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J. People Plants Environ > Volume 27(3); 2024 > Article
Kim and Min: Reclassification of Green Infrastructure Types and Functions: Focused on Matsudo City, Chiba Prefecture, Japan

ABSTRACT

Background and objective: Globally, the sustainability of urban areas is being compromised due to indiscriminate urban development, making the creation and management of green spaces increasingly critical. Green spaces play a pivotal role in connecting degraded natural ecosystems, and the concept of Green Infrastructure is gaining prominence as a strategy for managing green networks. A Green Infrastructure (GI) is a network of interconnected green spaces that provide benefits to humans through their utilization and management, fulfilling environmental, social, and economic functions. However, in most urban areas, green spaces lack connectivity between each other and are not managed in an integrated manner. Additionally, the types and functions of green spaces defined by policies and regulations vary, making it challenging to implement GI. Therefore, this study aims to examine and reclassify precursor indicators in order to effectively apply GI to urban strategies. It seeks to discuss management approaches based on GI, with the aim of facilitating its implementation.
Methods: The city of Liverpool in the UK has presented a multifunctionality strategy for GI, which has been utilized as a global exemplary case. This study adopts the multifunctionality GI strategy proposed by the city of Liverpool, and reclassifies the types and functions of GI. It selects indicators through Focus Group Interviews(FGI) with GI experts and field surveys. The selected indicators of GI were utilized in a survey for evaluation of multifunctionality. The quantitative data collected through the survey were mapped using overlay techniques, in which led to the deriving a multifunctionality map of GI. In the process of mapping, weights derived from Analytic Hierarchy Process (AHP) analysis were applied to enhance the reliability of the quantitative data from the survey.
Results: In this study, suitable indicators for GI in the study area were selected, and the functionality of each land cover (LC) type was evaluated. As a result, the study area was found to provide multifunctionality within a single land parcel. The highest-scoring LC type is Woodland, and the predominant functional category is Human-Wildlife Coexistence. The lowest-scoring LC type is Cemetery, with the least represented functional category being Timber Production.
Conclusion: GI fulfills multiple functions that provide a range of benefits to humans (multifunctionality). To maximize such multifunctionality, it is crucial to manage scores for each functional category according to LC type. GI is not solely focused on specific functions, but also requires strategies to enhance functionalities lacking in LC types with low multifunctionality scores. The GI indicators proposed in this study and the GI multifunctionality assessment can serve as essential data for review when local authorities are formulating spatial plans related to urban areas, green spaces, forests, and other relevant areas.

Introduction

Around the world, the sustainability of urban areas which for most countries, hold approximately half of the population (European Commission, 2019; UN, 2022) is being threatened by indiscriminate development (Hartmuth et al., 2008; Xing et al., 2009; Wu, 2010; Mieg, 2012; Kou and Tsou, 2015; Cohen, 2017). The fragmentation, degradation, and disconnection of green spaces within and outside of urban areas must be addressed to improve and maintain urban sustainability (Kong et al., 2010; Bakhshi, 2015; Kruize et al., 2019; Chi et al., 2020; Wang et al., 2022; Zhou et al., 2023). Green spaces not only play a key role in connecting natural ecosystems that have been isolated or degraded by urbanization, but also provide benefits to humans (Cetin, 2015; Akpinar et al., 2016; Mu et al., 2020; Vidal et al., 2020). As such, green space connectivity is attracting attention as an important means of creating sustainable cities, and research on the creation and management of green-space networks is also actively underway (Short et al., 2017; Constantinescu et al., 2019). In particular, the concept of Green Infrastructure (GI) has been in the limelight, and is being considered as a management strategy for green-space networks to achieve urban sustainability (Sandstrom, 2002; Pauleit et al., 2019; Wang, 2022; Hoover, 2023).
A GI is a network of interconnected green spaces that provide benefits to humans through their use and management (Williamson, 2003; Benedict and McMahon, 2006; Mell, 2008; Kaplan, 2012; Andreucci, 2013; Lindholm, 2017; Wang and Banzhaf, 2018; GI The Conservation Fund Web-Page, 2024). It includes different types of green spaces within natural systems and urban infrastructure, such as waterways, wetlands, agricultural lands, street trees, urban parks and gardens (Weber et al., 2006; Naumann et a l., 2011; Andreucci, 2013; Lee e t al., 2014; Zhang et al., 2022). As such, green spaces distributed within and outside urban areas have different functions for each type, and promote the performance of GI functions through interconnection (Naumann et al., 2011). GIs provide environmental and ecological functions that mitigate urban heat islands, reduce flood damage, remove air pollutants, improve water quality and provide habitat (Winslow, 2021), as well as social and cultural functions that include recreation, education and culture (Tzoulas et al., 2007). However, although GIs have the benefit of providing environmental, social and economic functions (Pitman et al., 2015; Symons et al., 2015; Parker and Baro, 2019; Honeck et al 2020; Mell and Clement, 2020; Jezzini et al., 2023), most urban green spaces lack connectivity and are not managed in an integrated manner, which limits the capacity of urban GI to actively fulfill its unique functions (Pozoukidou, 2020).
Green spaces, the most basic element of GI, are classified by land cover and are altered by human actions, including changes in land use, and development activities. Changes in land use can alter land cover, improving or maintaining the connectivity and functionality of individual green spaces (Staccione et al., 2022). Land cover (LC), which is what covers the terrestrial surface, reflects the use and function of each green space (Gregorio, 2005; Campbell and Wynne, 2011; Phiri and Morgenroth, 2017; Zaitunah et al., 2022) and is used as a tool to derive the characteristics and roles of each green space and GI (Kang and Kim, 2015; Kim et al., 2023). Based on the LC of each green space, the purpose of GI network formation and utilization plans can be established (Zang et al., 2022); such a network can provide complex functions in addition to the unique functions of GI (Stürck and Verburg, 2017; Isola et al., 2022; Hansen et al., 2019; Kim and Song, 2019). Since the multi-functionality of GI refers to the complex functions that benefit humans when a tightly connected network of green spaces is formed, spatial connectivity must be considered as essential to achieve maximum multi-functionality (Dige et al., 2011; Lähde et al., 2019; Korkou et al., 2023). As a result, when GI is combined with integrated operation and management, humans can receive many benefits from each green space and GI (Papageorgiou and Gemenetzi, 2018; Monteiro et al., 2020; Chen et al., 2022).
The UK has developed the concept of GI and applied it to actual urban planning and management. There has also been active research into the function of GI, and the network of green spaces (Llausas and Roe, 2012). Key examples of this research include studies on urban water management using GI (Ellis, 2013; Hoang and Fenner, 2016; Li et al., 2020), ameliorating urban heat islands through LC change (Emmanuel and Loconsole, 2015; Tiwari et al., 2021), the impact of green space accessibility on human public health (Leese and Zubaidi, 2023), predicting changes in biodiversity and ecosystem services based on an analysis of species and habitat patterns in cities (Brunbjerg et al., 2018), and the possibility of restoring green space in urban areas for food security (Dobson et al., 2020). As such, in the UK, GI has been considered as an important element for urban operation and management, and together with research on it in various fields, it is being applied and used in actual urban operation and management strategies (Fisher et al., 2020). For example, the city of Liverpool, UK, which is featured as a global best practice, has applied GI to the management and planning of green spaces within the city at the local government level (Kinoshita et al., 2016, Wendler et a l., 2022), and has developed and disseminated an action plan for implementation (Liverpool City, 2010). According to the Liverpool City Green Infrastructure Strategy (Liverpool City, 2010), the city has established an integrated approach to green spaces based on GI in land use planning and management, and has proposed a multi-functional GI strategy that provides various functions in addition to the natural functions unique to each green space. Specifically, each LC was classified into 17 types and 28 functions, and based on this, plans for the operation and utilization of GI were prepared by mapping the entire city.
However, we encounter the limits to the Liverpool City GI Strategy, which is attracting global attention, when we attempt to directly apply it to other urban areas (Kinoshita et al., 2016), as LC, which is the basis of GI types, is categorized by the laws and systems of each country, and thus Liverpool’s GI cannot be fully replicated (Diogo and Koomen, 2016). Japan’s population has become concentrated in urban areas due to the country’s rapid urbanization since the 1960s (Urushima, 2015). This has led to a rapid change in LC, which has reduced the amount of rainwater penetration in urban areas, resulting in severe urban flooding (Nakaguchi and Komori, 2020), and caused urban problems such as a reduction in green space due to urban sprawl and expansion (Koohsari et al., 2022). In response, the Japanese government built satellite cities to disperse the population of large cities during the bubble economy era (Yutaka, 2019), but most of these were built without considering the concepts of green space and GI (Otsuka et al., 2020), and are currently facing regional decline and need effective management (Kumada, 2002). After the Great East Japan Earthquake in March 2011, the introduction of the GI concept into urban operations and management began to be discussed in earnest, and research on the need and function of GI has continued (Iwasa, 2015). Moreover, the importance and use of GI are emphasized in the National Land Formation and Land Use Plans, which are plans for sustainable land development and management at the national level (Ministry of Land, Infrastructure, Transport and Tourism (MLIT), 2023b). However, Japan’s LC is mainly categorized by urban infrastructure facilities rather than the concept of green space, including outdoor spaces in architecture, roads, and facility maintenance, making it difficult to directly apply GI to policies and systems (Natuhara, 2018). Therefore, in order to effectively apply GI to urban strategies, it is necessary to closely examine the legal issues, including the area, use, and function of green space as defined by relevant laws and systems, as well as the types and functions of Japanese GI.
In this study, GI types and functions suitable for Japanese urban areas were reclassified based on the GI indicators of the c ity of Liverpool, UK, a global best practice. In addition, the GI types and functions proposed in this study were mapped by applying them to an actual target site. Using this as the basis, we sought to discuss sustainable management approaches for GI.

