| 1980—2020年粤港澳大湾区城镇用地空间格局类型演变及其驱动力多维探测 |
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| 引用本文： | 鞠洪润,张生瑞,闫逸晨.1980—2020年粤港澳大湾区城镇用地空间格局类型演变及其驱动力多维探测[J].地理学报,2022,77(5):1086-1101. |
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| 作者姓名： | 鞠洪润 张生瑞 闫逸晨 |
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| 作者单位： | 1.青岛大学旅游与地理科学学院,青岛 2660712.中国海洋大学管理学院,青岛 2661003.北京师范大学地理科学学部,北京 100875 |
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| 基金项目： | 国家自然科学基金项目(42001243)；;教育部人文社会科学研究项目(20YJC630212)；;山东省自然科学基金项目(ZR2020QD008)~~； |
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| 摘 要： | 深入研究1978年改革开放以来粤港澳大湾区城镇用地空间格局类型,探索土地城镇化多维和交互驱动机制,对推进粤港澳大湾区建设,打造世界级城市群具有重要意义。本文基于模糊聚类,从规模、形态和分布3个维度划分和定义粤港澳大湾区城镇用地空间格局类型,利用地理探测器测度城镇用地空间格局多维变化驱动力及其交互作用。结果表明：① 粤港澳大湾区城镇用地空间格局类型包括分形/复杂大面积型、分形小面积型、复杂小面积型、简单小面积型和散布型5种类型,城镇用地规模和形状复杂性具有一定的正相关性,2010年后用地规模趋于稳定,形态的规则性和紧凑性得到优化,分布集中。② 人口、GDP、地方财政收入、固定资产投资额和路网密度等社会经济因素对城镇用地面积和形态变化影响显著,核心城市对城市群发展的牵引作用在2000年后得以显现。2010—2020年各影响因子对城镇用地面积、分布和类型变化的作用差异有所减弱,但社会经济因素对形状特征的影响力上升。③ 城镇用地面积特征变化的影响力交互作用最为多样,表现有非线性增强、协同增强、单因子减弱和非线性减弱4种类型;对形状、分布和空间格局类型变化的影响力交互作用主要表现为协同增强和非线性增强。核心城市牵引力、路网密度、河网密度与多数因子交互产生“1+1>2”的效果,反映出城市群核心区位、交通优势对城镇用地扩展的强烈推动作用。
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| 关 键 词： | 城镇用地 空间格局类型 多维驱动力 交互作用 粤港澳大湾区 |
| 收稿时间： | 2021-01-06 |
| 修稿时间： | 2022-03-21 |
Spatial pattern changes of urban expansion and multi-dimensional analysis of driving forces in the Guangdong-Hong Kong-Macao Greater Bay Area in 1980-2020 |
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| JU Hongrun,ZHANG Shengrui,YAN Yichen.Spatial pattern changes of urban expansion and multi-dimensional analysis of driving forces in the Guangdong-Hong Kong-Macao Greater Bay Area in 1980-2020[J].Acta Geographica Sinica,2022,77(5):1086-1101. |
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| Authors: | JU Hongrun ZHANG Shengrui YAN Yichen |
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| Institution: | 1. School of Tourism and Geography Science, Qingdao University, Qingdao 266071, Shandong, China2. Management College, Ocean University of China, Qingdao 266100, Shandong, China3. Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China |
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| Abstract: | Exploring the types of spatial patterns of urban land use in the Guangdong, Hong Kong and Macao since the reform and opening up in the late 1970s, and the multi-dimensional and interactive driving mechanism for the evolution of urban land spatial pattern, is important for promoting the construction of the Guangdong-Hong Kong-Macao Greater Bay Area, and building a world-class bay area and urban agglomeration. This study divided and defined the evolution of urban land patterns types in the Greater Bay Area from the perspectives of area, shape and distribution characteristics based on fuzzy clustering. Using geographic detectors, this study measured the multi-dimensional driving forces and interactions of urban land use changes in the study area. The results showed that: (1) In terms of spatial pattern, there are five types of urban land use: fractal/complex large area, fractal small area, complex small area, simple small area and scattered area. The area scale and shape complexity of urban land had a certain positive correlation. (2) Socio-economic factors such as population, GDP, local fiscal revenue, fixed asset investment, and road network density had significant impacts on urban land area and morphological changes. The impacts of core cities on the development of urban agglomerations became apparent after 2000. In the later stage of the research, the differences among the effects of various influencing factors on the changes in the area, distribution and spatial pattern types of urban land use tended to be weakened, but the influences of social and economic factors on the shape characteristics increased. (3) The interactions of influence on the change of urban land area characteristics were the most complex, with four types of nonlinear enhancement, synergy enhancement, single factor weakening and nonlinear weakening; the interactions of influence on shape, distribution and spatial pattern changes were mainly manifested as synergistic enhancement and non-linear enhancement. Interactions between core city traction, road network density, river network density and most factors produced a "1+1 > 2" effect, reflecting the strong promotion effects by the core cities of urban agglomerations and transportation advantages. |
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| Keywords: | urban land use spatial pattern type multi-dimensional driving forces interactive mechanism Guangdong-Hong Kong-Macao Greater Bay Area |
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