摘要
基于对郑州市城市体检多源异构大数据的融合,以郑州市主城区为研究单元,通过构建多尺度统计模型、非补偿性聚合等方法对城市内部社区、街道尺度的居民主、客观福祉匹配性及空间差异特征进行分析。结果表明:在城市内部空间尺度,居民的主、客观福祉测度结果具有显著的地理匹配性,匹配程度由城市中心向郊区逐渐降低。在街道尺度,不同街道的居民主、客观福祉匹配性表现出明显的空间分异特征,位于城市中心和东部的街道居民主观幸福感和客观生活质量水平匹配性高于其他街道。
Based on the fusion of multi-source heterogeneous data from the Zhengzhou City health check,utilizing the main urban area of Zhengzhou City as the research unit.The aim of the study is to analyze the spatial differences in residents’subjective and objective well-being matching at the intra-city community and street scales,employing the construction of multilevel statistical models and non-compensatory aggregation.The results indicate that at the spatial scale of the inner city,residents’subjective and objective well-being measures have a significant geographical match,with a gradual decline in the degree of match from the city center to the suburbs.Additionally,at the street scale,there are notable spatial disparities in the match between subjective and objective well-being in each street,with the match between subjective well-being and objective quality of life in the streets located in the city center and the eastern part of the city being higher than that in other streets.This study highlights the importance of considering multiple sources of data and spatial scales when analyzing well-being and suggests the need for targeted policies and interventions to improve well-being in areas with lower subjective and objective well-being matches.
作者
张志鹏
董冠鹏
王相彪
郭雨臣
ZHANG Zhipeng;DONG Guanpeng;WANG Xiangbiao;GUO Yuchen(Key Research Institute of Yellow River Civilization and Sustainable Development&Collaborative Innovation Center on Yellow River Civilization Jointly Built by Henan Province and Ministry of Education,Ministry of Education,Henan University,Kaifeng 475004,China;Key Laboratory of Geospatial Technology for Middle and Lower YellowRiver Regions,Ministry of Education,Henan University,Kaifeng 475004,China)
出处
《地域研究与开发》
北大核心
2024年第3期83-89,96,共8页
Areal Research and Development
基金
国家自然科学基金项目(42001115)。