Research Methods

Study Area

The target area of this study is Matsudo City, in Chiba Prefecture, Japan, which has a total area of about 61.38㎢, and is located about 20 km from downtown Tokyo. It is adjacent to the metropolitan city of Tokyo, bordered by the Edo River to the northwest, and has developed into a suburb of Tokyo, centered on National Route 6 and the JR Joban Line, which connects to Tokyo (Matsudo City Official Web-Page, 2024). The population of Matsudo City is approximately 498,000 and has been increasing by about 0.23% per year for the past 10 years (2014 to 2023). By age, the largest demographic group is the 45–50 age group, but the largest influx of people is occurring in the 20–24 age group (Matsudo City, 2022a). This influx seems to be the result of Tokyo’s urban sprawl turning the area into one of its commuter towns (Ermilova et al., 2018) with a high commuter rate (37.9%; Ouchino News, 2024). In the past, Matsudo City, whose residents were mainly farmers, began a land improvement project in 1955, and developed industrial complexes centered on the Matsudo area (Table 1,7) and residential complexes centered on the Tokiwadaira area (Table 1––1) and Kogane area (Table 1,6), resulting in the typical characteristics of urbanization (Son and Yoon, 2011).
Yet despite this urbanization process, Matsudo City has excellent green space resources, with the distribution of green space accounting for 25% of the total area (Matsudo City, 2022b). Since the city has a large area of farmland around the Edo River in the northwest and borders the Shimosa Plateau in Chiba Prefecture in the east, there is a large area of forest and grassland that has not been developed during the urbanization process (Yoon et al., 2010). There are 29 major green spaces in the s tudy a rea, including the Forest and Park for the 21st Century located in the center of the area (Table 1), and they are preserved through the “Forest Conservation System” (Matsudo City, 2022a). As such, major green spaces in the area are managed in compliance with land use regulations. Notably, to prevent indiscriminate urban development, LC types are managed by dividing them into urban and non-urban areas based on the characteristics of the land.
In this study, LC types that are managed according to land use regulations were examined, which can be considered as GI. For the LC types used in this study, 4 types were selected for urban areas and 9 types for non-urban areas (Fig. 1). The types for urban areas include Agricultural Land, Woodland, Water Body and Other Nature, while those for non-urban areas include Ordinary Land, Public Facility Site, Cultural and Educational Site, Open Space, Derelict Land, Defense Area, Transportation Facility Site, Traffic Site and Road Site. Reclassification of LC types and reorganization of functions are required since it was challenging to apply the selected LC types directly as a GI concept, and the functions of each green space are different. Therefore, in this study, to apply the GI concept to the study area, we sought to classify them according to Japanese laws and policies based on the GI indicators of Liverpool City, UK, an excellent case.

Methods

In this study, GI indicators from Liverpool, UK, a representative case, were selected and collected, but LC types and functions of GI were reclassified to enable them to be defined according to Japanese laws and policies (Fig. 2). The reclassified types and functions were selected as indicators through focus group interviews (FGI) with GI-related experts and field surveys. The selected LC type and function indicators were used in a multifunctionality assessment survey of GI. Quantitative data collected through the survey were mapped using an overlay technique, resulting in a multifunctional map of GI. In the mapping process, weights derived through the Analytic Hierarchy Process (AHP) were applied to increase the reliability of the quantitative data obtained from the survey. In this study, GI indicators were collected and selected, and GI was mapped by conducting a multifunctionality assessment using the selected GI indicators. Based on this, we aimed to identify considerations for the effective application of the GI of the study area to the urban strategy, and to suggest implications for the proper use and management of GI in the future.

Reclassification of GI Indicators for Land Cover Types and Functions

Since the GI indicators for LC types and functions of the GI strategy of the City of Liverpool, UK (Liverpool GI Strategy) adopted in this study were difficult to apply directly to the study area in Japan, a process of reclassification of the indicators to suit the area was carried out. In the reclassification process, to ensure the rationality of each indicator, the national territory, urban, green space, and land-related plans and policy literature of Japan’s MLIT, Chiba Prefecture, and Matsudo City, the study area, were reviewed. Furthermore, a focus group interview (FGI) was conducted with a total of 10 relevant experts to secure expertise in GI: the group consisted of five holders of PhDs in landscape architecture and urban planning with research experience in GI, and five public officials who perform or have experience in urban planning and green space-related work. The GI indicators for the City of Liverpool were reclassified from 18 LC types to 13, and from 28 functions to 17, through processes of inclusion, exclusion and reclassification appropriate to the study area.
The GI LC typology reconstructed by excluding some of the Liverpool GI indicators in the process of reclassification into the Japanese LC typology is as follows (Table 2 and Fig. 3). Since the City of Liverpool classified transportation facilities such as railways and roads and industrial and commercial areas as urban infrastructure and excluded them from its GI typology, these LC types were excluded from this study. Due to the regional characteristics of the study area, there is no coastline, and management standards and spatial data are not available for green roofs and street trees, so these were also excluded. In addition, Normalized Difference Vegetation Index (NDVI) data were used to derive green spaces of Private Domestic Garden, Institutional Ground, and General Amenity Space, and spatial data were reclassified using an FGI.
The types that were excluded and integrated in the process of reconstructing the function typology indicators are as follows (Table 3). There are differences between the green travel route and recreation functions in Liverpool and the corresponding definitions in Japan. The green travel route function in Liverpool was defined as green space for pedestrians and bicycle paths, but it was excluded in Japan, as it corresponds to general roads. The recreation function was checked and integrated through a field survey, as the scope and purpose of use of public and private spaces in Liverpool differ from those in Japan.
In Japan, the Corridor for Wildlife function is separately designated and managed as a management a rea, but s ince this function is not designated in the study area (Chiba Prefecture, 2022), it is difficult to determine. Therefore, it was replaced by the human-wildlife coexistence function (Sefi Mekonen, 2020) to include both the Habitat and Corridor for Wildlife functions. In addition, in Japan’s National GI Strategy (Ministry of Land, Infrastructure, Transport and Tourism, 2023a), the functions of soil/water pollutant removal, air pollutant trapping, and carbon absorption and storage are integrated into the soil/water pollutant removal function, and the functions of rainwater infiltration, conveyance, and interception are integrated into the disaster prevention function.
The characteristics of the selected GI indicators are as follows (Table 4). While the LC types were classified into physical factors (Jones et al., 2022), natural factors (Fatti et al., 2019) and productive factors (Oh et al., 2007), the function types were classified into social function (Mansor and Said, 2008), economic function (Maes et al., 2015) and ecological function (Jim, 2013). Based on this, we sought to examine the characteristics of the study area to identify what benefits the GI indicators provide to people.

