Walkability Scores Research Articles

Spatial Image-Based Walkability Evaluation Using Regression Model

Spatial Image-Based Walkability Evaluation Using Regression Model

Quantifying Area-Level Physical Activity Offerings in Social Context: A Novel Concept That Goes Beyond Walkability and Access to Open Spaces.

Social support is a crucial factor influencing the sustainability of physical activity (PA). This proof-of-concept study presents the development of a Social Physical Activity Index for Area (SPAIFA) an indicator reflecting opportunities for individuals to actively participate as part of a group within which opportunities for social interaction can be developed. Six government councils in the state of New South Wales, Australia, were selected encompassing 174 suburbs. Using 2 search engines' map tools, we identified PA venues for each suburb (eg, park, studios, etc). To enumerate activities per suburb, we used (1)venue websites, (2)New South Wales Office of Sport website, (3)national websites of grassroots PA for nonorganized activity (eg,parkrun, meetup, etc), and (4)social media. The database was linked to the suburb demographic profile, the area disadvantage score, walkability and open space scores, and the proportion of insufficiently active residents. Spatial analysis techniques were used to identify SPAIFA clusters. SPAIFA councils' average was 9.9 activities per 10,000 people (ranging from 6.6/10,000 to 16.2/10,000). SPAIFA-Old (ie,activities specific to older adults) varied significantly (ranging from 11.7/10,000 to 0.8/10,000 seniors). Disadvantaged areas and a high proportion of insufficiently active residents were associated with being classified as low SPAIFA (P < .01). Three clusters of low SPAIFA were identified, and 17 high-risk areas where low SPAIFA was compounded by poor environmental support. SPAIFA can be used by councils and policymakers as an indicator for monitoring and intervening in areas where natural and/or urban design is not conducive for PA.

Investigating the walkability of primary, secondary and K-12 schools across metropolitan Perth, Western Australia

Having a walkable built environment is important to encourage active school transport. The aim of this study was to measure the walkability of all Perth, Western Australia (WA) schools and investigate whether differences in walkability exist by school type, socioeconomic status (SES) and/or subregion. Geographic Information Systems technology was used to measure walkability (i.e., traffic exposure and pedestrian connectivity) surrounding all Perth schools (n = 651) in 2021. Walkability scores and their individual components were compared using odds ratios and one-way ANOVAs with post-hoc comparisons by school type (primary, secondary and K-12; government and non-government), school SES and subregion. The majority of Perth schools (73.8%) were below the WA Planning Commission’s target for a walkable catchment area. Neighbourhoods surrounding high SES schools were significantly more walkable than neighbourhoods surrounding medium and low SES schools (mean walkability scores: 12.4, 10.5, 10.1, respectively, p < .001). Neighbourhoods surrounding schools located in the Central subregion (mean 12.3) were significantly more walkable than neighbourhoods surrounding schools located in the North-West (mean 11.0, p = .024), South Metropolitan (mean 10.0, p < .001) and North-East (mean 8.4, p < .001) subregions. No significant differences in walkability index scores were found for school type. This study found a large proportion of Perth schools were surrounded by disconnected street networks and that neighbourhoods surrounding high SES schools were, on average, more walkable than neighbourhoods surrounding medium and low SES schools. The results highlight the importance of modifying the built environment to increase opportunities for active school transport, particularly in low and medium socio-economic areas.

Accessibility of Walking and Biking as Forms of Exercise in Harris County, Texas, USA

The prevalence of obesity in Texas, specifically Harris County, is a growing health concern. 26.7% of Texan adults reported no leisure time activity, which is significantly higher than the national average (24.4%). This study aimed at collecting walkability and bike-ability scores for 115 zip codes covering the greater City of Houston in Harris County, Texas, USA. The walkability and bike-ability scores are objective representations of the ability one completes their daily errands. Walkscore.com was used to collect the data from 115 zip codes found inside Harris County. It ranks walkability and bike-ability on a scale of 0 to 100 depending on the availability of walking and biking infrastructure in an area. Thirty-three (28.4%) zip codes had walkability scores between 0 and 24, thirty-nine (33.6%) had scores between 25 and 49, thirty (25.9%) had scores between 50 and 69, eleven (9.5%) had scores between 70 and 89, and only two zip codes scored above 90 (1.7%). Only thirty-five counties have a reported bike-ability score. Zero (0%) are within 0-24, thirty (83.3%) are within 25 to 49, two (5.6%) are within 50 to 69, three (8.33%) are within 70 to 89, and zero (0%) are within 90-100. The majority (72, 62.1%) required vehicle transportation while only thirteen (11.2%) had walkability scores over 70. Only 5 (4.3%) of the total zip codes within Harris County have adequate biking infrastructure.

