DOI: 10.3303/CET24113023 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Paper Received: 5 May 2024; Revised: 12 August 2024; Accepted: 1 November 2024 
Please cite this article as: She J., 2024, GIS-Based Urban Green Spaces Accessibility Analysis from the View of Transportation: A Case Study 
of Hong Kong, Chemical Engineering Transactions, 113, 133-138  DOI:10.3303/CET24113023 
  

 CHEMICAL ENGINEERING TRANSACTIONS  
 

VOL. 113, 2024 

A publication of 

 

The Italian Association 
of Chemical Engineering 
Online at www.cetjournal.it 

Guest Editors: Jeng Shiun Lim, Bohong Wang, Guo Ren Mong, Petar S. Varbanov 

Copyright © 2024, AIDIC Servizi S.r.l. 

ISBN 979-12-81206-14-4; ISSN 2283-9216 

GIS-Based Urban Green Spaces Accessibility Analysis from 

the View of Transportation: a Case Study of Hong Kong  

Jingcao She 

Sino-Portuguese Centre for New Energy Technologies (Shanghai) Co., Ltd. 

shejingcao@sidri.com 

Public green spaces have gradually proved to be a key element in promoting sustainable urban development. 

Green spaces are both the most important natural landscape of a city and provide accessible green spaces for 

activities that meet the recreational needs of urban residents. If parks are convenient and accessible to 

residents, they can increase the probability of residents participating in outdoor physical activity, improve their 

physical and mental health, and alleviate their potential physical and mental fatigue. This study proposes an 

evaluation method for urban green space accessibility with the aim of improving residents' well-being. Taking 

Hong Kong Special Administrative Region (SAR), China as an example, the study analyzes the impact of 

transportation on urban green space accessibility. The methodologies are network analysis and kernel density 

analysis based on the ArcGIS software analysis platform. Research shows the walking time of urban parks is 

almost maintained within 14 min in Hong Kong, but the North District with higher green spaces resources have 

lower accessibility. In this context, this study makes recommendations for policymakers from the perspective of 

transportation and road system construction based on results. One of the study recommended conclusions is 

to reduce the number of dead-end roads in the city, develop urban slow-moving road systems such as walking 

and bicycling, and establish good transportation conditions to improve the accessibility of parks. 

1. Introduction 

Majority of the world's population is migrating to cities, especially in developing countries promoted the 

urbanization process. World Bank reported more than half of the world's population currently lives in cities, and 

predicted the urban population is expected to account for two-thirds of the total urban population by 2050. The 

acceleration of urbanization leads to the occupation of green space in cities, directly leads to the high 

fragmentation degree of urban green space, which in turn leads to many social environment and residential life 

problems. Urban green space, defined as open areas designated in land use planning for parks and other "green 

spaces" (e.g., plants, water features and other kinds of natural habitats) (Palliwoda and Priess, 2021), which 

are gradually proved to be one of the key elements in promoting sustainable urban development. As the most 

important component of the urban natural landscape, green space provides significant ecological services for 

urban residents, such as regulating the local microclimate, improving air quality, managing rainwater and floods 

(Paudel and States, 2023). 

Urban green public space can also meet the needs of urban residents by creating and maintaining public spaces 

and natural environments for social interaction, healthy interpersonal interactions and social equity are promoted 

(Pasanen et al., 2023). In addition, the probability of people participating in outdoor physical activity increases 

if parkland is easily accessible to residents (Kondo et al., 2018). At the same time, it can provide residents with 

activity or exercise space to improve their physical and mental health and alleviate their potential physical and 

mental fatigue (Wolch et al., 2014).Studies have found that in areas where public green space is not easily 

accessible in cities, people's obesity rate and death risk are correspondingly higher(Semeraro et al., 2021). 

Urban green space accessibility also can contribute to carbon emission reduction. Green land vegetation can 

play a role in CO2 sequestration and thus play a role in climate change mitigation. Comparing carbon sink 

estimates with total urban CO2 emissions benefits municipalities for appropriate green space planning to 

increasing carbon sinks while reducing CO2 emissions. Given the importance of urban green space, a systematic 

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and comprehensive understanding of the accessibility of urban green space in the process of rapid urbanization 

can help to formulate appropriate green policies that benefit residents. 

