1. Introduction
Social infrastructure is defined as a complex system of facilities, programs, and social networks that aim to improve the quality of life [
1]. It includes educational, medical, cultural, and sports facilities that are essential for the everyday life of citizens. Central and local governments have developed a social infrastructure plan to ensure the following: (1) the areas are sufficiently supplied with social infrastructure; (2) social infrastructure is as equitably distributed as possible; (3) social infrastructure is effectively and efficiently configured so that service providers can flexibly respond to changing local community needs over a long time period [
2]. New towns or cities built through systematic planning are generally considered to have an adequate level of social infrastructure facilities. However, old towns or cities do not have an adequate level of social infrastructure. Local governments that administer old towns are interested in improving social infrastructure. Accordingly, financial investment is increasing in these regions.
The scope and definition of a social infrastructure varies depending on the characteristics and circumstances of a country. In Melbourne, Australia, swimming pools, recreation centers, community conference spaces, nurseries, libraries, senior welfare facilities, disabled welfare facilities, parks, hospitals, elementary schools, and middle schools are defined as social infrastructure [
3]. In Germany, public services include education, welfare, health care, community, electricity, and water and sewage, which are basic services in everyday life of the people [
4]. London, UK, social infrastructure includes health and social care, education, childcare center, recreation facilities, public toilets, and burial space [
5]. Facilities and services necessary for a city are classified into culture, welfare, childcare, education, health care, commerce, and finance, which include facilities and services such as childcare centers, kindergartens, schools, hospitals, markets, welfare centers, post offices, and banks in Japan [
6].
There have been two approaches to social infrastructure planning in cities. The first is a population-based approach, and the other is an access-based approach. An example of a population-based approach is presented in Healthy Urban Planning. Basic social infrastructure is needed within 1 km of the home for the community of 4000 to 5000 people [
7]. Similarly, the only criterion for providing social infrastructure in South Korea was the population or number of households in the region. However, if only the population is considered in social infrastructure planning, the convenience of the residents might be overlooked. For example, a study found that the average distance from old-age, low-rise housing to social infrastructure in some areas in South Korea was approximately 2.7 km [
8]. The elderly cannot walk 2.7 km to use the facilities. Therefore, these social infrastructure facilities do not effectively increase the convenience or quality of life of residents.
In order to resolve this problem, the Korea Ministry of Land, Infrastructure, and Transport (KMoLIT) put forward access-based guidelines in 2018 for social infrastructure planning. The new guidelines use travel time to a facility (on foot or by vehicle) as the threshold for determining the satisfaction in terms of residents’ convenience [
9]. For example, the Korean government is planning to build a park so that anyone can use the park within 15 min of walking from home. This threshold seems reasonable because although sufficient social infrastructure facilities are provided in a region, they do not enhance residents’ satisfaction and quality of life if they are located in a poorly accessible location. However, any explicit method of evaluating the accessibility of social infrastructure facilities has not been proposed.
The present study proposes a comprehensive evaluation method for social infrastructure planning regarding accessibility, as shown in
Figure 1. This method consists of two steps: (1) evaluating the overall accessibility of social infrastructure in a region such as a neighborhood (town) or city by computing the Accessibility Index (AI) and (2) identifying the social infrastructure “blind area” of the region. AI is an index representing accessibility to a region’s social infrastructure. A social infrastructure blind area is a residential area with poor access to social infrastructure. The overall research process was conducted using Geographic Information Systems (GIS). Data collection, manipulation (such as joining the spatial and non-spatial data), spatial-query analysis, and spatial display were performed using GIS. In addition, a navigation application programming interface (API) was employed to calculate the walking time and vehicle travel time between a residence and a social infrastructure facility.
The social infrastructure facilities investigated in this study are elementary schools, parks, childcare facilities, kindergartens, sports facilities, and libraries. Elementary schools, neighborhood parks, childcare facilities, kindergartens, neighborhood sports facilities, and neighborhood libraries are town-level facilities that citizens can generally use within walking distance. City parks, city sports facilities, and city libraries are city-level facilities relatively more extensive than the town-level facilities, and citizens usually drive to use them. The reasons for setting up the research facilities are as follows: First, these facilities are usually provided and operated mainly by the public; thus, more careful planning is required. Second, we selected the facilities that can guarantee data reliability. Data on the information of facilities, such as usage, size, and location, were obtained through local governments. Finally, the proposed method was applied to a real case in Namdong-gu, Incheon, South Korea.
