Spatial Pattern of the Walkability Index, Walk Score and Walk Score Modification for Elderly

Bibliographic Data

ID22034263
AuthorsJiri Horak (0000-0001-6665-5294, VSB - Technical University of Ostrava, corresponding author), Pavel Kukuliač (0000-0002-6318-5247, VSB - Technical University of Ostrava), Petra Maresova (0000-0002-1218-501X, University of Hradec Králové), Lucie Orlíková (0000-0001-9777-7788, VSB - Technical University of Ostrava), Ondrej Kolodziej (0000-0002-5845-8765, VSB - Technical University of Ostrava)
Year2022
Volume11
Issue5
Pages279
Publication date2022-04-27
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueISPRS International Journal of Geo-Information (JOURNAL)
Journal identifiersISSN: 2220-9964 • E-ISSN: 2220-9964
PublisherMDPI AG (PUBLISHER • IT)
DOI10.3390/ijgi11050279
OpenAlexW4225137045
LanguageEN
Citations received9
References cited83

Contemporary cities require excellent walking conditions to support human physical activity, increase humans’ well-being, reduce traffic, and create a healthy urban environment. Various indicators and metrics exist to evaluate walking conditions. To evaluate the spatial pattern of objective-based indicators, two popular indices were selected—the Walkability Index (WAI), representing environmental-based indicators, and Walk Score (WS), which applies an accessibility-based approach. Both indicators were evaluated using adequate spatial units (circle buffers with radii from 400 m to 2414 m) in two Czech cities. A new software tool was developed for the calculation of WS using OSM data and freely available network services. The new variant of WS was specifically designed for the elderly. Differing gait speeds, and variable settings of targets and their weights enabled the adaptation of WS to local conditions and personal needs. WAI and WS demonstrated different spatial pattern where WAI is better used for smaller radii (up to approx. 800 m) and WS for larger radii (starting from 800 m). The assessment of WS for both cities indicates that approx. 40% of inhabitants live in unsatisfactory walking conditions. A sensitivity analysis discovered the major influences of gait speed and the β coefficient on the walkability assessment

Built environment · Civil engineering · Geography · Level design · Statistics · Transport engineering · Walkability · World Wide Web · Computer Science · Engineering · Environmental Science · Human Mobility and Location-Based Analysis · Mathematics · Physical Activity and Health · Urban Transport and Accessibility · Artificial Intelligence

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