Functional Assessment by GI Land Cover Type

After reviewing the GI LC typology used in Liverpool, UK, a globally advanced case of GI strategy, each LC type and function was reclassified to match the status of Matsudo City, Japan, the study area (Table 2 and 3). I n this process, a direct survey of relevant specialists/majors was conducted to verify the objectivity, representativeness, and rationality of the LC types and each function. Moreover, to compensate for the limitations of the survey, an FGI was conducted with experts, and the relative importance was derived using the AHP method (Table 5). Since relative importance is used to calculate weights to compensate for the limitations of the spatial data-based scoring process (Shin, 2015; Min, 2016; Min et al., 2019), specialist weights were assigned to the results of the specialist survey to derive realistic and convincing results.
A direct survey of 41 graduate students majoring in landscape architecture or urban planning, who had lived in the study area for at least five years and had GI expertise, was conducted using a questionnaire that included photos of the area in 2018 and a description of the photos. A 3-point scale was used to ensure smooth scoring of the survey responses. The degree of all functions for each LC type was assessed by assigning a score of 0, 1, or 2 for each question.
The AHP was implemented based on the decisions/judgments of ten experts who participated in a FGI in the process of reconstructing GI LC type and function indicators. They were interviewed using a 9-point scale method and an AHP Excel template to compare the relative importance of each LC type (Goepel, 2013). The consistency index of the judgments was verified (less than 0.1), three categories of LC types were classified, and pairwise comparisons were made between each of the 15 LC types.

Results and Discussion

Function scores for each GI were derived for each LC type through a survey. They indicated the degree of function of the relevant land types, which was converted into a score. For each LC type, the function scores were added up to derive the multifunctionality score and rank, and for each function, the function scores of each LC type were also added up to derive the total function score and rank (Table 6). A GI multifunctionality map was constructed by overlaying and mapping the multifunctionality scores for each LC type (Fig. 4).
The higher the score for each function, the lower the degree of external disturbance and damage, indicating that the function is well served in the LC type. The lower the score, the more urbanization has already occurred, indicating a need for conservation or management of the function. The LC type with the highest multifunctionality score was found to be “Woodland,” followed by “Water Body,” “Water Course,” “Wetland” and “Orchard.” Meanwhile, “Cemetery” has the lowest multifunctionality score of all LC types, followed by “Derelict Land,” “General Amenity Space,” “Outdoor Sports Facility” and “Private Domestic Garden.” Examining the multifunctionality scores based on factor categories for LC types (Table 4), it was found that natural factors had high scores and physical factors had low scores. In addition, the function with the highest score was “Human-Wildlife Coexistence,” followed by “Evaporative Cooling,” “Inaccessible Water Storage,” “Aesthetic” and “Recreation.” Meanwhile, the “Timber Production” function was found to have the lowest scores of all GI functions, followed by “Biofuel Production,” “Food Production,” “Cultural Assets” and “Heritage” functions.
Comparing the function scores for each LC type, the LC type with the highest GI function score was “Woodland,” accounting for 6.4% (24.09㎡) of the study area. “Woodland” was analyzed to have overwhelmingly higher ecological function scores than the other functional categories of LC types, with Human-Wildlife Coexistence having the highest score, followed by Shading from Sun, Wind Shelter, Evaporative Cooling, Noise Absorption and Removal of Pollutants from Soil/Water. However, it has low scores for social and economic functions, with Food Production having the lowest score, followed by Cultural Assets, Biofuel Production, Heritage, Timber Production and Learning. Notably, it was found that “Woodland” provides multiple benefits: an ecological environment suitable for habitat (e.g., sun and wind shelter for humans and wildlife), a social environment (learning and recreation), and economic resources (timber and biofuel). A field survey revealed that the forest areas in the study area, which correspond to “Woodland,” had various plant communities, including deciduous and coniferous forests and bamboo forests, and were maintained in a natural state without damage or disturbance by humans (Table 7). On the other hand, the LC type with the lowest GI function score was “Cemetery,” accounting for 4.5% (1.09㎢) of the total area. “Cemetery” had high scores for social and ecological functions, with Heritage having the highest score, followed by Cultural Assets, Human-Wildlife Coexistence, Aesthetic, Accessible Water Storage and Disaster Prevention, while it had low scores for economic functions, with Timber Production having the lowest score, followed by Biofuel Production, Food Production and Wind Shelter. For “Cemetery,” it seems that only its social functions were emphasized, including history and culture, and its environmental and economic functions were considered very low, thus it was not recognized as GI. In fact, in 1980, a large-scale cemetery was built at the national level within the study area to meet the demand for cemeteries due to population growth in Tokyo. Only half of the total area of the cemetery consisted of graves, and the remaining area consisted of open spaces (e.g., plazas and green areas) corresponding to the GI LC types, and habitats of Pinus densiflora, Pinus thunbergii, and Zelkova serrata, as well as various shrub forests, with their good management status confirmed by a field survey (Table 7). Various educational and promotional actions are needed to change the perception of “Cemetery” as a GI LC type.
By conducting a multifunctional analysis, it was found that the LC types of natural factors categorized in Table 4 have high function scores, and what they provide corresponds to ecological functions. In other words, the LC types of Woodland, Water Body, Water Course, and Wetland provide the ecological functions of “Human-Wildlife Coexistence,” “Shading from Sun,” “Wind Shelter,” “Evaporative Cooling” and “Noise Absorption.” As these LC types may be under pressure from urban development and are vulnerable to damage by humans, their ecological function must be maintained through special and ongoing management. There are LC types with low multifunctionality scores that only have high scores for specific functions; continuous, multi-faceted measures should be sought to improve their low-scoring functions.
To maximize the multifunctionality of GI, which provides various benefits to humans, it is important to manage the score for each function according to the LC type. By analyzing the scores of each function, it was found that the scores of ecological functions were significantly high and those of social functions were significantly low. In other words, the study area has not provided the maximum possible benefits to humans due to the large variance in the scores for each function. LC types with low multifunctionality scores that focus only on specific functions will require actions to increase scores for functions other than those specific functions. Moreover, when promoting the maintenance or development of non-GI elements, including buildings and roads, it is necessary to consider ways to enhance the social functions of the study area that are lacking. If the study area obtains equal function scores by resolving the areas in which functions are inadequate, its multifunctionality scores will be higher, increasing the benefits to humans.

Conclusion

In this study, Japanese GI type and function indicators were reclassified, reorganized, and applied to the actual target site based on Japan’s green space-related laws and systems. The multifunctionality scores for each GI type were the highest for Woodland and the lowest for Cemetery. The scores for each GI function were the highest for Human-Wildlife Coexistence, and the lowest for Timber Production. Woodland had the highest function scores for Human-Wildlife Coexistence and Shading from Sun, and the lowest for Food Production. Meanwhile, Cemetery had the highest function score for Heritage and the lowest for Timber Production. Considering the operation and management aspects of GI, Woodland requires continuous conservation and management as it provides shade from sun and wildlife habitat. Meanwhile, although Cemetery had a high heritage value, most of its function scores were lower than those of other land types. For this reason, it can easily be considered a non-functional LC and may be under constant development pressure. Furthermore, there should be ongoing discussions about actions to maximize the historic value of Cemeteries or actions to improve the multifunctionality score by applying other functions to improve the scores for each function.
The Japanese GI and function typology suggested in this study seems sufficient to be used as basic data that should be reviewed when each local government in Japan makes spatial plans related to cities, green spaces, forests, and more. However, to develop the methodology more realistically, the status of the study area needs to be analyzed sufficiently and thoroughly. Moreover, in addition to the professional knowledge of experts, it is necessary to explore in depth the GI types and functions that ordinary study area residents think about, as well as their satisfaction with and improvements to the current GI. Proper use and appropriate management plans for GI are needed to obtain sustainable benefits from nature.

