元	－0.001(－0.067)	0.014(0.957)	0.033(1.333)	－0.055(－1.698)
R ²	0.211	0.093	0.525	0.620
R ²(within)	0.908	0.661	0.625	－2.283
样本量	54	54	48	48
检验	F(6,42)=6.035×10¹⁴, p=0.000	F(6,39)=1.785×10¹⁴, p=0.000	F(6,36)=7.208×10¹⁵,p=0.000	F(6,29)=4.821×10¹⁵, p=0.000

项	RE模型（2000—2009年）	双向固定效应模型（2000—2009年）	RE模型（2010—2017年）	双向固定效应模型（2010—2017年）
截距	0.244^**(8.582)	0.248^**(43.427)	0.227^**(8.073)	0.258^**(36.971)
人口自然增长率/%	0.008^*(2.291)	0.012^*(2.340)	0.010^**(4.992)	0.011^**(3.175)
第二产业产值占比/%	－0.014^*(－2.359)	－0.017^*(－2.368)	0.030^**(6.767)	－0.018(－1.730)
固定资产投资额/万元	0.043^**(6.144)	0.040^**(4.549)	－0.015^**(－4.013)	－0.013^**(－3.538)
科研从业人员数/万人	0.070^**(2.909)	0.055^**(2.884)	0.050^*(2.514)	0.037^**(3.830)
医院卫生院数量/间	0.019(1.872)	0.009(0.884)	0.066^**(3.029)	0.045^*(1.999)
R ²	0.142	0.109	0.161	0.115
R ²(within)	0.548	0.545	0.235	－0.202
样本量	400	400	295	295
检验	χ²(5)=47.496, p=0.000	F(5,346)=7.696, p=0.000	χ²(5)=73.319, p=0.000	F(5,245)=5.366, p=0.000