Quality of hybrid location data drawn from GPS‐enabled mobile phones: Does it matter?. Issue 2 (27th January 2020)
- Record Type:
- Journal Article
- Title:
- Quality of hybrid location data drawn from GPS‐enabled mobile phones: Does it matter?. Issue 2 (27th January 2020)
- Main Title:
- Quality of hybrid location data drawn from GPS‐enabled mobile phones: Does it matter?
- Authors:
- Yoo, Eun‐Hye
Roberts, John E.
Eum, Youngseob
Shi, Youdi - Abstract:
- Abstract: Despite their increasing popularity in human mobility studies, few studies have investigated the geo‐spatial quality of GPS‐enabled mobile phone data in which phone location is determined by special queries designed to collect location data with predetermined sampling intervals (hereafter "active mobile phone data"). We focus on two key issues in active mobile phone data—systematic gaps in tracking records and positioning uncertainty—and investigate their effects on human mobility pattern analyses. To address gaps in records, we develop an imputation strategy that utilizes local environment information, such as parcel boundaries, and recording time intervals. We evaluate the performance of the proposed imputation strategy by comparing raw versus imputed data with participants' online survey responses. The results indicate that imputed data are superior to raw data in identifying individuals' frequently visited places on a weekly basis. To assess the location accuracy of active mobile phone data, we investigate the spatial and temporal patterns of the positional uncertainty of each record and examine via Monte Carlo simulation how inaccurate location information might affect human mobility pattern indicators. Results suggest that the level of uncertainty varies as a function of time of day and the type of land use at which the position was determined, both of which are closely related to the location technology used to determine the location. Our study highlightsAbstract: Despite their increasing popularity in human mobility studies, few studies have investigated the geo‐spatial quality of GPS‐enabled mobile phone data in which phone location is determined by special queries designed to collect location data with predetermined sampling intervals (hereafter "active mobile phone data"). We focus on two key issues in active mobile phone data—systematic gaps in tracking records and positioning uncertainty—and investigate their effects on human mobility pattern analyses. To address gaps in records, we develop an imputation strategy that utilizes local environment information, such as parcel boundaries, and recording time intervals. We evaluate the performance of the proposed imputation strategy by comparing raw versus imputed data with participants' online survey responses. The results indicate that imputed data are superior to raw data in identifying individuals' frequently visited places on a weekly basis. To assess the location accuracy of active mobile phone data, we investigate the spatial and temporal patterns of the positional uncertainty of each record and examine via Monte Carlo simulation how inaccurate location information might affect human mobility pattern indicators. Results suggest that the level of uncertainty varies as a function of time of day and the type of land use at which the position was determined, both of which are closely related to the location technology used to determine the location. Our study highlights the importance of understanding and addressing limitations of mobile phone derived positioning data prior to their use in human mobility studies. … (more)
- Is Part Of:
- Transactions in GIS. Volume 24:Issue 2(2020)
- Journal:
- Transactions in GIS
- Issue:
- Volume 24:Issue 2(2020)
- Issue Display:
- Volume 24, Issue 2 (2020)
- Year:
- 2020
- Volume:
- 24
- Issue:
- 2
- Issue Sort Value:
- 2020-0024-0002-0000
- Page Start:
- 462
- Page End:
- 482
- Publication Date:
- 2020-01-27
- Subjects:
- Geographic information systems -- Periodicals
910.285 - Journal URLs:
- http://www.blackwell-synergy.com/servlet/useragent?func=showIssues&code=tgis ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1111/tgis.12612 ↗
- Languages:
- English
- ISSNs:
- 1361-1682
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 9020.502000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 13280.xml