Spatio‐Temporal Accessibility Modeling With Mobile Phone and <scp>GTFS</scp> Data: Insights for Urban Transport Planning in Helsinki

ABSTRACT This paper presents a spatially explicit method for evaluating urban accessibility using anonymized mobile phone origin–destination data combined with GTFS‐based public transport travel times. Focusing on the Helsinki Capital Region, we apply cumulative and potential accessibility metrics across multiple transport modes to assess spatial and temporal variation in mobility patterns. The integration of mobile phone data with high‐resolution transport networks enables the identification of areas with poor public transport accessibility and high car dependency, particularly among affluent populations. By leveraging geospatial methods and time‐specific data, this study provides a replicable analytical framework for urban transport planning. It supports evidence‐based strategies to promote sustainable, multimodal mobility in metropolitan regions.

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Publication Details

Journal
Transactions in GIS
Published
2025-12-01
DOI
https://doi.org/10.1111/tgis.70163
Citations
1
Primary Topic
Human Mobility and Location-Based Analysis
Type
article
Field-Weighted Citation Impact
2.18
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article

Spatio‐Temporal Accessibility Modeling With Mobile Phone and GTFS Data: Insights for Urban Transport Planning in Helsinki

Sławomir Goliszek
1 citations
Transactions in GIS
Human Mobility and Location-Based Analysis
2.18
article

Spatio‐Temporal Accessibility Modeling With Mobile Phone and GTFS Data: Insights for Urban Transport Planning in Helsinki

Sławomir Goliszek
article en
1 citations

Abstract

ABSTRACT This paper presents a spatially explicit method for evaluating urban accessibility using anonymized mobile phone origin–destination data combined with GTFS‐based public transport travel times. Focusing on the Helsinki Capital Region, we apply cumulative and potential accessibility metrics across multiple transport modes to assess spatial and temporal variation in mobility patterns. The integration of mobile phone data with high‐resolution transport networks enables the identification of areas with poor public transport accessibility and high car dependency, particularly among affluent populations. By leveraging geospatial methods and time‐specific data, this study provides a replicable analytical framework for urban transport planning. It supports evidence‐based strategies to promote sustainable, multimodal mobility in metropolitan regions.

Transactions in GISVol. 29(8)
University of Helsinki (FI), Institute of Geography and Spatial Organization, Polish Academy of Sciences (PL), General Electric (Finland) (FI)
Openalex Percentile: Top 9%
Human Mobility and Location-Based Analysis
2.18
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Spatio‐Temporal Accessibility Modeling With Mobile Phone and <scp>GTFS</scp> Data: Insights for Urban Transport Planning in Helsinki — Sławomir Goliszek · Transactions in GIS (2025) | TGRS Research Map | TGRS