Fig. 1
Map of Study Area and Land Cover Status. Source : Matsudo City Official Web-Page, 2024 and Matsudo City Town Improvement Dept, Urban Planning Div. (2018. updated data).
ksppe-2024-27-3-217f1.jpg
Fig. 2
Research Process.
ksppe-2024-27-3-217f2.jpg
Fig. 3
Matsudo City’s Land Cover Typology of GI Map.
ksppe-2024-27-3-217f3.jpg
Fig. 4
GI Multifunctionality Map of Matsudo City.
ksppe-2024-27-3-217f4.jpg
Fig. 5
Benefits Rate by GI Land Cover Typology in Matsudo City.
ksppe-2024-27-3-217f5.jpg
Fig. 6
Benefits Rate by GI Function Typology in Matsudo City.
ksppe-2024-27-3-217f6.jpg
Table 1
General Conditions of Matsudo City
Number Area/㎢(%) Population Significant Green Resources
1 Tokiwadaira / 11.2㎢ (18%) 95,749 Shobu Park, Mutsumi Dai 2 Park, Tokiwadaira Park, Kanegasaku Park, Kanegasaku Natural Park, Forest and Park for the 21st Century, Special Green Space Conservation Area
2 Tobu / 9.0㎢ (14%) 41,606 Moeginokaze Park, Higashimatsudo Central Park, Higashimatsudoyuinohana Park
3 Akira / 7.1㎢ (11%) 39,876 Matsudoundo Park, conservation forest area, Special Green Space Conservation Area
4 ShinMatsudo / 5.9㎢ (9%) 62,766 Shinmatsudo Central Park, Shinmatsudominami Park, Yokosuka Central Park
5 Yagiri / 4.9㎢ (8%) 22,010 kakinokidai Park, Special Green Space Conservation Area
6 Kogane / 4.9㎢ (8%) 48,332 Kogane Park, Oyaguchi Historical Park, Special Green Space Conservation Area
7 Matsudo / 4.3㎢ (7%) 52,058 Sagamidai Park, Nijusseiki Park, Minamihanashima Park, Matsudo Central Park, Tojogaoka Historical Park, Special Green Space Conservation Area
8 Mabashi / 4.3㎢ (7%) 37,952 Hachigasaki Park, Special Green Space Conservation Area
9 K ogasaki / 3.5㎢ (5%) 52,234 Kogasaki Dai 2 Park
10 Koganehara / 3.3㎢ (5%) 22,576 Penguin Park, Koganehara Park, Kurigasawa Park
11 Mutsumi / 3.0㎢ (4%) 23,168 Mutsumi Central Park
Total 61.38㎢(100%) 498,327 -
Table 2
Selected Indicators for Land Cover Typology of GI
Liverpool of U.K. GI land typology Matsudo of Japan Land Cover typology Selection Matsudo of Japan GI Land Cover typology Remarks
Agricultural land Agricultural land Rice field Agricultural land
Orchard Field Orchard
Allotment Grazing land Allotment
Wetland Grassland, moorland, Wetland Reclassification Wetland
Grassland or moorland Grassland or moorland
Woodland Woodland Woodland
Water body Water body Water body
Water course Other nature (River, aqueducts and running water) Water course
Private domestic garden Ordinary land Residential land Reclassification Private domestic garden NDVI
None Commercial land Exception
None Industrial land Exception
Institutional grounds Public facilities site Reclassification Institutional grounds NDVI
General amenity space Cultural and education site Reclassification General amenity space NDVI
Park or public garden Open Space Reclassification Park or public garden
Cemetery Cemetery
Outdoor sports facility Outdoor sports facility
Derelict land Derelict land Derelict land
Street trees None Exception
Green roof None Exception
Coastal habitat None Exception
None Defense area Exception
None Transportation facility site Exception
None Traffic site Exception
None Road site Exception

Source : Matsudo City, Town Improvement Dept, Urban Planning Div(2018. updated data)

Table 3
Selected Indicators for GI Function Typology
Liverpool of U.K. GI Function Typology Selection Japan’s GI Function Typology Reference
Recreation public Integration Recreation Japanese Forestry Agency Web-Page, 2024a
Recreation private
Recreation public with restrictions
Aesthetic Aesthetic Saitama Prefecture Web-Page, 2024
Shading from sun Shading from sun Ministry of Land_Infrastructure_Transport and Tourism, 2016
Evaporative cooling Evaporative cooling Ministry of Land_Infrastructure_Transport and Tourism, 2017
Noise absorption Noise absorption Ministry of Environment_Government of Japan Web-Page, 2024a
Habitat for wildlife Integration Human-wildlife coexistence Chiba Prefecture, 2022
Corridor for wildlife
Heritage Heritage Ministry of Foreign Affairs of Japan Web-Page, 2024a
Cultural asset Cultural asset Ministry of Foreign Affairs of Japan Web-Page, 2024b
Carbon storage Integration Pollutant removal from soil/water Ministry of Environment_Government of Japan, 2019
Pollutant removal from soil/water
Trapping air pollutants
Soil stabilisation
Food production Food production Ministry of Agriculture_Forestry and Fisheries Web-Page, 2024b
Timber production Timber production Kyushu Forest Management Bureau Web-Page, 2024
Biofuels production Biofuels production Japanese Forestry Agency Web-Page, 2024b
Wind shelter Wind shelter Hokkaido Forestry Bureau Web-Page, 2024
Learning Learning Ministry of Environment_Government of Japan Web-Page, 2024
Flow reduction through surface roughness Integration Disaster Prevention Ministry of Land_Infrastructure_Transport and Tourism Web-Page, 2024
Water conveyance
Water interception
Water infiltration
Accessible water storage Accessible water storage Ministry of Land_Infrastructure_Transport and Tourism, 2018
Inaccessible water storage Inaccessible water storage Ministry of Land_Infrastructure_Transport and Tourism, 2018
Coastal storm protection Exception None
Green travel route Exception None
Table 4
Characteristics of GI Typology
Category GI Typology
Land Cover Physical factors General amenity space, Outdoor sports facility, Open Space, Derelict land, Cemetery
Natural factors Institutional grounds, Woodland, Water body, Grassland, Private domestic garden, Wetland, Water course
Productive factors Agricultural land, Allotment, Orchard

Function Social function Recreation, Learning, Cultural asset, Heritage, Aesthetic
Economic function Food production, timber production, Biofuels production
Ecological function Coexistence between human and wildlife, Shading from sun, Wind shelter, Evaporative cooling, Noise absorption, Disaster Prevention, Pollutant removal from soil/water, Accessible water storage, Inaccessible water storage
Table 5
AHP Analysis Results
Criteria Relative Importance
1. Physical factors 5.50%
 1-1. General amenity space 0.77%
 1-2. Outdoor sports facility 0.91%
 1-3. Open Space 2.43%
 1-4. Derelict land 0.88%
 1-5. Cemetery 0.51%
2. Natural factors 77.20%
 2-1. Institutional grounds 2.44%
 2-2. Woodland 20.79%
 2-3. Water body 17.14%
 2-4. Grassland 4.85%
 2-5. Private domestic garden 2.28%
 2-6. Wetland 10.89%
 2-7. Water course 18.80%
3. Productive factors 17.30%
 3-1. Agricultural land 5.52%
 3-2. Allotment 3.82%
 3-3. Orchard 7.96%
Table 6
Evaluation of the GI Typology Based on Land Cover and Functions
GI Function Typology



GI Land Cover Typology Recreation Learning Cultural assets Heritage Aesthetic Food production Timber production Biofuels production Coexistence between human and wildlife Shading from sun Wind shelter Evaporative cooling Noise absorption Pollutant removal from soil / water Accessible water storage Inaccessible water storage Disaster Prevention Score Rank
General amenity space 0.331 0.316 0.185 0.185 0.193 0.054 0.015 0.015 0.092 0.169 0.177 0.031 0.031 0.015 0.062 0.085 0.046 2.002 13

Outdoor sports facility 0.499 0.454 0.118 0.109 0.227 0.009 0.018 0.018 0.054 0.118 0.082 0.054 0.045 0.036 0.064 0.127 0.100 2.133 12

Open Space 1.532 1.386 0.875 0.924 1.361 0.267 0.194 0.292 1.240 1.459 1.410 1.337 1.288 1.288 1.313 1.459 1.386 19.010 10

Derelict land 0.123 0.079 0.062 0.044 0.079 0.062 0.026 0.070 0.194 0.114 0.114 0.123 0.070 0.097 0.141 0.220 0.123 1.742 14

Cemetery 0.051 0.056 0.123 0.184 0.077 0.015 0.005 0.010 0.087 0.046 0.041 0.046 0.046 0.046 0.072 0.061 0.072 1.038 15

Institutional grounds 1.393 1.271 1.149 1.149 1.540 0.122 0.220 0.293 1.222 1.515 1.418 1.515 1.515 1.320 1.320 1.344 1.369 19.674 9