Hong Kong is one of an emblematical cities in the world with largest population density and limited space, and 

following the compact development model requires the concentration of floor space and comprehensive 

allocation of urban functions in the city center. BBC mentioned that public green space accounts for 40 % of 

total land use in Hong Kong, much higher than in London or New York. However, deeper research shows that 

the majority of citizens live on less than a quarter of Hong Kong's land, yet Hong Kong's largest parks are located 

in less densely populated areas, with some Hong Kong residents taking an average of one hour to reach a major 

country park. Civic Exchange Charity research report showed that compared to other cities, Hong Kong has 

very little outdoor recreation space available to the public, only about 2.7 m2 per resident; Singapore, which is 

smaller than Hong Kong, has 7.4 m2 of urban public space per capita.  

Kwak et al. (2024) through a comprehensive analysis of transportation, environment, health, spatial 

restructuring, and economic aspects using the Seoul Green Transportation Zone as a research case, the 

effectiveness of travel demand management (TDM) in reducing greenhouse gas emissions and promoting urban 

sustainable development has been demonstrated. Jeong et al. (2023) A specially tailored algorithm for personal 

mobility has been proposed, and an effective path combining personal mobility characteristics has been 

proposed as an alternative to traditional transportation to improve the accessibility of metropolitan railways in 

metropolitan areas. In this study, aims to adopt the network analysis module method and kernel density analysis 

method of ArcGIS to explore the accessibility of urban green space by taking Hong Kong as a case study, and 

provides references for urban public green spaces design and its optimal layout in urban planning from a 

transportation perspective, so that more urban residents can enjoy urban green space resources more 

conveniently. 

2. Methodology 

2.1 Simple buffer method 

A buffer zone is established at the centre of the park, with the maximum service distance as the radius, in order 

to facilitate the easy reach of the park by people within the buffer zone (Kun et al., 2012). Conversely,  buffer 

zone are unable to enjoy the park services, either in the form of a point buffer and a surface buffer. 

This approach employs a straight line to measure the service radius, which fails to account for the heterogeneity 

of the urban landscape and the existence of natural and man-made landscape barriers to park accessibility (Oh 

and Jeong, 2007). As a result, the service area of the park is often overstated and accessibility overestimated. 

Furthermore, this approach assumes that all urban park boundaries are park access points, in reality, not all 

boundary points are accessible. Consequently, this approach tends to overestimate urban parks accessibility. 

2.2 Cost-weighted distance method 

The cost-weighted distance method is based on a raster data classification of the urban landscape and employs 

a shortest path search algorithm to calculate the cumulative resistance (distance, time, cost, etc.) to reach the 

park in order to evaluate the accessibility of urban parks (Larbi et al., 2018). 

The fundamental tenet of the cost-weighted distance method is the classification of the urban landscape, 

followed by the assignment of varying relative crossing resistances, which are then employed to calculate the 

cumulative resistance of each point to the park (Gill et al., 2019). However, it still in the theoretical stage about 

the resistance understanding of citizens in the process of entering the park. (Suleiman et al., 2015). This is 

because there are only two situations in the process of reaching a certain point: traversable and non-traversable. 

The method provides a relative resistance to the classification spaces, which is challenging to accurately reflect 

the actual situation. 

2.3 Network analysis module method 

The network analysis method may be regarded as a vector version of the cost-weighted distance method based 

on the road network or the buffer method. The method integrates the barriers to entry into the park, and 

calculates the coverage of urban parks at a certain resistance value based on a road network according to a 

certain mode of transportation (Comber, et al., 2008). This method more accurately reflects the process of 

citizens entering the park in the actual way, and overcomes the obstacles in the process of measuring straight-

line distance, which cannot identify the accessibility and the resistance measurement error caused by the cost-

weighted distance method (Ahmed, et al., 2017). Network analysis extension module is an important extension 

module in ArcGIS desktop. The module can create and edit network dataset for traffic network, and also be 

performed based on the network dataset. It mainly includes the following types of analysis and processing: 

finding the optimal path, finding the service area, finding the nearest facilities, creating origin-destination cost 

matrix, and solving the problem of vehicle driving route (path planning).  

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This study employs topology analysis based on the Hong Kong road network data downloaded from Open Street 

Map (OSM) and imported into GIS. The corrected road network data is then used to establish a database and 

a network data set. The latter is employed to construct network analysis, which is then used to calculate the 

service area function in the network analysis module. The starting point is entered into Hong Kong City Park 

SHP, and the interval is set at 5 min. The results are then exported as an image, with the layout, scale, north 

arrow and legend being imported and the image being exported. 