Factors influencing subjective walkability: Results from built environment audit data

Subjective walkability is a measure of the perceived friendliness of walking in an area. Though subjective walkability is less commonly assessed than objective measurements, the latter often fail to reflect the experience of walking. This study aims to better understand subjective walkability and how it varies between travel and leisure walking by investigating its relationship with the built environment and land-use characteristics. Data is collected from 848 street segments in Montreal, Canada, using the MAPS-mini audit tool, external measurements including Walkscore as well as synthetic subjective walkability scores. Mixed effect multilevel models are then generated using travel and leisure subjective walkability scores as dependent variables and built environment features as independent variables. Statistically significant positive predictors of perceived walkability differ between walking for travel and walking for leisure. Walkscore is found to have a weak but significant effect on perceived walkability for travel but no effect at all for leisure. Based on this research, a multi-scalar approach both at the street and neighborhood level making use of a combination of objective and subjective walkability measures should be employed to study predictors of walking behavior. Lastly, distinctions of walking behaviors based on trip purpose should be integrated in future research.

Impact of neighbourhood walkability on weekly walking minutes among adults with visual impairments: A preliminary study

Weekly and consistent physical activity can help minimize the risk of preventable disease and improve mental health and cognitive function among adults. Despite these benefits, adults with visual impairments tend to not meet physical activity recommendations. The purpose of this preliminary study was to examine how neighbourhood walk score (walkability) is associated with weekly walking minutes in adults with visual impairments. Participants were recruited from two visual impairment–related listservs in the United States. A total of 88 participants (aged 22–85 years; 78% female) were included. Participants completed an online survey including demographic, walking duration, and zip code questions. Linear regression analyses were performed to determine whether there were significant associations between walkability and weekly walking minutes. Walkability scores were not significantly related to walking minutes per week ( p = .84), but age was negatively associated with walking minutes per week (β = −.16), holding other factors constant. Neighbourhood walkability was not significantly associated with walking minutes per week among adults with visual impairments in this study. As these adults age, the amount of walking decreased. Future research in this line of inquiry should expand to include other variables that may influence the relationship between walkability and walking minutes per week and examine the barriers to physical activity among individuals with visual impairments.

Associations Between Minute-Level Smartphone-Derived Exposure to Walkability and Consumer Wearable-Derived Physical Activity in the US-based Nurses’ Health Study 3 Cohort 2018-2020

Background and Aim: Walkable environments have been linked to increased physical activity and improved health outcomes. However, most studies measure exposure based on residential address alone, not accounting for mobility patterns. We aimed to explore the association of smartphone mobility-derived walkability exposure and wearable-based physical activity in a group of US women. Methods: We quantified associations of minute observation level smartphone GPS-based walkability with daily Fitbit wearable accelerometry data. The NHS3 mhealth study followed 348 participants who completed four seasonal seven-day sampling periods. GPS points collected every 10 minutes were linked to a census tract-level walkability index calculated by a summed z-score of road intersection density from 2018 TIGER/Line shapefiles, 2018 Infogroup business density, and 2015-2019 5-year American Community Survey population density estimates. Mean Fitbit-derived steps per minute was calculated for each 10-minute period (n=639,364). Generalized Additive Mixed Models accounting for correlated data within individuals and enabling penalized splines were used to explore associations. We adjusted for GPS based socioeconomic status, daily GPS temperature and precipitation, satellite-based greenness in the 30m around each GPS point, and individual factors. Results: Mean minute-level walkability was 0.24 (SD = 3.07) and mean steps per minute was 7.04 (SD = 14.98). Associations were non-linear in nature, trending steeply upward and plateauing at the highest levels of walkability. We found an increase of 2.24 (95% CI: 1.40, 3.09) mean steps per minute for each 1-point increase in walkability scores from -1.66 to 5.50. Conclusions: We used data at fine spatial-temporal scales to present novel estimates on time-intensive longitudinal associations between walkability and physical activity, while accounting for within- and between-participant differences. Participants were more likely to be physically active in more walkable areas, suggesting improvements in the built environment may improve health outcomes downstream of physical activity. Keywords: Wearables, Walkability, Physical Activity, Mixed Models

Associations between walkability and pedestrian related injuries is modified by sociodemographic characteristics

