城市流动性的双重性作为城市可持续生活空间建设中的异质现象:以巴西坎皮纳格兰德市的贫困推断为例

Claudio Germano dos Santos Oliveira, Isabel Lausanne Fontgalland
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摘要

使用统计和地理参考工具有助于解释在城市中预先存在的城市结构下城市流动性的差异。本研究的对象Campina Grande-PB城市的特点是,人口爆炸和智慧城市概念下城市阶层的新布局等二元因素普遍存在。也就是说,屏幕上的分析包含了现有的移动系统,展示了当前空间如何通过空间句法理论影响不同社会阶层的移动潜力。该研究使用了地理信息系统(gis),通过深度地图®和QGIS处理,结合社会经济变量在社区空间句法测量的生产。本研究得出结论,该方法确定了在中高收入人群高度集中的中心区,一种更有利于汽车使用的形式,而在弱势群体集中度较高的街区,一种有利于步行和自行车、摩托车使用的系统。公共交通系统呈现出更有效的覆盖范围,因为它本身是当地贫困循环原因的限制性因素,尽管它有可能成为当地经济活力的驱动力,有利于在空间上最脆弱和最隔离的地区增加收入。
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The duality of urban mobility as a heterogeneous phenomenon in the construction of sustainable living space in cities: a look at the inference of poverty in the city of Campina Grande, Brazil
The use of statistical and geo-referenced tools helps to explain the differentiation of urban mobility given the pre-existing urban configuration in cities. The city of Campina Grande-PB, object of this study, is characterized by the prevalence of dualist elements such as the growing demographic explosion and the new layout of urban strata in terms of the smart cities concept. That said, the analysis on screen comprises the existing mobility system, demonstrating how the current space influences the potential of movement in different social strata through the Theory of Spatial Syntax. The research used the Geographic Information System-GIS, processed through Depthmap® and QGIS, in the production of spatial syntactic measures in neighborhoods combined with socioeconomic variables. In this study, it was concluded that the method identified in central areas, with a high concentration of middle and high income, a format more conducive to car use, while in neighborhoods with a higher concentration of vulnerable population, a system that favors the walkability and the use of bicycles and motorcycles. The public transport system presented a more efficient coverage, as it presents itself as a restrictive factor in the circular causation of local poverty, although it has the potential to be a driver of local economic dynamism to favor increased income in the most vulnerable and segregated locations spatially.
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