2.4 Kernel density analysis method 

The kernel density analysis method in GIS can be applied to point, line and area feature classes in order to 

calculate the density of point, line or area features in the vicinity of each output raster cell. This type of analysis 

is applicable to a surface with a smooth topography, the surface value is highest at the location of the point and 

gradually decreases with increasing distance from the point, until it reduces to zero within the search radius 

distance (Mohaymany et al., 2013). The density of each output raster cell is the sum of the values of all kernel 

surfaces superimposed at the centre of the raster cell. Kernel density analysis can be applied to a variety of 

scenarios, and this study employs it to calculate the distribution density of the park. The process begins with 

selecting the kernel density tool, inputting the requisite elements, and then selecting the park SHP. In order to 

facilitate a more detailed analysis of the relationship between park distribution and traffic, the park density grid 

was set to 30 % transparency in GIS, and the subway stations were adjusted to eye-catching colours. The 

coordinate system employed is consistent with that of the park SHP, and the processing range is consistent with 

the Hong Kong Administrative Region. Furthermore, the range of grid analysis is also consistent with the 

boundary of Hong Kong. 

3. Results and Analysis 

3.1 Urban Green Spaces Distribution in Hong Kong 

Hong Kong is characterised by a high mountainous topography, with a relatively low level of flat land. The 

majority of the land area is submerged by the sea. Figure 1 illustrates that the majority of Hong Kong is 

mountainous, includes 20.5 % of forest land and 49.8 % of grassland and shrubs. The majority of Hong Kong's 

urban parks are situated within the built-up areas of the city, including the Eastern District, Wanchai District, 

Central and Western District, Kwun Tong District, Kowloon City District, Yau Tsim Mong District, and so forth. 

Among these districts, Kwun Tong District and Kowloon City District exhibit the highest park density. 

 

Figure 1: Distribution of Green Space and Urban Parks in Hong Kong  

3.2 Transportation and Accessibility 

Hong Kong has constructed and manages hundreds of parks of varying sizes, which are strategically located 

within the urban fabric. These parks serve as convenient rest spaces for citizens, offering a valuable public 

amenity. To analyse the distribution of urban parks and subway stations, a density analysis was conducted 

using the kernel density method. Figure 2(a) shows a clear distribution between the density of urban parks and 

the distribution of subway stations. This indicates that the greater the population density of an area, the greater 

the availability of public transportation options. Figure 2(b) indicates the road network in Hong Kong. The 

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accessibility of green space resources is contingent upon the accessibility of transportation networks, which 

means residents living in proximity to subway stations have higher green space accessibility. Nevertheless, 

there is a greater availability of green space resources in areas with limited transportation infrastructure, such 

as the North District. The distribution of green space resources is skewed towards local residents, which 

consequently results in residents of other areas being unable to access these resources effectively. 

(a) (b) 

 

 

 

Figure 2: (a) Superposition of Urban Park Density and Subway Station (b) Road Network 

In order to obtain a map of accessibility to green spaces, the study involved downloading Hong Kong road data 

from OSM website. This data was then used to establish a personal geographic database, which was 

subsequently imported into the  personal geographic database. Finally, a topology was created to repair the 

road network data. Subsequently, a network dataset was established based on the repair data, loaded into GIS, 

and the network analysis tool was opened. The new service area module was then selected, and park data was 

input at the location of the facility point. The impedance values in the layer properties were set to 5, 8, 11, 14, 

17, 20, 23, 26 and 29. After on-site exploration, it takes about 5 min to travel from the concentrated green spaces 

(Victoria Bay) in Hong Kong  to the nearest city park, while the subway travel time to the relatively distant green 

spaces (Northern Districts) is about 30 min. In this study, 5 was chosen as the first value, increasing by 3 until 

the last value of 29, ensuring that the impedance values are set within 30. 

Through using the network analysis method, Figure 3 indicates that the accessibility of urban parks tends to 

diverge from Victoria Bay to the surrounding areas.  