BackgroundWalkability scores have been developed to measure how well the characteristics of the physical environment support walking. However, because pedestrian safety is not taken into account, areas that have higher Walk Scores could be associated with more walking and also more pedestrian-related injury. We aimed to explore the association between Walk Score and pedestrian-related injury in Sydney. MethodPedestrian-related injuries from 2010 to 2018 in Sydney were identified in the New South Wales Combined Admitted Patient Epidemiology Data. Walk Score was used to measure area-level walkability in Sydney statistical division. Regression models were used to examine the association between Walk Score, pedestrian-related injury, length of hospital stay (LOS) and injury severity. ResultAmong people aged ≤64 years, there was no significant association between walkability score and pedestrian-related injury. Among people aged ≥ 65 years, walkability score was significantly positively associated with pedestrian-related injury, which peaked at Somewhat Walkable. For most disadvantaged areas, the risk of pedestrian-related injury was highest for areas that were classified as Somewhat Walkable. For moderately disadvantaged areas, the risk of pedestrian-related injury was highest at Very Walkable to Walker's Paradise areas. For the least disadvantaged areas, there was no significant association between walkability score and pedestrian-related injury. For LOS among people aged ≥ 65 years or in the most disadvantaged areas, it peaked at Somewhat Walkable areas. For injury severity, the risk of serious pedestrian-related injury was highest at Very Walkable to Walker's Paradise areas among people aged 16–64 years. ConclusionFor the majority of the population, built environment characteristics that are considered to make walking attractive also make it safer, offsetting any exposure-related increase injury risk. However, this is not the case for people aged ≥ 19 years, and those living in socioeconomically disadvantaged areas. Incorporating measures of pedestrian safety in walkability scores may create an impetus to ensure that the built environment is designed to support the safety of pedestrians from these groups.

ALF-Score++, a novel approach to transfer knowledge and predict network-based walkability scores across cities

Walkability is an important measure with strong ties to our health. However, there are existing gaps in the literature. Our previous work proposed new approaches to address existing limitations. This paper explores new ways of applying transferability using transfer-learning. Road networks, POIs, and road-related characteristics grow/change over time. Moreover, calculating walkability for all locations in all cities is very time-consuming. Transferability enables reuse of already-learned knowledge for continued learning, reduce training time, resource consumption, training labels and improve prediction accuracy. We propose ALF-Score++, that reuses trained models to generate transferable models capable of predicting walkability score for cities not seen in the process. We trained transfer-learned models for St. John’s NL and Montréal QC and used them to predict walkability scores for Kingston ON and Vancouver BC. MAE error of 13.87 units (ranging 0–100) was achieved for transfer-learning using MLP and 4.56 units for direct-training (random forest) on personalized clusters.

Perceived Walkability and Respective Urban Determinants: Insights from Bologna and Porto

Walking is undoubtedly a sustainable and healthy mode of transport. However, the decision to walk is influenced by many built environment and streetscape attributes. Specifically, the term walkability is used to describe the extent to which the urban environment is pedestrian-friendly, usually by quantifying multiple built environment attributes at the neighbourhood scale. The present study adopts a qualitative approach to evaluate perceived walkability. Based on a questionnaire (n = 1438) administered in the cities of Bologna and Porto, this paper analyses how respondents perceived and evaluated 19 built environment and streetscape attributes. An Exploratory Factor Analysis was carried out to examine the correlations between the various attributes and to identify the underlying walkability determinants. The analysis indicated that 13 attributes were highly correlated, resulting in four determinants: (i) urban ambiance, which includes land use and street design attributes, such as land use mix, enclosure, transparency, and architectural and landscape diversity; (ii) pedestrian infrastructure, which is related to sidewalk conditions; (iii) street connectivity and proximity to community facilities; and iv) access to other modes of transport. In turn, traffic safety and security were not correlated with perceived walkability in both cities. These findings suggest that specific urban design and pedestrian infrastructure attributes should be highly considered when formulating policies aiming to create more pedestrian-friendly cities, as well as in walkability studies and when developing walkability scores and indexes.

ALF-Score-A novel approach to build a predictive network-based walkability scoring system.

