Evaluation of Walkability Index for Embedded Community Services from an Age-Friendly Perspective: A Case Study of Mapple Community in Chengdu, China
Abstract
:1. Introduction
1.1. Research Background
1.2. Literature Review
- The lack of comprehensive evaluation suitable for all different groups. Although a large number of studies have been conducted specifically for the elderly or children, there is little literature that considers the comprehensive use of community facilities by different age groups.
- The lack of quantitative consideration for the decline in attractiveness of community facilities. In real life, the elderly or children may find it more difficult to walk to facilities due to their physical condition and mobility. Although some scholars have proposed introducing Gaussian functions in calculations to simulate distance attenuation [34], they have not fully considered the differences in mobility among different populations.
- There is a lack of integration between accessibility and availability. Accessibility and availability are both important factors in infrastructure evaluation. Therefore, it is necessary to quantitatively calculate the arrival process from a spatial perspective and conduct micro-level investigations based on the usage patterns of different populations.
1.3. Research Questions and Objectives
- Construct a classification system for embedded community service facilities and assign functional weights based on demand significance.
- Calculate walkability indices using accessibility models to quantify spatial access to services.
- Evaluate the spatial suitability and equity of facility distribution from the perspectives of different age groups. By integrating GIS spatial analysis and empirical survey data, the study provides a quantitative framework for assessing age-friendliness in embedded services. The findings are aligned with national policy trends and offer practical guidance for optimizing community-level public service delivery in the context of inclusive urban renewal.
2. Materials and Methods
2.1. Study Area
2.2. Data Resource
2.3. Study Design
2.3.1. Facility Usage Frequency and Weighting Calculation
- Demographic Information—This section collected basic socio-demographic attributes of respondents, including age, gender, household size, and number of elderly household members.
- Service Demand and Frequency of Use—Respondents were asked whether they had a need for each of the seven categories of embedded service facilities. Responses were coded as 0 (no demand) or 1 (has demand). Furthermore, for those indicating demand, they were asked about the frequency of usage, coded as 1 (never), 2 (occasionally), 3 (frequently).
- Computation of Demand Index—A demand index was calculated by multiplying the binary demand value by the usage frequency. The index values were then interpreted as follows: 0 = No demand; 1 = Demand but never used; 2 = Occasionally used; 3 = Frequently used.
2.3.2. Facility Time Decay Curve Fitting
2.3.3. Facility Accessibility Evaluation
3. Embedded Service Facility Results in Age-Friendly Communities
3.1. Facility Demand from the Perspective of Age-Friendly Communities
3.2. Comparison of Walkability Index Before and After the Maple Community Update
3.3. Walkability Index of Various Age Groups in Maple Community
4. Discussion
4.1. The Impact of the Distribution of Embedded Service Facilities on Walkability in Age-Friendly Communities
4.2. Optimization Suggestions for Embedded Service Facilities
4.3. Research Innovations and Outlook
- We proposed a walkability calculation method for embedded community service facilities from an age-friendly perspective. Empirical research was conducted through spatial accessibility calculations and questionnaire surveys.
- We proposed a distance attenuation function for community service facilities targeting different groups of people. Most previous studies have used a single function to calculate the decline in attractiveness of service facilities, while ignoring the heterogeneity of users. This study takes this factor into consideration.
- A comprehensive evaluation system for walkability was constructed by combining accessibility theory with usability theory.
- Conduct comparative analyses across more cities and communities to test the universality of the evaluation framework and develop context-specific optimization strategies.
- Integrate dynamic datasets such as real-time population flows and big data to assess the temporal efficiency and supply–demand balance of facilities, enabling more adaptive planning approaches.
- Enrich the evaluation index system by including indicators such as walking environment quality, user satisfaction, and intergenerational interaction benefits, thus providing a more comprehensive quantification of age-friendly community characteristics. Through continued empirical research and refinement of evaluation metrics, this line of inquiry can contribute to a deeper understanding of how embedded community service facilities function under aging pressures, offering robust theoretical support and policy insights for urban renewal practices.
- This study reveals the long-term constraints of early planning on the older population but does not delve into the causal relationship between social cohesion and facility accessibility. In the future, it is necessary to combine longitudinal data to analyze how embedded facility renewal can incrementally improve older residents’ social networks and sense of belonging to the community.
