Quantifying the recreational value of urban parks using smartphone mobility data

Urban parks provide substantial environmental, social, and health benefits, yet their recreational economic value often remains unquantified due to limitations in traditional data collection methods. Although previous studies have estimated park recreational value, they rarely capture how this value varies across neighborhoods and seasons because fine-grained, time-sensitive data are typically unavailable. This study addresses this gap by applying large-scale smartphone mobility data and the Travel Cost Method (TCM) analysis to estimate the recreational use value of Dick Nichols District Park, which is one of the most visited District parks in Austin, Texas. Using consumer surplus as a monetary measure of recreational benefits, the analysis combines visitation rates, travel distances, and opportunity costs with neighborhood-level sociodemographic indicators to reveal spatial and temporal patterns in park use. Our results show that the Park’s 2019 (Before COVID-19) annual recreational use value ranges from $306,983.80 to $307,067.72. Spatially, block groups in Austin’s northeastern quadrant exhibit higher recreational value, likely reflecting stronger connectivity and moderate travel distances. Our temporal analysis shows that June has the highest monthly recreational value. This study illustrates how large-scale mobility data can be integrated into recreational value assessment, offering greater visibility, scalability, and cost-effectiveness than traditional approaches. By leveraging these richer data streams, planners and policymakers can conduct more equitable, evidence-based park planning and resource allocation.

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Publication Details

Journal
Computational Urban Science
Published
2026-04-01
DOI
https://doi.org/10.1007/s43762-026-00257-6
Primary Topic
Urban Green Space and Health
Type
article
Field-Weighted Citation Impact
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article

Quantifying the recreational value of urban parks using smartphone mobility data

Yunpei Zhang, Hyewon Yoon, Guo Zipeng, Bo Zhang et al.
Computational Urban Science
Urban Green Space and Health
article

Quantifying the recreational value of urban parks using smartphone mobility data

Yunpei Zhang, Hyewon Yoon, Guo Zipeng, Bo Zhang, Hongmei Lu, Rui Zhu, Yang Song
article en

Abstract

Urban parks provide substantial environmental, social, and health benefits, yet their recreational economic value often remains unquantified due to limitations in traditional data collection methods. Although previous studies have estimated park recreational value, they rarely capture how this value varies across neighborhoods and seasons because fine-grained, time-sensitive data are typically unavailable. This study addresses this gap by applying large-scale smartphone mobility data and the Travel Cost Method (TCM) analysis to estimate the recreational use value of Dick Nichols District Park, which is one of the most visited District parks in Austin, Texas. Using consumer surplus as a monetary measure of recreational benefits, the analysis combines visitation rates, travel distances, and opportunity costs with neighborhood-level sociodemographic indicators to reveal spatial and temporal patterns in park use. Our results show that the Park’s 2019 (Before COVID-19) annual recreational use value ranges from $306,983.80 to $307,067.72. Spatially, block groups in Austin’s northeastern quadrant exhibit higher recreational value, likely reflecting stronger connectivity and moderate travel distances. Our temporal analysis shows that June has the highest monthly recreational value. This study illustrates how large-scale mobility data can be integrated into recreational value assessment, offering greater visibility, scalability, and cost-effectiveness than traditional approaches. By leveraging these richer data streams, planners and policymakers can conduct more equitable, evidence-based park planning and resource allocation.

Computational Urban ScienceVol. 6(1)
Oklahoma State University (US), Texas Tech University (US), Texas A&M University System (US), Vrije Universiteit Amsterdam (NL), Texas A&M University (US)
Sustainable cities and communities
Openalex Percentile: Top 32%
Urban Green Space and Health
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