 

 

Figure 3: Accessibility map of Hong Kong Park Green Space  

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In areas with well-developed transportation infrastructure, the accessibility of urban parks is high, allowing more 

people to enjoy green resources. Currently, a total of 23 country parks, 15 special areas, four marine parks and 

one marine reserve account for more than 38 % of Hong Kong's total land area. However, reserve green space 

cannot be included in the scope of urban green space due to its protection status. The only accessible urban 

green space is a small number of parks located within the urban area. The good accessibility of parks in the 

urban area since the implementation of urban planning and green space conservation policies can be attributed 

to the increase in the amount of green spaces around densely populated areas. The urban development in Hong 

Kong is extremely concentrated, with a small usable land area and an extremely concentrated distribution of 

parks. The walking time of urban parks is almost maintained within 14 min, with the exception of the conservation 

of green space. However, although the country parks have better resource conditions, most of them deviate 

from the urban areas (in the North District). Although the population density in the North District is not as high 

as in the city center, according to population data released by the Hong Kong government, there are currently 

305,000 people living in there. For these residents, the lack of convenient transportation options results in a 

relatively high time requirement for commuters to reach urban parks, which in turn contributes to a below-

average level of accessibility. 

3.3 Suggestions 

The accessibility of green space in some locations is severely limited, and the park is unable to fulfil its potential 

and benefit a greater number of people. Field In Trust Agency stressed the importance of ‘locating park’. If the 

park easy for locals and visitors to find and enter or not, and whether the road to the park is suitable for both 

pedestrians and vehicles, as well as if the park can be reached by foot from the home or office. Travel time, 

economic cost, and urban traffic conditions are all factors that affect the accessibility of the park and the 

willingness of people.  It is recommended that the government implement measures to enhance the construction 

of transportation infrastructure, facilitating the convenient travel of individuals and enabling the full realization of 

the health benefits associated with green spaces. Furthermore, the availability of alternative pedestrian routes 

is constrained by the prevalence of high-grade roads, which often necessitates a circuitous route to reach the 

park, reducing the accessibility of green space within the park. In this context, it is imperative to prioritize the 

construction of infrastructure that facilitates the safe crossing of high-grade roads by residents. Secondly, 

policymakers could implement measures to reduce the number of dead ends and dead roads, actively develop 

urban slow-moving road systems such as walking and bicycles, and construct effective traffic 

conditions,enhancing the accessibility of the park. Furthermore, the establishment of green spaces within areas 

with developed transportation infrastructure, such as bus stations or subway stations, would facilitate greater 

accessibility to green space resources for a larger number of individuals. 

4. Conclusions 

In the construction process of park green spaces, it is necessary to comprehensively consider the population 

density and the actual land use nature of the surrounding environment. Different types of park green spaces 

have different accessibility requirements for different service groups. The accessibility improvement of urban 

green spaces with relatively small scale and fewer serving populations mainly lies in the improvement of local 

road accessibility and the satisfaction of the needs of medium density residents. However, large parks, such as 

country parks, theoretically have a larger service radius and serve a larger number of people. The road section 

where they are located needs to have good global accessibility, and the overall requirements for the park are 

relatively high. Excessive numbers and dense distribution of parks can affect the urban construction process to 

a certain extent, and the actual service efficiency of park green spaces will also be affected. In such densely 

populated and high demand areas, it is necessary to build urban comprehensive green spaces with higher 

quality and more comprehensive functions. This not only effectively coordinates the balance between various 

functional land uses, but also alleviates the land shortage situation and achieves supply-demand matching. 

The objective of this study is to utilize GIS technology and related software to investigate the impact of the 

subway on the accessibility of urban green space. This will be achieved by employing network analysis and 

kernel density analysis, with Hong Kong serving as a case study. The research findings demonstrate that it is 

possible to evaluate and analyse the accessibility of park green space based on ArcGIS, in conjunction with 

network analysis and kernel density analysis. The findings of this study have the potential to inform the optimal 

allocation of green space in Hong Kong parks. 

This study differs from previous research on green space accessibility in that it considers and analyses the 

effects of park green space layout and road network on accessibility in a comprehensive manner. Nevertheless, 

while this study has made significant progress, there is still room for improvement. First, in the real world, parks 

are polygonal. However, this study simplified the form of parks as ‘points’. If the polygon is assumed to be a 

point during analysis, errors may occur, and more detailed consideration of the features. Therefore, assumptions 

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of the data for spatial analysis is needed in the future. The other is due to the limitations of the data, it does not 

consider the differences in residents' choice of transportation mode and the differences in the service capacity 

of different types of park green space. These are areas that require further research. In the subsequent study, 

the CO2 reduction model based on the temperature cooling curve and spatial accessibility network analysis can 

be used to evaluate CO2 reduction potential of urban green space to further clarify the relationship between 

green space accessibility and CO2 emissions. 