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
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Data Type | Data Description | Data Source |
---|---|---|
Facility Weighting Data | Weights were assigned based on residents’ demand and usage frequency for different types of facilities. | Results from on-site questionnaire surveys |
Road Network Data | Pedestrian-accessible road centerlines were extracted, including expressways, urban arterials, subarterials, local streets, and pedestrian paths. | OSM (OpenStreetMap) open-source data |
Residential Entrance Point Data | Locations of all residential compound entrances and exits within the study area. | Verified through field investigation |
Embedded Service Facility Point Data | Locations of various types of embedded service facilities within the study area. | POI data retrieved from Gaode Map |
Facility Category | Facility Subcategory | Quantity |
---|---|---|
Elderly Care Services | Elderly Care Institutions; Home-Based Elderly Service Centers; Community Elderly Care Centers | 3 |
Childcare and Daycare Services | Child Daycare Centers | 5 |
Community Meal Assistance | Community Canteens | 1 |
Housekeeping and Convenience Services | Express Delivery Stations; On-Demand Cleaning Services; Neighborhood Barbershops | 5 |
Healthcare Services | Community Health Service Stations; General Hospitals | 25 |
Sports and Fitness Facilities | Multipurpose Sports Complexes; Public Fitness Gyms; Outdoor Fitness Trails | 11 |
Cultural and Recreational Facilities | Urban Study Rooms; Community Cultural Centers; Community Activity Rooms; Public Cultural Facilities | 1 |
Type | Elderly Care Facilities | Childcare and Daycare Facilities | Community Meal Assistance Facilities | Housekeeping and Convenience Facilities | Healthcare Facilities | Sports and Fitness Facilities | Cultural and Recreational Facilities |
---|---|---|---|---|---|---|---|
Adolescents | / | 0.15 | / | 0.15 | 0.18 | 0.32 | 0.22 |
Young Adults | 0.08 | 0.09 | 0.05 | 0.23 | 0.19 | 0.22 | 0.14 |
Middle-aged Adults | 0.10 | 0.06 | 0.06 | 0.14 | 0.24 | 0.27 | 0.12 |
Older Adults | 0.12 | / | 0.10 | 0.17 | 0.22 | 0.27 | 0.11 |
Walkability Score | Description |
---|---|
90~100 | Walker’s Paradise: Daily errands do not require a car; all needs met by walking. |
70~89 | Very Walkable: Most errands can be accomplished on foot. |
50~69 | Somewhat Walkable: Some errands can be accomplished on foot. |
25~49 | Car-Dependent: Most errands require a car. |
0~24 | Car-Dependent: Almost all errands require a car. |
Walk Score | Adolescents | Young Adults | Middle-Aged Adults | Older Adults | ||||
---|---|---|---|---|---|---|---|---|
Road Length (m) | Rate (%) | Road Length (m) | Rate (%) | Road Length (m) | Rate (%) | Road Length (m) | Rate (%) | |
0–24 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
24–49 | 0 | 0 | 0 | 0 | 0 | 0 | 115.89 | 1.32 |
50–69 | 531.15 | 6.05 | 0 | 0 | 515.34 | 5.87 | 2864.71 | 32.63 |
70–89 | 4686.43 | 53.38 | 2159.73 | 24.6 | 5674.99 | 64.64 | 5122.77 | 58.35 |
90–100 | 3561.79 | 40.57 | 6619.65 | 75.4 | 2589.04 | 29.49 | 676.89 | 7.71 |
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Yang, J.; Wu, Y.; Chen, X.; Luo, B.; Wu, R.; Lin, R. Evaluation of Walkability Index for Embedded Community Services from an Age-Friendly Perspective: A Case Study of Mapple Community in Chengdu, China. Land 2025, 14, 1189. https://doi.org/10.3390/land14061189
Yang J, Wu Y, Chen X, Luo B, Wu R, Lin R. Evaluation of Walkability Index for Embedded Community Services from an Age-Friendly Perspective: A Case Study of Mapple Community in Chengdu, China. Land. 2025; 14(6):1189. https://doi.org/10.3390/land14061189
Chicago/Turabian StyleYang, Jing, Yuqiu Wu, Xuemei Chen, Binjie Luo, Ran Wu, and Rong Lin. 2025. "Evaluation of Walkability Index for Embedded Community Services from an Age-Friendly Perspective: A Case Study of Mapple Community in Chengdu, China" Land 14, no. 6: 1189. https://doi.org/10.3390/land14061189
APA StyleYang, J., Wu, Y., Chen, X., Luo, B., Wu, R., & Lin, R. (2025). Evaluation of Walkability Index for Embedded Community Services from an Age-Friendly Perspective: A Case Study of Mapple Community in Chengdu, China. Land, 14(6), 1189. https://doi.org/10.3390/land14061189