Discovering Urban Functional Zones Using Latent Activity Trajectories
Discovering Urban Functional Zones Using Latent Activity Trajectories
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DOI：
10.1109/tkde.2014.2345405
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发表时间：
2015-03-01
影响因子：
8.9
通讯作者：
Xiong, Hui
中科院分区：
文献类型：
--
作者：
Yuan, Nicholas Jing;Zheng, Yu;Xiong, Hui
随着城市化和现代文明的发展，城市中出现了居住区、商业区、教育区等不同的功能区。在大都会中，人们每天在这些功能区之间通勤，以从事不同的社会经济活动，例如，工作购物娱乐在本文中，我们提出了一个数据驱动的框架，发现功能区在一个城市。具体来说，我们引入了潜在活动轨迹（LAT）的概念，它捕获了按时间顺序在不同地点的公民进行的社会经济活动。然后，我们根据主要道路（如高速公路和城市快速路）将城市区域划分为不连续的区域。我们已经开发了一个主题建模为基础的方法来集群的分割区域到功能区利用移动性和位置语义挖掘LAT。此外，我们使用核密度估计来识别每个功能区的强度。大量的实验进行了几个城市规模的数据集，以表明该框架提供了一个强大的能力来捕捉城市动态，并提供了有价值的校准，以城市规划师的功能区。
The step of urbanization and modern civilization fosters different functional zones in a city, such as residential areas, business districts, and educational areas. In a metropolis, people commute between these functional zones every day to engage in different socioeconomic activities, e.g., working, shopping, and entertaining. In this paper, we propose a data-driven framework to discover functional zones in a city. Specifically, we introduce the concept of latent activity trajectory (LAT), which captures socioeconomic activities conducted by citizens at different locations in a chronological order. Later, we segment an urban area into disjointed regions according to major roads, such as highways and urban expressways. We have developed a topic-modeling-based approach to cluster the segmented regions into functional zones leveraging mobility and location semantics mined from LAT. Furthermore, we identify the intensity of each functional zone using Kernel Density Estimation. Extensive experiments are conducted with several urban scale datasets to show that the proposed framework offers a powerful ability to capture city dynamics and provides valuable calibrations to urban planners in terms of functional zones.