Woodland 12.267 11.851 7.693 9.980 11.851 4.366 11.851 8.732 13.930 13.930 13.722 13.722 13.722 13.722 12.890 13.514 12.682 200.424 1

Water body 10.114 9.428 6.685 7.200 10.628 3.600 0.857 2.914 11.314 7.200 5.143 9.771 7.543 7.200 7.371 8.914 8.400 124.281 2

Grassland 0.775 0.727 0.388 0.388 0.727 0.097 0.097 0.775 2.665 0.727 1.066 1.938 1.890 1.987 1.938 2.229 2.229 20.644 8

Private domestic garden 0.981 0.684 0.456 0.479 0.981 0.319 0.228 0.319 1.118 1.323 1.186 1.255 1.163 1.095 1.049 1.118 1.118 14.872 11

Wetland 6.101 6.101 4.140 4.793 6.427 2.179 2.724 5.120 7.081 5.120 3.595 6.101 5.338 6.645 5.992 5.556 5.556 88.568 4

Water course 10.905 10.341 6.581 7.145 12.033 3.760 0.188 2.820 12.221 6.581 2.820 11.281 7.145 5.829 7.521 9.213 4.700 121.084 3

Agricultural land 1.490 2.207 0.773 1.104 2.042 3.532 0.331 1.159 2.649 0.441 0.497 2.097 2.152 2.207 2.428 3.090 2.870 31.070 6

allotment 1.376 1.568 0.573 0.535 1.147 2.447 0.421 0.994 1.759 0.612 0.612 1.529 1.568 1.529 1.720 2.179 1.835 22.405 7

Orchard 3.263 3.661 1.273 1.830 3.104 5.252 2.308 2.547 4.059 4.536 4.695 4.536 4.377 4.536 4.536 4.934 4.775 64.221 5

 Score 51.201 50.129 31.073 36.048 52.416 26.082 19.483 26.080 59.685 43.891 36.577 55.337 47.894 47.553 48.416 54.043 47.260 /

 Rank 5 6 14 13 4 15 17 16 1 11 12 2 8 9 7 3 10
Table 7
Land Cover typology of Woodland and Cemetery
Woodland Cemetery
ksppe-2024-27-3-217f7.jpg ksppe-2024-27-3-217f8.jpg

References

Akpinar, A., C. Barbosa-Leiker, K.R. Brooks. 2016. Does green space matter? Exploring relationships between green space type and health indicators. Urban Forestry &and Urban Greening. 20:407-418. https://doi.org/10.1016/j.ufug.2016.10.013
crossref
Andreucci, M.B. 2013. Progressing Green Infrastructure In Europe. WIT Transactions on Ecology and the Environment. 179(10):413-422. https://doi.org/10.2495/SC130351
crossref
Bakhshi, M. 2015. The position of Green Space in Improving Beauty and Quality of sustainable Space of City. Environment Conservation Journal. 16(SE):269-276. https://doi.org/10.36953/ECJ.2015.SE1631
crossref
Benedict, M.A., E.T. McMahon. 2002 Green infrastructure: smart conservation for the 21st century. Renewable resources journal 20(3):12-17. https://api.semanticscholar.org/CorpusID:140592769.

Benton-Short, L., M. Keeley, J. Rowland. 2017. Green infrastructure, green space, and sustainable urbanism: geography’s important role. Urban Geography. 40(3):330-351. https://doi.org/10.1080/02723638.2017.1360105
crossref
Brunbjerg, A.L., J.D. Hale, A.J. Bates, R.E. Fowler, E.J. Rosenfeld, J.P. Sadler. 2018. Can patterns of urban biodiversity be predicted using simple measures of green infrastructure? Urban Forestry and Urban Greening. 32:143-153. https://doi.org/10.1016/j.ufug.2018.03.015
crossref
Cetin, M. 2015. Using GIS analysis to assess urban green space in terms of accessibility: case study in Kutahya. International Journal of Sustainable Development and World Ecology. 22(5):420-424. https://doi.org/10.1080/13504509.2015.1061066
crossref
Chen, X., L. Xu, R. Zhu, Q. Ma, Y. Shi, Z. Lu. 2022. Changes and Characteristics of Green Infrastructure Network Based on Spatio-Temporal Priority. Land. 11(6):901. https://doi.org/10.3390/land11060901
crossref
Chi, L., J. Wang, L. Sun, C. Lv. 2020. Construction and optimization of green space ecological networks in urban fringe areas: A case study with the urban fringe area of Tongzhou district in Beijing. Journal of Cleaner Production. 276:124266. https://doi.org/10.1016/j.jclepro.2020.124266
crossref
Chiba Prefecture. 2022 13th Chiba Prefecture Bird and Animal Protection Management Project Plan Retrieved from https://www.pref.chiba.lg.jp/shizen/choujuu/jigyoukeikaku/keikaku.html.

Cohen, M. 2017. A Systematic Review of Urban Sustainability Assessment Literature. Sustainability. 9(11):2048. https://doi.org/10.3390/su9112048
crossref
Constantinescu, M., A. Orîndaru, ŞC Căescu, A. Pachiţanu. 2019. Sustainable Development of Urban Green Areas for Quality of Life Improvement—Argument for Increased Citizen Participation. Sustainability. 11(18):4868. https://doi.org/10.3390/su11184868
crossref
Dige, G., R. Eales, J. Baker, W. Sheate. 2011 Green infrastructure and territorial cohesion The concept of green infrastructure and its integration into policies using monitoring systems. EEA Technical report No.18 Retrieved from https://www.researchgate.net/publication/282975374_Green_infrastructure_and_territorial_cohesion_The_concept_of_green_infrastructure_and_its_integration_into_policies_using_monitoring_systems.

Diogo, V., E. Koomen. 2016. Land cover and land use indicators: review of available data. OECD Green Growth Papers. Retrieved from https://doi.org/10.1787/22260935
crossref
Dobson, M.C., J.L. Edmondson, P.H. Warren. 2020. Urban food cultivation in the United Kingdom: Quantifying loss of allotment land and identifying potential for restoration. Landscape and Urban Planning. 199:103803. https://doi.org/10.1016/j.landurbplan.2020.103803
crossref
Ellis, J.B. 2013. Sustainable surface water management and green infrastructure in UK urban catchment planning. Journal of Environmental Planning and Management. 56(1):24-41. https://doi.org/10.1080/09640568.2011.648752
crossref
Emmanuel, R., A. Loconsole. 2015. Green infrastructure as an adaptation approach to tackling urban overheating in the Glasgow Clyde Valley Region, UK. Landscape and Urban Planning. 138:71-96. https://doi.org/10.1016/j.landurbplan.2015.02.012
crossref
Ermilova, M., M. Terada, R. Shimoda, I. Kinoshita. 2018. Improving the Practice of Landscape Design Collaboration between University and Local Community: Case study in Matsudo, Japan. Environment-Behaviour Proceedings Journal. 3(9):25-34. https://doi.org/10.21834/e-bpj.v3i9.1491
crossref
European Commission. 2019 Atlas of the Human Planet 2019 Retrieved from https://publications.jrc.ec.europa.eu/repository/handle/JRC118979.

Fatti, C.C., S. Khanyile, S. Dunsmore, A. Fitchett. 2019. Towards applying a green infrastructure approach in the Gauteng City-Region. Gauteng City-Region Observatory. https://doi.org/10.36634/SEBV3078
crossref
Fisher, D., K. Blackstock, K. Irvine. 2020. “It’s on the ‘nice to have’ pile”: Potential principles to improve the implementation of socially inclusive Green Infrastructure. Ambio. 50:1574-1586. https://doi.org/10.1007/s13280-020-01372-2
crossref pmid pmc
Fukuoka, T., S. KATO. 2015. Toward the implementation of green infrastructure in Japan through the examination of city of Portland’s green infrastructure projects. Journal of The Japanese Institute of Landscape Architecture. 78(5):777-782. https://doi.org/10.5632/jila.78.777
crossref
Goepel, K.D. 2013. Implementing the analytic hierarchy process as a standard method for multi-criteria decision making in corporate enterprises–a new AHP excel template with multiple inputs. In Proceedings of the international symposium on the analytic hierarchy process. 2(10):1-10. https://doi.org/10.13033/isahp.y2013.047
crossref
Green Infrastructure The Conservation Fund Web-Page. 2024 March 5 What is Green Infrastructure? Retrieved from https://greeninfrastructure.net/who-we-are/what-is-green-infrastructure/.