Walkability is a term that describes various aspects of the built and social environment and has been associated with physical activity and public health. Walkability is subjective and although multiple definitions of walkability exist, there is no single agreed upon definition. Road networks are integral parts of mobility and should be an important part of walkability. However, using the road structure as nodes is not widely discussed in existing methods. Most walkability measures only provide area–based scores with low spatial resolution, have a one–size–fits–all approach, and do not consider individuals opinion. Active Living Feature Score (ALF–Score) is a network–based walkability measure that incorporates road network structures as a core component. It also utilizes user opinion to build a high–confidence ground–truth that is used in our machine learning pipeline to generate models capable of estimating walkability. We found combination of network features with road embedding and points of interest features creates a complimentary feature set enabling us to train our models with an accuracy of over 87% while maintaining a conversion consistency of over 98%. Our proposed approach outperforms existing measures by introducing a novel method to estimate walkability scores that are representative of users opinion with a high spatial resolution, for any point on the road.

Green Walkability and Physical Activity in UK Biobank: A Cross-Sectional Analysis of Adults in Greater London.

Urban greenspace provides opportunities for outdoor exercise and may increase physical activity, with accompanying health benefits. Areas suitable for walking (walkability) are also associated with increased physical activity, but interactions with greenspace are poorly understood. We investigated associations of walkability and green walkability with physical activity in an urban adult cohort. We used cross-sectional data from Greater London UK Biobank participants (n = 57,726) and assessed walkability along roads and footpaths within 1000 m of their residential addresses. Additionally, we assessed green walkability by integrating trees and low-lying vegetation into the walkability index. Physical activity outcomes included self-reported and accelerometer-measured physical activity and active transport. We assessed associations using log-linear, logistic and linear regression models, adjusted for individual- and area-level confounders. Higher green walkability was associated with favourable International Physical Activity Questionnaire responses and achievement of weekly UK government physical activity guideline recommendations. Participants living in the highest versus lowest quintile of green walkability participated in 2.41 min (95% confidence intervals: 0.22, 4.60) additional minutes of moderate-and-vigorous physical activity per day. Higher walkability and green walkability scores were also associated with choosing active transport modes such as walking and cycling. Our green walkability approach demonstrates the utility in accounting for walkability and greenspace simultaneously to understand the role of the built environment on physical activity.

A longitudinal examination of objective neighborhood walkability, body mass index, and waist circumference: the REasons for Geographic And Racial Differences in Stroke study

BackgroundStudies have shown neighborhood walkability is associated with obesity. To advance this research, study designs involving longer follow-up, broader geographic regions, appropriate neighborhood characterization, assessment of exposure length and severity, and consideration of stayers and movers are needed. Using a cohort spanning the conterminous United States, this study examines the longitudinal relationship between a network buffer-derived, duration-weighted neighborhood walkability measure and two adiposity-related outcomes.MethodsThis study included 12,846 Black/African American and White adults in the REasons for Geographic And Racial Differences in Stroke study. Body mass index (BMI) and waist circumference (WC) were assessed at baseline and up to 13.3 years later (M (SD) = 9.4 (1.0) years). BMI and WC were dichotomized. Walk Score® was duration-weighted based on time at each address and categorized as Very Car-Dependent, Car-Dependent, Somewhat Walkable, Very Walkable, and Walker’s Paradise. Unadjusted and adjusted logistic regression models tested each neighborhood walkability-adiposity association. Adjusted models controlled for demographics, health factors, neighborhood socioeconomic status, follow-up time, and either baseline BMI or baseline WC. Adjusted models also tested for interactions. Post-estimation Wald tests examined whether categorical variables had coefficients jointly equal to zero. Orthogonal polynomial contrasts tested for a linear trend in the neighborhood walkability-adiposity relationships.ResultsThe odds of being overweight/obese at follow-up were lower for residents with duration-weighted Walk Score® values in the Walker’s Paradise range and residents with values in the Very Walkable range compared to residents with values in the Very Car-Dependent range. Residents with duration-weighted Walk Score® values classified as Very Walkable had significantly lower odds of having a moderate-to-high risk WC at follow-up relative to those in the Very Car-Dependent range. For both outcomes, the effects were small but meaningful. The negative linear trend was significant for BMI but not WC.ConclusionPeople with cumulative neighborhood walkability scores in the Walker’s Paradise range were less likely to be overweight/obese independent of other factors, while people with scores in the Very Walkable range were less likely to be overweight/obese and less likely to have a moderate-to-high risk WC. Addressing neighborhood walkability is one approach to combating obesity.

