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辽中南城市群城市用地结构的时空演变分析 被引量:21

Study on Evolution of Urban Land Structure in Liaozhongnan City Groups
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摘要 辽中南城市群作为国家增长第四级重要引擎,在振兴东北老工业基地政策影响下,探究其用地结构时空演变规律是调整用地结构的前提。文章基于辽中南城市群2006-2014年城市用地结构数据,运用信息熵和偏移份额模型分析用地结构的时空变化特征、地类演变规律及空间配置差异。结果表明:①2006-2014年城市群用地结构信息熵与均衡度经历了“无序-有序-相对平稳”的演变。②居住用地、公共设施用地和市政公用设施用地为增长性结构,其中公共设施用地有显著补给效应;工业用地、仓储用地、道路交通用地及绿地为衰减性结构,其中仓储用地和道路交通用地有显著挤出效应。③空间格局上,居住用地、公共设施用地、工业用地、道路交通用地及绿地在各地区分布较为均衡,市政公用设施用地次之,仓储用地分布集中。④各地区对不同类型城市用地的竞争优势具有显著的空间差异,经济越发达地区其竞争优势地类越多。 Liaozhongnan City Groups, as a national level fourth engine, under the policy of revitalizing the northeast old industrial base, it is the premise of adjusting land use structure to explore its temporal and spatial evolution law. Based on urban land use structure data from 2006 to 2014, an information entropy model and shift-share model are used to analyze the temporal spatial variations characteristics, land type evolution and space configuration differences. The result showed that: (1)We found a process of "disorder-order-relatively steady" for the information entropy and equilibrium degree of construction land. (2) Residential land, public facilities land and municipal public facilities land belong to a structure of growth form. Public facilities land showed a significant supply effect. Industrial land, storage land, road traffic land and green land had a structure of damping form. Storage land and road traffic land showed a significant crowding-out effect. (3) From the perspective of spatial allocation, the most balanced lands were residential land, land for public facilities, industrial land, land for transportation system and green land, followed by municipal public facilities land, land for storage was unbalanced. (4)There are significant differences in the competitiveness of different types of urban land in different areas. The more developed areas are, the more competitive advantages structure are.
出处 《经济地理》 CSSCI CSCD 北大核心 2018年第1期69-77,共9页 Economic Geography
基金 国家社会科学基金青年项目(15CGL078)
关键词 城市用地结构 信息熵模型 偏移份额模型 辽中南城市群 urban land structure information entropy model shift-share model Liaozhongnan City Groups
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