Gregorio, A.D., L. Jansen. 2000 Land Cover Classification System (LCCS): Classification Concepts and User Manual Food and Agriculture Organization of the United Nations; Retrieved from https://api.semanticscholar.org/CorpusID:130559577.

Hansen, R., A.S. Olafsson, A.P. N. Van der Jagt, E. Rall, S. Pauleit. 2019. Planning multifunctional green infrastructure for compact cities: What is the state of practice? Ecological Indicators. 96(2):99-110. https://doi.org/10.1016/j.ecolind.2017.09.042
crossref
Hartmuth, G., K. Hubler, D. Rink. 2008. Operationalization and contextualization of sustainability at the local level. Sustainable Development. 16:261-270. https://doi.org/10.1002/sd.377
crossref
Hoang, L., R.A. Fenner. 2016. System interactions of stormwater management using sustainable urban drainage systems and green infrastructure. Urban Water Journal. 13(7):39-758. https://doi.org/10.1080/1573062X.2015.1036083
crossref
Hokkaido Forestry Bureau Web-Page 2024 March 10 Retrieved from https://www.rinya.maff.go.jp/hokkaido/square/morinokoto/2010/101111.html.

Honeck, E., A. Sanguet, M. Schlaepfer, A.N. Wyler, A. Lehmann. 2020. Methods for identifying green infrastructure. SN Applied Sciences. 2:1916. https://doi.org/10.1007/s42452-020-03575-4
crossref
Hoover, F.A., S. Meerow, E. Coleman, Z. Grabowski, T. McPhearson. 2023. Why go green? Comparing rationales and planning criteria for green infrastructure in U.S. city plans. Landscape and Urban Planning. 237:104781. https://doi.org/10.1016/j.landurbplan.2023.104781
crossref
Isola, F., S. Lai, F. Leone, C. Zoppi. 2022. Strengthening a Regional Green Infrastructure through Improved Multifunctionality and Connectedness: Policy Suggestions from Sardinia, Italy. Sustainability. 14(15):9788. https://doi.org/10.3390/su14159788
crossref
Iwasa, Y.K. 2015. Approaches to Green Infrastructure by Land, Infrastructure and Transportation Ministry(Topics). Ecology and Civil Engineering. 18(2):165-166. https://doi.org/10.3825/ece.18.165
crossref
Japanese Forestry Agency Web-Page. 2024a March 21 Health and recreation functions Retrieved from https://www.rinya.maff.go.jp/j/keikaku/tamenteki/con_2_6.html.

Japanese Forestry Agency Web-Page. 2024b March 5 Retrieved from https://www.rinya.maff.go.jp/j/riyou/biomass/con_7.html.

Jezzini, Y., G. Assaf, R.H. Assaad. 2023. Models and Methods for Quantifying the Environmental, Economic, and Social Benefits and Challenges of Green Infrastructure: A Critical Review. Sustainability. 15(9):7544. https://doi.org/10.3390/su15097544
crossref
Jim, C.Y. 2013. Sustainable urban greening strategies for compact cities in developing and developed economies. Urban Ecosystems. 16:741-761. https://doi.org/10.1007/s11252-012-0268-x
crossref
Jones, L., S. Anderson, J. Læssøe, E. Banzhaf, A. Jenson, D.N. Bird, J. Miller, M.G. Hutchins, J. Yang, J. Garrett, T. Taylor, B.W. Wheeler, R. Lovell, D. Fletcher, Y. Qu, M. Vieno, M. Zandersen. 2022. A typology for urban Green Infrastructure to guide multifunctional planning of nature-based solutions. Nature-Based Solutions. 2:100041. https://doi.org/10.1016/j.nbsj.2022.100041
crossref
Kang, S.J., J.O. Kim. 2015. Morphological analysis of green infrastructure in the Seoul metropolitan area, South Korea. Landscape and Ecological Engineering. 11:259-268. https://doi.org/10.1007/s11355-014-0268-5
crossref
Kaplan, A. 2012. “Green Infrastructure” Concept as an Effective Medium to Manipulating Sustainable Urban Development. (Eds), Green and Ecological Technologies for Urban Planning: Creating Smart Cities In: Ercoskun Ozge Yalciner, IGI Global. (pp. 234-254). https://doi.org/10.4018/978-1-61350-453-6.ch013
crossref
Kim, D.H., S.K. Song. 2019. The Multifunctional Benefits of Green Infrastructure in Community Development: An Analytical Review Based on 447 Cases. Sustainability. 11(14):3917. https://doi.org/10.3390/su11143917
crossref
Kim, Y.J., R.J. Lee, T.H. Lee, Y.C. Shin. 2023. Green Infrastructure and Urban Vacancies: Land Cover and Natural Environment as Predictors of Vacant Land in Austin, Texas. Land. 12(11):2031. https://doi.org/10.3390/land12112031
crossref
Kinoshita, T., K. Hashimoto, K. Ye. 2016. Planning method for small areas in Liverpool green infrastructure strategy, United Kingdom. Journal of the Japanese Institute of Landscape Architecture. 79(5):681-684. https://doi.org/10.5632/jila.79.681
crossref
Kong, F., H. Yin, N. Nakagoshi, Y. Zong. 2010. Urban green space network development for biodiversity conservation: Identification based on graph theory and gravity modeling. Landscape and Urban Planning. 95(1–2):16-27. https://doi.org/10.1016/j.landurbplan.2009.11.001
crossref
Koohsari, M.J., A. Yasunaga, G.R. McCormack, T. Nakaya, Y. Nagai, K. Oka. 2022. The design challenges for dog ownership and dog walking in dense urban areas: The case of Japan. Frontiers in Public Health. 10:904122. https://doi.org/10.3389/fpubh.2022.904122
crossref pmid pmc
Korkou, M., A.K. M. Tarigan, H.M. Hanslin. 2023. The multifunctionality concept in urban green infrastructure planning: A systematic literature review. Urban Forestry and Urban Greening. 85:127975. https://doi.org/10.1016/j.ufug.2023.127975
crossref
Kou, H.F., K.W. Tsou. 2015. Application of Environmental Change Efficiency to the Sustainability of Urban Development at the Neighborhood Level. Sustainability. 7(8):10479-10498. https://doi.org/10.3390/su70810479
crossref
Kruize, M., N. van der Vliet, B. Staatsen, R. Bell, A. Chiabai, G. Muiños, S. Higgins, S. Quiroga, P. Martinez-Juarez, M. Aberg Yngwe, F. Tsichlas, P. Karnaki, M. Luísa Lima, S. García de Jalón, M. Khan, G. Morris, I. Stegeman. 2019. Urban Green Space: Creating a Triple Win for Environmental Sustainability, Health, and Health Equity through Behavior Change. International Journal of Environmental Research and Public Health. 16(22):4403. https://doi.org/10.3390/ijerph16224403
crossref pmid pmc
Kumada, T. 2002. The Change of the Suburban Cities in Tokyo Metropolitan Area during the Bubble Economy Era and the Lost Decade. The annual report of kanto society of urbanology. 4:13-22. https://doi.org/10.24682/ksurb.4.0_13
crossref
Kyushu Forest Management Bureau Web-Page 2024 March 5 Retrieved from https://www.rinya.maff.go.jp/kyusyu/invitation/q_a/rkuma10b.html.

Lähde, E., A. Khadka, O. Tahvonen, T. Kokkonen. 2019. Can We Really Have It All?—Designing Multifunctionality with Sustainable Urban Drainage System Elements. Sustainability. 11(7):1854. https://doi.org/10.3390/su11071854
crossref
Lee, E.S., C.W. Noh, J.S. Sung. 2014. Meaning structure of green infrastructure-a literature review about definitions. Journal of the Korean Institute of Landscape Architecture. 42(2):65-76. https://doi.org/10.9715/KILA.2014.42.2.065
crossref
Leese, C., H. Al-Zubaidi. 2023. Urban green and blue spaces for influencing physical activity in the United Kingdom: A narrative review of the policy and evidence. Lifestyle Medicine. 5(1):e96. https://doi.org/10.1002/lim2.96
crossref
Li, L., A.M. Collins, A. Cheshmehzangi, F.K. S. Chan. 2020. Identifying enablers and barriers to the implementation of the Green Infrastructure for urban flood management: A comparative analysis of the UK and China. Urban Forestry & Urban Greening. 54:126770. https://doi.org/10.1016/j.ufug.2020.126770
crossref
Lindholm, G. 2017. The Implementation of Green Infrastructure: Relating a General Concept to Context and Site. Sustainability. 9(4):610. https://doi.org/10.3390/su9040610
crossref
Liverpool City. 2010 Liverpool City Green Infrastructure Strategy Retrieved from http://www.greeninfrastructurenw.co.uk/liverpool/.

