基于POI数据的城市场景细粒度制图

doi:10.11896/jsjkx.210800274

摘要/Abstract

摘要： “场景”是城市文化、意义、情感等的外化符号,是一个超越城市物理空间的概念。知识经济时代背景下,城市场景描述了由不同舒适物组合所产生的蕴含文化、价值观和生活方式的抽象概念,是吸引高级人力资本聚集的内生动力。因此,准确把握城市场景的状态和空间分布是城市发展的一个重要维度。目前,一些研究基于官方商业编码或大众点评等数据开展了基于城市或区域尺度的城市场景制图。文中利用大数据方法,基于POI数据构建了用于城市场景细粒度制图的方法框架,并衡量了深圳城市场景的细粒度分布状态。结果显示,深圳的主要场景特征为企业、正式、爱炫、时尚和逾越;同时,深圳主要呈现出3种场景模式,分别主要来自工作、居住和创意娱乐空间。总体而言,所提方法框架能有效地探测细粒度的城市场景,有利于深刻理解和准确识别城市场景,并为城市发展带来启发。

关键词: POI, 场景, 舒适物, 制图

Abstract: As a symbol of urban culture, meaning and emotion, “scene” is a concept beyond the physical space.In the context of the knowledge economy, urban scene is an abstract concept describing culture, values and lifestyle generated by the combination of amenities.It is regarded to attract high-quality human capital and thus is the endogenous driving force of the economy and urban development.Therefore, accurately grasping the state and spatial distribution of urban scenes is an essential dimension of urban development.Several studies have mapped urban scenes based on the scale of the whole city or region, such as ZIP code tabulation area via official commercial codes or Dianping data.This study attempts to propose a methodological framework to achieve fine-grained mapping of urban scenes based on POI data and statistical methods.Scenes in Shenzhen are estimated, and the results show that the main scenes of Shenzhen are corporate, formality, exhibitionism, fashion and transgression.Moreover, three scenes patterns are presented, which may come from work, residential and creative entertainment spaces, respectively.In general, a practical methodological framework is proposed to map finer-grained scenes in cities, which is conducive to a more profound understanding and accurate identification of urban scenes and brings inspiration for urban development.

Key words: Amenities, Mapping, POI, Scenes

中图分类号:

TP302.4

曾进, 鲁永刚, 乐阳. 基于POI数据的城市场景细粒度制图[J]. 计算机科学, 2022, 49(4): 9-15. https://doi.org/10.11896/jsjkx.210800274

ZENG Jin, LU Yong-gang, YUE Yang. Finer-grained Mapping for Urban Scenes Based on POI[J]. Computer Science, 2022, 49(4): 9-15. https://doi.org/10.11896/jsjkx.210800274

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