Comparing Methods for Measuring Walkability

Walkability analyses have gained increased attention for economic, environmental and health reasons, but the methods for assessing walkability have yet to be broadly evaluated. In this paper, five methods for calculating walkability scores are described: in-radius, circle buffers, road network node buffers, road network edge buffers and a fully integrated network approach. Unweighted and various weighted versions are analyzed to capture levels of preference for walking longer distances. The methods are evaluated via an application to train stations in central Tokyo in terms of accuracy, similarity and algorithm performance. The fully integrated network method produces the most accurate results in the shortest amount of processing time, but requires a large upfront investment of time and resources. The circle buffer method runs a bit slower, but does not require any network information and when properly weighted yields walkability scores very similar to the integrated network approach.

Exploring the trend of walkability measures by applying hierarchical clustering technique

IntroductionOver the last two decades, many walkability attributes and variables have been considered in the evaluation of walkability scores with various methods and approaches. This study investigates the recent trend of walkability measures in terms of the scale of analysis, the case study location, the type of measurements, the data collection tool, the analysis method, and the research field. MethodsIn a review of existing literature, this paper analyzes and compares the walkability studies over the past two decades. A total of 75 articles from 40 journals and conference proceedings were selected through a systematic and sequential procedure. In order to explore the research trend among the reviewed articles, we applied a hierarchical clustering technique. A meta-analysis was performed to systematically assess the results of previous walkability studies to derive conclusions about the future direction of research. ResultsThe result of this review reveals that recent walkability studies in North America have prevailed in a street-level microscopic analysis while the others in Asia and Europe have focused on both large and small-scale walkability analysis. Advanced images and instrument audit tools are being applied nowadays in addition to traditional physical audit tools for measuring walkability. In recent years, urban design qualities objectively measuring at a street level (e.g., comfort/convenience, aesthetics, sidewalk design, etc.) have been widely used in determining walkability in lieu of the traditionally used attributes (e.g., roadway level of service). ConclusionThis study presents a future direction for walkability studies along with the recent trend in walkability measures and data analysis. Walkability studies have attracted significant attention more recently than in previous years. The recent trend of automated and systematic walkability data collection will eventually enable detailed analysis at a large scale and contribute to advancing walkability studies.

Traditional and novel walkable built environment metrics and social capital

A rapidly growing body of literature has explored associations between urban design attributes, which are conducive to walking, and social capital. The current study aimed to build on the limitations of previous research. Specifically, this study estimated the associations between traditional and novel walkable built environment metrics and social capital among a sample of adults in Japan. Data (n = 1010) from a randomly selected cross-section of residents (40–69 years old) from two areas in Japan were included. Social capital was assessed by questionnaires. Several objective and perceived walkable built environment attributes were calculated. Covariate-adjusted multivariable linear regression models were used to estimate associations between neighborhood built attributes and the three social capital scores. Street connectivity was negatively associated with activities with neighbors (b = -0.21, 95% CI -0.31, -0.11). Perceived population density was negatively associated with all three social capital scores, including social cohesion, activities with neighbors, and social participation (b = -0.21, 95% CI -0.30, -0.11, b = -0.15, 95% CI -0.24, -0.06, and b = -0.16, 95% CI -0.29, -0.02, respectively). Traditional walkability and Walk Score® were negatively associated with activities with neighbors (b = -0.04, 95% CI -0.07, -0.00 and b = -0.09, 95% CI -0.15, -0.04, respectively). No significant associations were observed between perceived walkability and social capital scores. Space syntax walkability was negatively associated with social cohesion and activities with neighbors (b = -0.12, 95% CI -0.23, -0.01 and b = -0.11, 95% CI -0.21, -0.01, respectively). This study provided unique findings demonstrating that walkable built environments may not necessarily support social capital in ultrahigh-density Asian cities.

Microscale Walkability Modelling. The Case of Athens City Centre

To date, several macro-level walkability measures have been proposed, but microscale and audit-based walkability approaches prove to be highly effective to support realistic, quick and cheap mechanisms for pedestrian-friendly environments. Yet, walkability audits are time- and cost-intensive solutions, because they require several streetscape observations. This study aims to investigate whether a multiple linear regression model of urban form- and function-related variables can effectively predict an audit-based average walkability indicator. For this purpose, we use a virtual, brief and reliable audit tool (MAPS-Mini) in Athens city centre in order to collect street-level data and in turn to construct a microscale walkability indicator (dependent variable). Moreover, our approach suggests a flexible statistical model of open-source data, with six exploratory variables of the macro-level built environment: angular integration, population density, transit stop density, pedestrian street density, retail and entertainment activity density, and building height. The results indicate that audit-based average walkability scores can be effectively estimated, as the regression model can explain about 82% of the variation. Furthermore, the density of retail and entertainment activities was indicated as the strongest correlate of more walking-friendly streetscapes, while some urban policy implications include the promotion of footpath repairs and better-engineered crossings.