Llausas, A., M. Roe. 2012. Green Infrastructure Planning: Cross-National Analysis between the North East of England (UK) and Catalonia (Spain). European Planning Studies,. 20(4):641-663. https://doi.org/10.1080/09654313.2012.665032
crossref
Maes, J., A. Barbosa, C. Baranzelli, G. Zulian, F. Batista e Silva, I. Vandecasteele, R. Hiederer, C. Liquete, M.L. Paracchini, S. Mubareka, C.J. Crisioni, C.P. Castillo, C. Lavalle. 2015. More green infrastructure is required to maintain ecosystem services under current trends in land-use change in Europe. Landscape Ecology. 30:517-534. https://doi.org/10.1007/s10980-014-0083-2
crossref pmid pmc
Mansor, M., I. Said. 2008. Green infrastructure network as social spaces for well-being of residents in Taping, Malaysia. Jurnal Alam Bina. 11(2):1-18. https://api.semanticscholar.org/CorpusID:56064890

Matsudo City Official Web-Page. 2023a December 22 Location, transportation, topography, and origin of place names of Matsudo City Retrieved from https://www.city.matsudo.chiba.jp/profile/ichi_chikei_yurai.html.

Matsudo City Official Web-Page. 2023b December 22 My favorite scenic spots in Matsudo Retrieved from https://www.city.matsudo.chiba.jp/miryoku/kankoumiryokubunka/shizen/keikan_spot/index.html.

Matsudo City. 2022a Matsudo City Urban Planning Master Plan Retrieved from https://www.city.matsudo.chiba.jp/shisei/keikaku-kousou/master-plan.html.

Matsudo City. 2022b Matsudo City Green Basic Plan Retrieved from https://www.city.matsudo.chiba.jp/shisei/keikaku-kousou/midorinokihon.html.

Mekonen, S. 2020. Coexistence between human and wildlife: The nature, causes and mitigations of human wildlife conflict around Bale Mountains National Park, Southeast Ethiopia. BMC Ecology. 20:51. https://doi.org/10.1186/s12898-020-00319-1
crossref pmid pmc
Mell, I. 2008 Green Infrstructure: concepts and planning. FORUM ejournal Newcastle. UK. Newcastle University; 8(1):69-80. Retrieved from https://www.academia.edu/724336/Green_Infrstructure_concepts_and_planning.

Mell, I., S. Clement. 2020. Progressing Green Infrastructure planning: understanding its scalar, temporal, geo-spatial and disciplinary evolution. Impact Assessment and Project Appraisal. 38(6):449-463. https://doi.org/10.1080/14615517.2019.1617517
crossref
Mieg, H.A. 2012. Sustainability and innovation in urban development: concept and case. Sustainable Development. 20(4):251-263. https://doi.org/10.1002/sd.471
crossref
Min, K.H. 2016 A study on development of coexistence index of environment and man for zoning Baekdudaegan mountain range as biosphere reserve. Master’s thesis Seoul National University; Seoul, Korea. https://hdl.handle.net/10371/129768.

Min, K.H., Y.H. Son, K.N. Furuya. 2019. Categorizing Types of Transition Areas in Biosphere Reserve: A Case Study of the Baekdudaegan Mountain Ranges in South Korea. IRSPSD(International Review for Spatial Planning and Sustainable Development). 2019. 7(1): https://doi.org/10.14246/irspsd.7.1_83
crossref
Ministry of Agriculture_Forestry and Fisheries Web-Page. 2024 March 21 Explanatory material on “Green Food System Strategy” Retrieved from https://www.maff.go.jp/j/kanbo/kankyo/seisaku/midori/?.

Ministry of Environment_Government of Japan Web-Page. 2024a March 10 Retrieved from https://www.env.go.jp/kijun/oto1-1.html.

Ministry of Environment_Government of Japan Web-Page 2024b March 10 Retrieved from https://www.env.go.jp/policy/post_151.html.

Ministry of Environment_Government of Japan. 2019 Scheme of the Soil Contamination Countermeasures Act Retrieved from https://www.env.go.jp/water/dojo/pamph_law-scheme/index.html.

Ministry of Foreign Affairs of Japan Web-Page. 2024a March 21 Retrieved from https://www.mofa.go.jp/policy/culture/coop/unesco/c_heritage/w_heritage/index.html.

Ministry of Foreign Affairs of Japan Web-Page. 2024b March 21 Retrieved from https://www.mofa.go.jp/policy/culture/coop/unesco/c_heritage/index.html.

Ministry of Land_Infrastructure_Transport and Tourism Web-Page. 2024 March 5 Retrieved from https://www.mlit.go.jp/toshi/park/toshi_parkgreen_tk_000134.html.

Ministry of Land_Infrastructure_Transport and Tourism. 2016 Guide to increasing the attractiveness of buildings through greenery Retrieved from https://www.mlit.go.jp/common/001156188.pdf.

Ministry of Land_Infrastructure_Transport and Tourism. 2017 It cools the city with greenery Retrieved from https://www.mlit.go.jp/report/press/toshi10_hh_000255.html.

Ministry of Land_Infrastructure_Transport and Tourism. 2018 Dam reservoir sediment management guide Retrieved from https://www.mlit.go.jp/river/shishin_guideline/index.html.

Ministry of Land_Infrastructure_Transport and Tourism. 2023a Green infrastructure promotion strategy Retrieved from https://www.mlit.go.jp/sogoseisaku/environment/sosei_environment_tk_000017.html.

Ministry of Land_Infrastructure_Transport and Tourism. 2023b National Land Planning: Second National Land Formation Plan Retrieved from https://www.mlit.go.jp/kokudoseisaku/kokudokeikaku_fr3_000003.html.

Monteiro, R., J.C. Ferreira, P. Antunes. 2020. Green Infrastructure Planning Principles: An Integrated Literature Review. Land. 9(12):525. https://doi.org/10.3390/land9120525
crossref
Mu, B., C. Liu, G. Tian, Y. Xu, Y. Zhang, A.L. Mayer, R. Lv, R. He, G. Kim. 2020. Conceptual Planning of Urban– Rural Green Space from a Multidimensional Perspective: A Case Study of Zhengzhou, China. Sustainability. 12(7):2863. https://doi.org/10.3390/su12072863
crossref
Nakaguchi, K., D. Komori. 2020. Evaluation of the Relationship Between Urban Scale and the Rainfall Inundation Risk in Five Cities of Japan. Journal of Social Safety Science. 37:49-55. https://doi.org/10.11314/jisss.37.49
crossref
Natuhara, Y. 2018. Green infrastructure: innovative use of indigenous ecosystems and knowledge. Landscape and Ecological Engineering. 14:187-192. https://doi.org/10.1007/s11355-018-0357-y
crossref
Naumann, S., G. Anzaldua, P. Berry, S. Burch, M. Davis, A. Frelih-Larsen, H. Gerdes, M. Sanders. 2011 Assessment of the potential of ecosystem-based approaches to climate change adaptation and mitigation in Europe. Final report to the European Commission DG Environment; Retrieved from https://www.ecologic.eu/17774.

Oh, J.H., S.G. Jung, J.O. Kwon, K.H. Park. 2007 A Landscape Ecological Classification based on Watershed Focusing Landcover Types. Journal of the Korean Association of Geographic Information Studies 10(4):22-34. Retrieved from https://koreascience.kr/article/JAKO200721761942642.page.

Otsuka, N., H. Abe, Y. Isehara, T. Miyagawa. 2021. The potential use of green infrastructure in the regeneration of brownfield sites: three case studies from Japan’s Osaka Bay Area. Local Environment. 26(11):1346-1363. https://doi.org/10.1080/13549839.2021.1983791
crossref
Ouchino News. 2024 January 16 Ease of living in Matsudo City, a highly convenient commuter town Ouchino News Editorial Department; Retrieved from https://o-uccino.com/front/articles/48915.

