本文从结构维、形态维、密度维、效率维构建了多维度城市蔓延测度指标体系,并基于地图可视化、标准差椭圆和冷热点分析探究中国2005~2020年城市综合蔓延度的时空特征及迁移演化格局,并采用时空地理加权模型(GTWR)实证考察多维度城市蔓延对碳排放强度影响的时空异质性.结果表明:(1)全国城市综合蔓延度呈现“东高西低”的空间差异特征,但在样本后期东部沿海地区及东北地区的城市蔓延度有所下滑.标准差椭圆呈现向心集聚的趋势,且分布重心整体向西南移动.冷热点分析则呈现“东热西冷”的区域性差异.(2)城市总蔓延度对碳排放具有显著影响,且随时间迁移在越来越多的城市中起到正向促进作用.正向促进作用区域主要集中在中西部及沿海地区,反向抑制作用区域多为华北平原和南部沿海地区.(3)各维度影响因素存在明显的时空异质性,时间趋势上,结构维在大部分城市促进碳排放,且影响力逐年增强;形态维在大部分城市对碳排放由促进作用转变为抑制作用;密度维、效率维在大部分城市抑制碳排放,但密度维逐年呈现出两极分化的趋势,效率维的影响力则整体减弱.空间分布上,结构维、密度维在东南沿海、西部和东北地区的影响力更强,形态维作用显著区域在东北地区和中西部地区,效率维作用显著区域则在中西部.
Abstract
This article constructed a multidimensional urban sprawl measurement index system from the structural dimension, morphological dimension, density dimension, and efficiency dimension. Based on map visualization, standard deviation ellipse, and cold and hot spot analysis, it explored the spatiotemporal characteristics and migration evolution patterns of China's urban comprehensive sprawl from 2005 to 2020. The spatiotemporal geographically weighted model (GTWR) was used to empirically examine the spatiotemporal heterogeneity of the impact of multidimensional urban sprawl on carbon emission intensity. Research shows that: (1) The comprehensive urban sprawl in China exhibited a spatial difference of "high in the east and low in the west", but the urban sprawl in the eastern coastal and northeastern regions has declined in the later stage of the sample. The standard deviation ellipse shows a trend of centripetal clustering, and the center of gravity of the distribution shifts towards the southwest as a whole. The analysis of hot and cold spots presents regional differences of "hot in the east and cold in the west". (2) The overall urban sprawl has a significant impact on carbon emissions, and over time, it plays a positive promoting role in an increasing number of cities. The positive promotion area is mainly concentrated in the central and western regions and coastal areas, while the negative inhibition area is mainly the North China Plain and the Pearl River Delta. (3) There is significant spatiotemporal heterogeneity in the influencing factors of each dimension. In terms of temporal trends, the structural dimension promotes carbon emissions in most cities and its influence increases year by year; The form dimension has shifted from a promoting effect to a inhibiting effect on carbon emissions in most cities; The density dimension and efficiency dimension suppress carbon emissions in most cities, but the density dimension shows a polarization trend year by year, while the influence of the efficiency dimension weakens overall. In terms of spatial distribution, the influence of structural dimension and density dimension is stronger in the southeastern, western, and northeastern regions, while the significant effect of morphological dimension is in the northeastern border and central western regions, and the significant effect of efficiency dimension is in the central and western regions.
关键词
GTWR模型 /
多维度城市蔓延 /
时空异质性 /
碳排放
Key words
carbon emissions /
GTWR model /
multidimensional urban sprawl /
spatiotemporal heterogeneity
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基金
国家自然科学基金青年基金资助项目(52208073);国家重点研发计划项目(2023YFC3807701)
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