Promotion of leisure-time physical activity by craft breweries in Knoxville, Tennessee

ABSTRACT There exists literature written on connections between alcohol consumption and physical activity, but no research has been conducted to assess co-occurrence of these as paired behaviours. However, a growing collection of popular articles point towards a particularly unique relationship between craft beer and leisure-time physical activity (LTPA). To empirically describe this phenomenon, the research objective was to profile craft breweries in Knoxville, TN regarding prevalence/type of LTPA promotion and its relation to neighbourhood built environment factors. Data from breweries (N = 13) were collected using electronic surveys, content analysis of Facebook, and Walk Score metrics. Analyses included descriptive and frequency statistics, non-parametric correlations, chi-square, and Mann-Whitney tests. All craft brewery respondents (N = 10) indicated hosting group activities (median = 4/month). Although a relatively small proportion (3.7%) of Facebook posts mentioned LTPA, the frequency with which these posts occurred was inversely related to shopping, culture, dining/drinking, and walkability scores (r’s = −.503 to −.831, p’s<.05). These findings point to craft breweries as potential entry points for LTPA promotion, warranting further research regarding patron behaviour and perceptions. We discuss our findings in relation to the role of craft breweries in neighbourhood revitalisation, as well concerns regarding aspects of diversity.

The association of neighborhood walkability with health outcomes in older adults after acute myocardial infarction: The SILVER-AMI study.

Physical activity and social support are associated with better outcomes after surviving acute myocardial infarction (AMI), and greater walkability has been associated with activity and support. We used data from the SILVER-AMI study (November 2014–June 2017), a longitudinal cohort of community-living adults ≥ 75 years hospitalized for AMI to assess associations of neighborhood walkability with health outcomes, and to assess whether physical activity and social support mediate this relationship, if it exists. We included data from 1345 participants who were not bedbound, were discharged home, and for whom we successfully linked walkability scores (from Walk Score®) for their home census block. Our primary outcome was hospital-free survival time (HFST) at six months after discharge; secondary outcomes included physical and mental health at six months, assessed using SF-12. Physical activity and social support were measured at baseline. Covariates included cognition, functioning, comorbidities, participation in rehabilitation or physical therapy, and demographics. We employed survival analysis to examine associations between walkability and HFST, before and after adjustment for covariates; we repeated analyses using linear regression with physical and mental health as outcomes. In adjusted models, walkability was not associated with physical health (ß = 0.010; 95% CI: −0.027, 0.047), mental health (ß = −0.08; 95% CI: −0.175, −0.013), or HFST (ß = 0.008; 95% CI: −0.023, 0.009). Social support was associated with mental health in adjusted models. Neighborhood walkability was not predictive of outcomes among older adults with existing coronary disease, suggesting that among older adults, mobility limitations may supercede neighborhood walkability.

Walkability scoring: Why and how does a three-dimensional pedestrian network matter?

Previous walkability scoring systems are all based on road networks, even though roads are not designed for pedestrians. To calculate an accurate walking score, we need pedestrian network data. This is especially the case in cities such as Hong Kong, where pedestrians are separated from vehicles by footbridges, underpasses or surface sidewalks. In this paper, we investigate why and how a three-dimensional pedestrian network makes a difference in walkability scoring, using Hong Kong as a case city. We developed a walkability scoring system based on networks and amenities, using multiple open-source programming platforms and languages. Separately, we calculated walkability scores (on a scale of 0–100) using the three-dimensional pedestrian network and road network of the city, comparing the differences between the two. A GIS raster analysis was conducted to extract walkability scoring differences from the two walkability surfaces, followed by a univariate linear model to examine how the scores were underestimated if without using the three-dimensional pedestrian network. Results show that streets were considered twice as walkable if rated by pedestrian network rather than road network. Walkability scores were 92% higher on average. The fitted model shows that the mean score underestimations were significantly different for different three-dimensional network elements. Surface sidewalks had an average underestimation of 33.75 (p &lt; 0.001), footbridges and underground paths expanded the underestimations by 3.85 and 2.97 (both p &lt; 0.001), respectively, and the linkages to footbridge and underground path enlarged the surface sidewalk underestimations by 2.68 and 4.92 (both p &lt; 0.001). We suggest that walkability evaluation systems should be developed on pedestrian networks instead of road networks, especially for high-density cities.