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基于RAGA-PPM模型的城市活力评价方法研究——以南京市中心城区为例

A Method for Evaluating Urban Vitality Using the RAGA-PPM Model:A Case Study of Central Nanjing

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【作者】 余蕾盛业华刘星雨

【Author】 YU Lei;SHENG Yehua;LIU Xingyu;The Ministry of Education Key Laboratory of Virtual Geographic Environment (Nanjing Normal University);Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application;

【通讯作者】 盛业华;

【机构】 南京师范大学虚拟地理环境教育部重点实验室江苏省地理信息资源开发与利用协同创新中心

【摘要】 城市活力是提高和维持城市竞争力和生命力的关键。随着城市化进程的发展,城市治理的难度越来越大,亟待城市规划和管理者对城市提出更合理且更精准的措施。本研究以南京市中心城区为研究区,基于基础路网和建筑数据、百度热力图数据、餐饮店铺数据、社交媒体签到数据、POI数据和创新源数据等多源地理大数据,分别从人群活动、网络互动和建成环境3个层面入手,构建一种深入且细致的城市综合活力评估框架。结合基于实数编码的加速遗传算法优化的投影寻踪模型(RAGA-PPM),对9个城市活力影响因子进行降维得到各因子对综合活力的贡献值,最后分析南京市单维活力和综合活力的空间分布格局,并与熵权法(EWM)计算的活力结果进行差异对比。研究结果表明:从活力产生的角度,整合人群活动、网络互动、物理建设3个维度的城市活力新框架得到的城市综合活力结果,能够更加精准地识别研究区的潜在活力极,通过对活力团样本区域分析,验证了本文提出的城市综合活力评估框架的有效性;南京市单维活力呈现出相似的空间特征,与综合活力一样都呈现出单中心的城市结构,高值区从新街口商圈往外围逐渐递减,且RAGA-PPM方法比EWM识别活力结果的更符合实际。本研究可以为城市设计者提供更加全面且多维的城市活力模式提供借鉴依据。

【Abstract】 Enhancing and sustaining urban competitiveness is contingent upon the presence of urban vitality.Urban planners and managers face increasing pressure to find more accurate and logical ways to manage urban development due to the growing challenges associated with municipal government. This study focuses on the central region of Nanjing. A detailed framework for evaluating urban vitality is proposed from three perspectives,human activities, network interactions, and the physical environment. This framework uses foundational road networks and building footprints from the World Map, Baidu heatmap, Dianping restaurant data, social media check-in data, Baidu Map POI, and innovation data. To create a comprehensive vitality evaluation framework,nine urban vitality indicators were reduced in dimensionality using the real-coded accelerated genetic algorithm based on the Projection Pursuit Model(RAGA-PPM). An analysis was also conducted on the differences with EWM and the spatial distribution patterns of both unidimensional and comprehensive vitality in Nanjing. The conclusions can be divided into three parts. First, the spatial distribution pattern of vitality in Nanjing’s central urban area is successfully reflected by the comprehensive evaluation technique based on multi-source big data.The validity of the proposed evaluation system was confirmed by analyzing vitality cluster sample locations.Second, similar spatial features may be seen in Nanjing’s unidimensional vitality, revealing a monocentric urban structure, with high-value areas gradually decreasing outward from the Xinjiekou commercial district. Commercial districts and metro stations are the focal points of population activity vitality, with each district exhibiting strong central values and secondary vitality clusters. Urban vitality values decline, with the Xinjiekou commercial area and Nanjing South Station serving as hubs of network interaction vitality. Urban vitality ratings decrease concentrically, with the Xinjiekou commercial area and Nanjing South Station serving as the hubs of network interaction vitality. Physical building vitality is geographically scattered, with high and relatively high values spread across most areas. Third, unidimensional vitality is not unfamiliar to comprehensive vitality. Additional viable centers for vitality were identified, with each district having a vitality hub. Xuanwu, Gulou, Jianye, and Qinhuai districts, which comprise the old city, form the core of Nanjing’s vibrancy and serve as significant hubs.Liuhe and Yuhuatai districts have the lowest vitality, while Xuanwu and Qinhuai districts show the highest vitality. Most districts with above-average comprehensive vitality scores are located near transportation hubs,university areas, industrial parks, pedestrian streets, and commercial centers. According to the study, urban designers may benefit from a more thorough and multifaceted understanding of urban vitality patterns.

【基金】 国家自然科学基金项目(42471463)~~
  • 【文献出处】 地球信息科学学报 ,Journal of Geo-information Science , 编辑部邮箱 ,2024年11期
  • 【分类号】TU984.113
  • 【下载频次】469
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