2. Accessibility
Accessibility, which is mainly measured by travel distance or travel time, can be calculated using various methods. First, buffer analysis is a method of evaluating an area within which access is good based on the boundaries created by a set of points within a specific distance based on a facility. Lim et al. [
10]. analyzed the accessibility of natural green spaces and urban parks according to the income-class factors in South Korea. GIS buffer analysis was used to measure the accessibility of local green spaces and urban parks. Ashiagbor et al. [
11] measured the accessibility of healthcare facilities in Ashanti, Ghana. They identified the accessible areas using buffer analysis around the healthcare facilities. Wang et al. [
12] used buffer analysis to measure the accessibility score of care facilities by residents in residential care facilities in Guangzhou, China.
Second, network analysis in GIS has been used to measure accessibility. For example, Islam and Aktar [
13] proposed measuring the accessibility to health services in Khulna, Bangladesh. The travel time-based accessibility measurement method was proposed by computing the average travel time to the nearest hospital using various modes of transportation. Chen et al. [
14] and Hu et al. [
15] used the two-step floating catchment area to measure the accessibility of healthcare services and urban parks. The distance was measured using road network analysis to calculate the accessibility.
Finally, the navigation API has been recently used for accessibility calculation. Several studies have been performed using navigation API, such as using Google Maps to calculate the travel time. Wang and Xu [
16] compared the travel time provided by Google Map Navigation API, which was calculated using the road network provided by the GIS software. Their study proved that the navigation API of Google Maps provided more accurate results than the road network analysis using the GIS software. Haitao et al. [
17] used the Google Maps navigation API to develop a method of measuring the Beijing public transportation accessibility.
The travel time calculated using buffer analysis or network analysis in GIS may not be accurate because it does not reflect the actual resistance, such as the crosswalks and slopes of walkways. However, the travel time provided by a navigation API is more accurate because it can reflect various resistances on the roads. Therefore, navigation API was employed to calculate the travel time to social infrastructure facilities in this study. The navigation API has not been used for the accessibility calculation of social infrastructure planning in South Korea.
5. Discussions
From the results, we can evaluate the overall accessibility of social infrastructure for residents. From the AIs, we found that neighborhood libraries are needed in Unyeon-dong, Jangsu-dong, and Namchon-dong. For example, the residents in Unyeon-dong spend 24.7 min on average to use neighborhood libraries. As previously mentioned, the South Korean government recommends 10 to 15 min to reach a neighborhood library from home. In particular, Unyeon-dong demonstrated poor accessibility in most facility types, such as parks, sports facilities, and childcare centers. Jangsu-dong also has poor accessibility to kindergartens and elementary schools. It was found that more kindergartens should be built in Mansu4-dong to improve accessibility.
Most of the dongs in Namdong-gu had satisfactory AIs for city-level facilities. They have reasonable accessibility to city libraries, city parks, and sports facilities. However, the AIs show that Ganseok1-dong, Ganseok2-dong, Ganseok4-dong, and Jangsu-dong have poor accessibility to city parks. Therefore, the Namdong-gu authorities should consider city parks first among city libraries, city parks, and sports facilities for social infrastructure planning.
As shown in the social infrastructure blind maps in
Figure 5, it was found that residents in the left bottom area of Namdong-gu have poor access to libraries, sports facilities, childcare centers, kindergartens, and elementary schools. This is because there are industrial complexes in the area. In this case, it is necessary to interpret the map carefully. For city-level facilities, the left bottom area of the map shows poor access to city libraries (
Figure 6a), whereas the top area of the map shows poor accessibility to city parks (
Figure 6b). Therefore, urban planners should consider geographical and social situations. For example, the type of facilities that residents mainly use may vary depending on the age distribution of the residents. Parks and libraries are facilities for all ages, while kindergartens, elementary schools, and childcare centers are facilities for specific ages.
The comprehensive accessibility evaluation method proposed in this study provides the following advantages:
The limitations of this study are as follows. First, we only dealt with accessibility to social infrastructure on the assumption that the capacity of the facilities is sufficiently satisfied. However, the capacity that represents the facility’s size, such as a park area and the number of library seats, should also be considered when social infrastructure planning. Second, we assumed that residents use only facilities located in the study area, Namdong-gu. However, residents living near the administrative boundary can use facilities outside the study area. Third, the shortest linear distance was used to match an RB and the nearest facility at a ratio of 1:1. In this case, the distance may be the closest, but the travel time may not be the shortest.