Papageorgiou, M., G. Gemenetzi. 2018. Setting the grounds for the green infrastructure in the metropolitan areas of Athens and Thessaloniki: the role of green space. European Journal of Environmental Sciences. 8(1):83-92. https://doi.org/10.14712/23361964.2018.12
crossref
Parker, J., M.E. Zingoni de Baro. 2019. Green Infrastructure in the Urban Environment: A Systematic Quantitative Review. Sustainability. 11(11):3182. https://doi.org/10.3390/su11113182
crossref
Pauleit, S., E. Andersson, B. Anton, A. Buijs, D. Haase, R. Hansen, I. Kowarik, A.S. Olafsson, S.V. der Jagt. 2019. Urban green infrastructure – connecting people and nature for sustainable cities. Urban Forestry & Urban Greening. 40:1-3. https://doi.org/10.1016/j.ufug.2019.04.007
crossref
Phiri, D., J. Morgenroth. 2017. Developments in Landsat Land Cover Classification Methods: A Review. Remote Sensing. 9(9):967. https://doi.org/10.3390/rs9090967
crossref
Pitman, S.D., C.B. Daniels, M.E. Ely. 2015. Green infrastructure as life support: urban nature and climate change. Transactions of the Royal Society of South Australia. 139(1):97-112. https://doi.org/10.1080/03721426.2015.1035219
crossref
Pozoukidou, G. 2020. Designing a green infrastructure network for metropolitan areas: a spatial planning approach. Euro-Mediterranean Journal for Environmental Integration. 5(40):1-15. https://doi.org/10.1007/s41207-020-00178-8
crossref
Saitama Prefecture Web-Page. 2024 March 21 Retrieved from https://www.pref.saitama.lg.jp/a0508/midorinoportal.html.

Sandström, U.G. 2002. Green Infrastructure Planning in Urban Sweden. Planning Practice & Research. 17(4):373-385. https://doi.org/10.1080/02697450216356
crossref
Shin, Y.N. 2015 A study of the open space typology and multi-functionality for the effective management of the green space resources: Siheung City, Gyeonggi-do. Master’s thesis Seoul National University; Seoul, Korea. https://hdl.handle.net/10371/129743.

Son, Y.H., M.Y. Yoon. 2011 Types of green landscapes in a suburban city perceptions of local residents. Journal of the Korean Institute of Landscape Architecture 39(5):101-110. http://uci.or.kr/G704-000407.2011.39.5.012.
crossref
Staccione, A., S. Candiago, J. Mysiak. 2022. Mapping a Green Infrastructure Network: a framework for spatial connectivity applied in Northern Italy. Environmental Science and Policy. 131:57-67. https://doi.org/10.1016/j.envsci.2022.01.017
crossref
Stürck, J., R.H. Verburg. 2017. Multifunctionality at what scale? A landscape multifunctionality assessment for the European Union under conditions of land use change. Landscape Ecology. 32:481-500. https://doi.org/10.1007/s10980-016-0459-6
crossref
Symons, J., R. Jones, C. Young, B. Rasmussen. 2015 Assessing the economic value of green infrastructure: Liter ature review Retrieved from https://vuir.vu.edu.au/32096/.

Tiwari, A., P. Kumar, G. Kalaiarasan, T.B. Ottosen. 2021. The impacts of existing and hypothetical green infrastructure scenarios on urban heat island formation. Environmental Pollution. 274:115898. https://doi.org/10.1016/j.envpol.2020.115898
crossref pmid
Tzoulas, K., K. Korpela, S. Venn, V. Yli-Pelkonen, A. Kaźmierczak, J. Niemela, P. James. 2007. Promoting ecosystem and human health in urban areas using Green Infrastructure: A literature review. Landscape and Urban Planning. 81(3):167-178. https://doi.org/10.1016/j.landurbplan.2007.02.001
crossref
United Nations. 2022 World Population Prospects 2022 Retrieved from https://population.un.org/wpp/Publications/.

Urushima, A.F. 2015. Territorial Prospective Visions for Japan’s High Growth: The Role of Local Urban Development. Nature and Culture. 10(1):12-35. https://doi.org/10.3167/nc.2015.100102
crossref
Vidal, D.G., N. Barros, R.L. Maia. 2020. Public and Green Spaces in the Context of Sustainable Development. Sustainable Cities and Communities. 479-487. https://doi.org/10.1007/978-3-319-95717-3_79
crossref
Wang, J., E. Banzhaf. 2018. Towards a better understanding of Green Infrastructure: A critical review. Ecological Indicators. 85:758-772. https://doi.org/10.1016/j.ecolind.2017.09.018
crossref
Wang, J., A. Rienow, M. David, C. Albert. 2022. Green infrastructure connectivity analysis across spatiotemporal scales: A transferable approach in the Ruhr Metropolitan Area, Germany. Science of The Total Environment. 813:152463. https://doi.org/10.1016/j.scitotenv.2021.152463
crossref pmid
Wang, R. 2022. Fuzzy-based multicriteria analysis of the driving factors and solution strategies for green infrastructure development in China. Sustainable Cities and Society. 82:103898. https://doi.org/10.1016/j.scs.2022.103898
crossref
Weber, T., A. Sloan, J. Wolf. 2006. Maryland’s Green Infrastructure Assessment: Development of a comprehensive approach to land conservation. Landscape and Urban Planning. 77(1–2):94-110. https://doi.org/10.1016/j.landurbplan.2005.02.002
crossref
Wendler, J., J.G. Carter, J. Rees. 2022 Urban Green Infrastructure Target Setting: A City Review. The IGNITION Project University of Manchester; For further information contact Jeremy Carter at Jeremy. Retrieved from https://gmgreencity.com/wp-content/uploads/2022/06/IGNITION_GI-target-setting-review_final-version.pdf.

Williamson, K.S. 2003 Growing with green infrastructure. Heritage Conservancy Retrieved from http://www.greeninfrastructurenw.co.uk/resources/Growing_with_GI.pdf.

Wu, J. 2010. Urban sustainability: an inevitable goal of landscape research. Landscape Ecology. 25:1-4. https://doi.org/10.1007/s10980-009-9444-7
crossref
Xing, Y., R.M. W. Horner, M.A. El-Haram, J. Bebbington. 2009. A framework model for assessing sustainability impacts of urban development. Accounting Forum. 33(3):209-224. https://doi.org/10.1016/j.accfor.2008.09.003
crossref
Yoon, M.Y., S.Y. Kim, Y.H. Son. 2010 A study on the value and utilization of slope forest landscapes in relation to the green landscape policy of Matsudo City, Chiba Prefecture - targeting the Yagiri area of Matsudo City. Journal of Korean Society of Landscape Architecture 195-198. Retrieved from https://scienceon.kisti.re.kr/srch/selectPORSrchArticle.do?cn=NPAP11488311.

Yutaka, G. 2019. Hiroshi Goto. The results of Yokohama city development and the spatial structure of the metropolitan area as seen in a social map - from the perspective of competition between cities in the metropolitan area. Yokohama City University Series. Humanities. 70(2–3):91-129. https://doi.org/10.15015/00001697
crossref
Zaitunah, A., A. Samsuri, Y. Mandalahi, L. Syaufina. 2022. Mapping land cover and vegetation detection in urban areas. Journal of Sylva Indonesiana. 5(1):68-80. https://doi.org/10.32734/jsi.v5i01.6904
crossref
Zang, Xin, Y. Ren, D. Zhang, K. Li. 2022. Construction of the green infrastructure network for adaption to the sustainable future urban sprawl: A case study of Lanzhou City, Gansu Province, China. Ecological Indicators. 125:109715. https://doi.org/10.1016/j.ecolind.2022.109715
crossref
Zhang, X., Y. Ren, D. Zhang, K. Li. 2022. Construction of the green infrastructure network for adaption to the sustainable future urban sprawl: A case study of Lanzhou City, Gansu Province, China. Ecological Indicators. 145:109715. https://doi.org/10.1016/j.ecolind.2022.109715
crossref
Zhou, Y., J. Yao, M. Chen, M. Tang. 2023. Optimizing an Urban Green Space Ecological Network by Coupling Structural and Functional Connectivity: A Case for Biodiversity Conservation Planning. Sustainability. 15(22):15818. https://doi.org/10.3390/su152215818
crossref


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