城市郊区空间边缘性感知中的陈旧观念

A.D. Chistova
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引用次数: 0

摘要

根据俄罗斯的领土和区域发展政策,通过分级管理制度的棱镜对国家空间进行了严格的结构划分。因此,整个国家的空间结构是通过边界系统固定下来的,其标志突出了国家级管理对象、俄罗斯联邦主体、领土、地区、区。本文将介绍影响对边缘化性质的新领土的认识的主要定型观念。众所周知,边缘社区的形成可追溯到整个文明史。必须将地理边缘性与空间边缘性区分开来。在地理学中,有 "边缘领地 "的概念,可以认为是那些位于偏远地区边缘或与世隔绝的地方。空间边缘化现象的特点正是社会上对某一特定地区的普遍成见。城市空间感知对人类行为和情感反应有着至关重要的影响,强调城市空间必须符合人类需求,以提高城市生活质量。然而,根据功能性对城市建筑进行分类,会因客观表述与主观感知之间的差异而产生偏差。这些偏差可能导致城市规划和设计无法充分满足城市居民的需求和偏好,从而对他们的生活质量和城市的整体功能产生负面影响。在本研究中,我们运用机器学习,通过客观绘图、主观感知分析和感知偏差评估三步方法,揭示了城市空间感知研究中的这些偏差。我们的研究结果表明,机器学习可以揭示这一研究领域中隐藏的模式,对城市规划和设计具有重要意义。特别值得注意的是,研究发现商业建筑与住宅或公共建筑的分布中心点存在显著差异。这一结果揭示了城市建筑功能的空间组织特征,对城市规划和发展具有重要指导意义。此外,它还揭示了不同数据来源和方法在解释城市空间感知方面的优缺点,为更全面地理解这一主题铺平了道路。这些结果凸显了在对城市建筑功能进行分类时,将客观绘图和主观视角相结合的重要性。
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Stereotypical ideas in the perception of spatial marginality of urban outskirts
According to the territorial-regional development policy of Russia, a rigid structuring of the country's space is applied through the prism of a hierarchical management system. As a result, the structure of the space of the entire country was fixed through a system of boundaries, the markers of which highlight management objects at the national level, subject of the Russian Federation, territory, region, district. This article will present the main stereotypes that influence the creation of the perception of new territories in the nature of marginality. As is known, the formation of marginal communities can be traced throughout the history of civilizations. It is important to separate geographical marginality from spatial marginality. In geography, there is the concept of “marginal territories”, which can be considered those located on the remote periphery of the region or in isolated places. Such a phenomenon as spatial marginality is characterized precisely by the prevailing stereotypes in society about a specific area. Urban spatial perception critically influences human behavior and emotional responses, emphasizing the need to align urban spaces with human needs to improve the quality of urban life. However, the classification of urban architecture based on functionality is subject to biases stemming from discrepancies between objective representation and subjective perception. These biases can lead to city planning and designs that fail to adequately meet the needs and preferences of city residents, negatively impacting their quality of life and the overall functionality of the city. In this study, we apply machine learning to uncover these biases in urban spatial perception research using a three-step methodology: objective mapping, subjective perception analysis, and perceptual bias assessment. Our results show that machine learning can reveal hidden patterns in this area of research with significant implications for urban planning and design. Of particular note, the study found significant discrepancies in the distribution centroids between commercial buildings and residential or public buildings. This result sheds light on the spatial organization characteristics of urban architectural functions, serving as a valuable guide for urban planning and development. Moreover, it reveals the advantages and disadvantages of different data sources and methods for interpreting urban spatial perception, paving the way to a more complete understanding of the subject. These results highlight the importance of integrating both objective mapping and subjective perspectives when classifying the functionality of urban architecture.
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