Potential Path Areas and Activity Spaces in Application: A Review

Patterson, Zachary; Farber, Steven

doi:10.1080/01441647.2015.1042944

Cited by 107 publications

(81 citation statements)

References 73 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Such distinct patterns arise because individual DPPA depends not only on individual traveled distance but also on the area's built-up density (measured by road network density). This is consistent with previous studies that have shown that traveled distance is incapable of representing complete human mobility patterns and is not relevant to individual geographic context (Sherman et al 2005;Kamruzzaman and Hine 2012;Patterson and Farber 2015). Such a result was also supported by the weak negative correlation (r D ¡ 0:2) between traveled distance and DSTP volume indicators.…”

Section: Human Mobility Patternssupporting

confidence: 80%

“…Results of this study provided several new insights on relationships between human mobility and accessibility. First, this study extended previous human mobility studies (Sch€ onfelder and Axhausen 2003;Casas 2007;Stanley et al 2011;Kamruzzaman and Hine 2012;Patterson and Farber 2015) by investigating human mobility impacts on accessibility for the entire region of a megacity with diverse land use characteristics (i.e., spatial distribution of service facilities). This study found that human mobility impacts on accessibility, in terms of the DUR m measure, can be positive or negative, depending on land use characteristics.…”

Section: Discussionmentioning

confidence: 71%

“…., PPA n ¡ 1 , which can be aggregated to create a daily potential path area (denoted by DPPA m ). These DPPA m and DSTP m can be regarded as 2D and 3D approaches for representing the phone user's mobility, respectively (Patterson and Farber 2015). It should be noted that these DSTP m and DPPA m concepts, to some extent, are different from the classical concepts based on activity diary data (Kwan 1998).…”

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

Understanding the Impacts of Human Mobility on Accessibility Using Massive Mobile Phone Tracking Data

Chen

Wang

et al. 2018

Annals of the American Association of Geographers

View full text Add to dashboard Cite

Section: Human Mobility Patternssupporting

confidence: 80%

Section: Discussionmentioning

confidence: 71%

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Understanding the Impacts of Human Mobility on Accessibility Using Massive Mobile Phone Tracking Data

Chen

Wang

et al. 2018

Annals of the American Association of Geographers

View full text Add to dashboard Cite

“…The most common method to operationalize activity space is the standard deviation ellipse (SDE) that measures the directional distribution of a series of GPS points or the "densest" areas where most of the individual mobility occurs [40]. The SDE is usually centered at an individual's home [41] and extended two standard deviations to cover 95% of the observed activity locations [42]. This study uses an SDE to represent the participant's activity space [42].…”

Section: Creating Activity Spacementioning

confidence: 99%

Association Between Physical Activity and Activity Space in Different Farming Seasons Among Rural Lao PDR Residents

Jiang

Lin

Yonto

et al. 2020

Preprint

View full text Add to dashboard Cite

Background: Southeast Asia is experiencing a health transition where non-communicable diseases (NCD) are exceeding communicable diseases. Despite NCDs accounting for roughly 60-85% of deaths in the region, many developing Southeast Asian countries are beginning to address the impacts of a physically inactive lifestyle for the first time. Our study aims to bridge this gap by objectively measuring physical activity in rural Lao PDR to reveal the association among physical activity, activity space, and seasonal variation. Methods: Multiple waves of survey data were collected in Songkhon District, Lao PDR between March 2010 and March 2011. Adults aged between 18 and 65 were recruited (n=48). A portable GPS recorded participants’ activity and farmland locations and an accelerometer recorded participants’ physical activity level and daily steps for seven consecutive days. Using a directional distribution tool in ArcGIS 10.5, the activity space area of each participant in each wave was calculated. Concurrently, participants recorded time spent on each daytime activity. Linear mixed models with the fixed effects as the observations from different waves and the random effects as individual participants were developed to identify factors associated with areas of activity space and counts of daily steps, respectively.Results: A total of 48 respondents with half being females were recruited. Walking was found to be the most frequent travel mode. Females were physically less active with smaller activity space and more overweight than their male counterparts. Participants were physically less active during the off-farming seasons. Conclusions: Findings contribute to the surveillance of risk factors needed to create healthy living environments. Our research is also one of the first to use empirical evidence demonstrating seasonal variations of rural residents’ activities in mainland Southeast Asia.

show abstract

“…We focus on one particular time geography concept: the Potential Path Area (PPA), a popular accessibility measure in transport (Patterson and Farber 2015). A PPA is the projection of a Space-Time Prism (STP) onto the geographical plane (Miller 2005).…”

Section: Introductionmentioning

confidence: 99%

Time-Geography in Four Dimensions: Potential Path Volumes around 3D Trajectories

Demšar¹,

Long²

2016

GIScience

View full text Add to dashboard Cite

An upcoming increase in availability and accuracy of 3D positioning requires development of new analytical approaches that will incorporate the third positional dimension, the elevation and model space and time as a 4D concept. In this paper we propose the extension of time geography into four dimensions. We generalise the time geography concept of a Potential Path Area into a Potential Path Volume around a 3D trajectory and present its mathematical definition. The algorithm for calculating PPVs around 3D trajectories is currently being implemented and will be tested on simulated data and real 3D data from movement ecology.

show abstract

Potential Path Areas and Activity Spaces in Application: A Review

Cited by 107 publications

References 73 publications

Understanding the Impacts of Human Mobility on Accessibility Using Massive Mobile Phone Tracking Data

Understanding the Impacts of Human Mobility on Accessibility Using Massive Mobile Phone Tracking Data

Association Between Physical Activity and Activity Space in Different Farming Seasons Among Rural Lao PDR Residents

Time-Geography in Four Dimensions: Potential Path Volumes around 3D Trajectories

Contact Info

Product

Resources

About