Constructing human activity spaces: A new approach incorporating complex urban activity-travel

Li, Ran; Tong, Daoqin

doi:10.1016/j.jtrangeo.2016.08.013

Cited by 48 publications

(30 citation statements)

References 34 publications

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“…A diagram of activity space including the escort-space is shown in Figure 1. Methods such as the confidence ellipse, kernel density estimation and the minimum spanning tree that primarily aim to measure a range of space have been widely used in previous studies (Li and Tong, 2016). However, these methods are not suitable for measuring escort-space because most escort behavior has a fixed route.…”

Section: The Concept Of Escort-spacementioning

confidence: 99%

Investigating the effect of the spatial relationship between home, workplace and school on parental chauffeurs’ daily travel mode choice

Liu

Shi

et al. 2018

Transport Policy

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Section: The Concept Of Escort-spacementioning

confidence: 99%

Investigating the effect of the spatial relationship between home, workplace and school on parental chauffeurs’ daily travel mode choice

Liu

Shi

et al. 2018

Transport Policy

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“…Especially for most used grid-based methods, although it is easier to control the area size, code the area, and maintain the hierarchy information, some researchers point out that the determination of the size, position, and orientation of grids is arbitrary [74], and the fixed-size unit is not sufficient to reflect the density of users and their activities [75]. As a result, macroscopically, the methods above all fall short in portraying the "activity space" [76], which refers to areas that are delimited by the course of daily routines of people, and microscopically, actions of moving across boundaries become less meaningful, as one may produce crossings simply by wandering around his home or workplace.…”

Section: Map-based Region Partitioning For Content Disseminationmentioning

confidence: 99%

Geo-DMP: A DTN-Based Mobile Prototype for Geospatial Data Retrieval

Xiang

et al. 2019

IJGI

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Geospatial information is gaining immense interest and importance as we enter the era of highly developed transportation and communication. Despite the proliferation of cellular network and WiFi, on some occasions, users still face barriers to accessing geospatial data. In this paper, we design and implement a distributed prototype system with a delay/disruption tolerant network (DTN), named Geo-DMP, for cooperatively and opportunistically sharing and exchanging named geospatial contents in a device-to-device fashion. First of all, we construct a lightweight “content agent” module to bridge the gap between the application layer and the underlying DTN protocol stack. Afterwards, to profile the mobility history of users in practical geospatial environments, we present a map segmentation scheme based on road network and administrative subdivision information. Subsequently, we associate the regional movement history information with the content retrieval process to devise a hierarchical and region-oriented DTN routing scheme for both requests and responses. Finally, we conduct extensive experiments with real-world trajectories and complete implementations on the emulation platform composed of virtual machines. The experiments corroborate that Geo-DMP has the capability of successfully retrieving geospatial contents for users for most of the time under mobile circumstances with episodic connectivity. Moreover, en-route caches can be efficiently exploited to provision contents from multiple sources with less network resource consumption and shorter user-perceived latencies.

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“…They argued that Twitter is exceptionally useful for investigating the global mobility patterns, but their processing was a macro simulation and similarly unstructured big data might be inconvenient for focusing on individual mobility patterns on a microscale. Li & Tong [16] used household travel survey data and raised a new approach for constructing human activity spaces underlying urban structure. However, their main contribution is to verify the models' effect, which is divorced from the viewpoint focusing on individual human mobility.…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Analysis of Human Mobility in Manila Metropolitan Area with Person-Trip Data

Liu

2018

Urban Science

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Abstract:The metropolitan area can be regarded as a multi-functional structure consisting of plural coordinated urban nucleuses. This study aims to clarify the characteristics of urban nucleuses and a spatiotemporal pattern of human mobility in the Manila metropolitan area. Hourly density of human mobility from 00:00 to 24:00 in the whole study area is quantitatively studied. Urban nucleuses with six types: central city, business city, commuter town, south suburb, north suburb, and subcenter city, are identified. Differences of human mobility owing to different human behaviors or properties are also analyzed in 10 typical areas with different urban functions. Results prove that pattern of human mobility in each area depends on its human social division, population composition, infrastructure condition, and functional structure. This study provides an effective thinking on handling geo-tagged big data supported by MATLAB programming and GIS technology. Moreover, spatiotemporal analysis of human mobility also possesses a meaningful academic value for transport geography.

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Constructing human activity spaces: A new approach incorporating complex urban activity-travel

Cited by 48 publications

References 34 publications

Investigating the effect of the spatial relationship between home, workplace and school on parental chauffeurs’ daily travel mode choice

Investigating the effect of the spatial relationship between home, workplace and school on parental chauffeurs’ daily travel mode choice

Geo-DMP: A DTN-Based Mobile Prototype for Geospatial Data Retrieval

Spatiotemporal Analysis of Human Mobility in Manila Metropolitan Area with Person-Trip Data

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