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Detecting Urban Dynamics with Taxi Trip Data for Evaluation and Optimizing of Spatial Planning

机译:利用出租车行程数据检测城市动态,以评估和优化空间规划

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Commonly, it is very hard to examine underlying urban dynamics due to rapid spatial expansion and land use variations. In this paper, the origin-destination (OD) data extracted from taxi trip data collected in Xiamen, China, covering 30 days was utilized to detect the underlying dynamics of Xiamen City. Specifically, we discretized the study area into 400m*400m grids so that the number of originating points and destination points of the taxi trips could be counted separately within each single grid. Then, heat maps of the taxi mobility were made to achieve a general understanding of urban dynamics. Secondly, we took advantage of the concept of complex networks to analyze the daily taxi trip data. Using a method of community detection, we divided the study area into six main sub-regions called functional self-sufficient zones (FSZs) in which spatial associations are tight and dense. The features of these FSZs helped us to gain a deeper understanding of urban dynamics. Finally, based on this understanding, we further evaluated and optimized the urban spatial planning of Xiamen. Balancing land use allocation was suggested to enhance the multicentric structure and reduce congestion. This study provides a relevant contribution by exploring the potential of applying taxi trip data to identify urban dynamics revelations and urban planning optimization solutions.
机译:通常,由于快速的空间扩张和土地利用变化,很难研究潜在的城市动态。本文利用从厦门市收集的30天的出租车出行数据中提取的始发地(OD)数据来检测厦门市的潜在动态。具体来说,我们将研究区域离散为400m * 400m的网格,以便可以在每个单个网格内分别计算出租车行程的起点和终点的数量。然后,绘制了出租车流动性的热图,以大致了解城市动态。其次,我们利用复杂网络的概念来分析每日出租车行程数据。使用社区检测的方法,我们将研究区域划分为六个主要的子区域,称为功能自给区(FSZ),其中空间关联紧密而密集。这些FSZ的功能帮助我们对城市动态有了更深入的了解。最后,基于这种理解,我们进一步评估和优化了厦门的城市空间规划。建议平衡土地使用分配以增强多中心结构并减少拥堵。这项研究通过探索应用出租车旅行数据来识别城市动态启示和城市规划优化解决方案的潜力,提供了相关的贡献。

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