References 

Ahmed S., Ibrahim R.F., Hefny H.A., 2017, GIS-based network analysis for the roads network of the Greater 

Cairo area, In Proc. of 2nd International Conference on Applied Research in Computer Science and 

Engineering. 

Comber A., Brunsdon C., Green, E., 2008, Using a GIS-based network analysis to determine urban greenspace 

accessibility for different ethnic and religious groups, Landscape and urban planning, 86(1), 103-114. 

Gill G.S., Cheng W., Zhou J., Park V.S., 2019, Comparative analysis of cost-weighted site ranking using 

alternate distance-based neighboring structures for spatial crash frequency modeling, Journal of 

Transportation Safety & Security, 11(1), 79-101. 

Jeong H., Yang M.H., Choi M., Kim S., Lee S., 2023, Environmental Sustainability Increase by Activation of 

Public Transport and Personal Mobility. Chemical Engineering Transactions, 106, 253-258.  

Kondo M.C., Fluehr J.M., McKeon T., Branas C.C., 2018, Urban green space and its impact on human health, 

International journal of environmental research and public health, 15(3), 445. 

Kwak J., Ku D., Jo J., Kim D., Bencekri M., Choi M., Lee S., 2024, Travel demand management strategies to 

mitigate climate change, In Proceedings of the Institution of Civil Engineers-Municipal Engineer, Emerald 

Publishing Limited, 1-25. 

Kun W., Hao S., Yannan X., Mingrui X., Quan Z., 2012, Accessibility analysis of urban parks based on GIS, 

In 2012 Fifth International Conference on Information and Computing Science, IEEE, 56-59. 

Lai C., 2017, Unopened space: Mapping equitable availability of open space in Hong Kong, Hong Kong, China: 

Civic Exchange, 1-104. 

Larbi E.K., Boye C.B., Peprah M.S., 2018, A GIS Approach in Optimal Route Selection in Mining Communities 

Using the Analytical Hierarchy Process and the Least Cost Path Analysis-A Case Study. In 5th UMaT 

Biennial International Mining and Mineral Conference, 50-62. 

Mohaymany A.S., Shahri M., Mirbagheri, B., 2013, GIS-based method for detecting high-crash-risk road 

segments using network kernel density estimation, Geo-spatial Information Science, 16(2), 113-119. 

Oh K., Jeong S., 2007, Assessing the spatial distribution of urban parks using GIS, Landscape and urban 

planning, 82(1-2), 25-32. 

Palliwoda J., Priess J.A., 2021, What do people value in urban green? Linking characteristics of urban green 

spaces to users' perceptions of nature benefits, disturbances, and disservices, Ecology & Society, 26(1). 

Paudel S., States S., 2023, Urban green spaces and sustainability: exploring the ecosystem services and 

disservices of grassy lawns versus floral meadows, Urban Forestry & Urban Greening, 84, 127932. 

Pasanen T.P., White M.P., Elliott L.R., van den Bosch M., Bratman G.N., Ojala A., Korpela K., Fleming L.E., 

2023, Urban green space and mental health among people living alone: The mediating roles of relational 

and collective restoration in an 18-country sample, Environmental Research, 232, 116324. 

Semeraro T., Scarano A., Buccolieri R., Santino A., Aarrevaara E., 2021, Planning of urban green spaces: An 

ecological perspective on human benefits, Land, 10(2), 105. 

Suleiman S., Agarwal V.C., Lal D., Sunusi A., 2015, Optimal route location by least cost path (LCP) analysis 

using (GIS) a case study, International Journal of Scientific Engineering and Technology Research, 4(44), 

9621-9626. 

Wolch J.R., Byrne J., Newell J.P., 2014, Urban green space, public health, and environmental justice: The 

challenge of making cities ‘just green enough’, Landscape and urban planning, 125, 234-244. 

 

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	GIS-Based Urban Green Spaces Accessibility Analysis from the View of Transportation: a Case Study of Hong Kong