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Volume 38, Issue 4 (2023)
GeoRes 2023, 38(4): 481-489 |
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Received: 2023/09/7 | Accepted: 2023/10/14 | Published: 2023/10/28
Received: 2023/09/7 | Accepted: 2023/10/14 | Published: 2023/10/28
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Raeisi M, Mohammadi M. Examination and Determination of the Central Cores of Zahedan City Using Geographic Information System (GIS). GeoRes 2023; 38 (4) :481-489
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Authors
M.K. Raeisi *1, M. Mohammadi2
1- Department of Geography, Payam-e-Noor University, Tehran, Iran
2- Department of Economic Sciences, Payam-e-Noor University, Tehran, Iran
2- Department of Economic Sciences, Payam-e-Noor University, Tehran, Iran
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Introduction
Urbanization is a socio-spatial process that is directly associated with the expansion of urban areas and the growth of the urban population. Developed countries such as the United States, Japan, and the United Kingdom have already completed their urbanization processes. The spatial structure of cities plays a significant role in their sustainable development. One of the key stages in analyzing the urban spatial structure is identifying the urban centers. A central assumption in most urban economic models is that all jobs in a city are located in the Central Business District (CBD), which constitutes the city’s core, where employment is concentrated and workers from all over the city commute for jobs. Another implicit assumption is that the city is circular and concentric. In this model, residents are distributed across a circular city and access the city center through radial routes. Since any point can potentially hold these conditions, identifying the core center of each city becomes essential [Wong, 2004; Chandio et al., 2011].
If we assume cities to be living, dynamic organisms, their central area functions as the heart [Shakoei, 2009]. Accordingly, the city center serves as the driving engine of urban development and hosts the most concentrated and significant urban functions. It seems that the city center is more of a functional concept rather than merely a physical one [Lin et al., 2012; Deswal & Laura, 2018].
The central area of a city encompasses a wide range of functions, and its position within the urban form and spatial structure is determined accordingly. The very concept of urban space depends on land occupation patterns and land uses, which in turn reflect activities and functions. Therefore, in order to understand the central area of a city, it must be analyzed from multiple perspectives and related concepts should be identified. Concepts such as the city center, the old city center, the civic or administrative center, the commercial center, the inner-city zone, and the community center are frequently referenced in discussions of urban centers [Dezert & Bastie, 2003]. Considering these concepts and terminologies, the central area of cities carries a broad semantic load and encompasses a wide range of meanings, which must be applied according to urban functions, spatial structures, and forms.
The central area plays an important economic role, perhaps the most prominent function of all. When the functional roles of different urban zones are not clearly defined, the center of a large city is often regarded as the commercial core [Ahlfeldt & Wendland, 2013]. The economic role of the urban center is so significant that, despite suburban employment growth, many urban cores continue to host dense concentrations of jobs. This indicates that economic agglomeration (the benefits derived from the clustering of economic activities) still matters in many markets [Voith, 1988; Romein et al., 2009].
The advantages of economic agglomeration are so strong that, despite vast physical urban sprawl, the central core and the broader central area continue to attract activities into a defined territory. The central area also plays a vital historical role, as in many cases the central zone of contemporary cities coincides with their original nucleus and historic core, where urban transformations can be traced. Central areas typically host historic buildings with diverse uses: private residences, grand mansions, heritage structures, corporate headquarters, and governmental offices such as post and customs administrations. Moreover, historically, many native communities have resided in what is now regarded as the city center [Razzu, 2005]. From this perspective, the historical identity of the central area provides the city with a distinctive character, so much so that many cities are recognized through their central areas.
Indeed, city centers embody collective memory and serve as valuable public realms familiar to residents. This has made residential redevelopment of city centers a key component of contemporary urban regeneration strategies [Tallon & Bromley, 2004; Mokarram & Hojati, 2017; Mohit & Ali, 2006]. Consequently, central areas increasingly attract middle- and upper-income groups, leading to their revitalization and flourishing. Administrative-political functions are also concentrated in city centers. Historically, as cities formed and governance systems emerged, the initial administrative complexes were established in the urban core. Many cities and their centers were initially founded with this purpose. Furthermore, given the significance of city centers across various domains, they have always been politically prominent. The concentration of a substantial share of administrative-political activities in the central area demonstrates its critical role in urban functional spaces.
Another essential function of city centers lies in transportation. Accessibility is the defining feature of the urban core, and it plays the most influential role in land-use decisions within city centers, ensuring economic sustainability and functional efficiency [Kazemian, 2001]. High accessibility attracts diverse activities, fosters land-use competition, and maximizes density in central zones. Public transportation systems are typically most concentrated in city centers, with networks converging toward them. Thus, the central area serves as a major hub for generating and attracting intra- and intercity trips.
According to Jean-Paul Lacaze, the structure of a city emerges from the interplay of networks of poles, axes, and flows, including infrastructure networks (roads and other systems), built volumes, open spaces, economic and production flows, trade and consumption patterns, socio-cultural facilities, power relations, symbolic landmarks, and meanings. Other factors also shape urban structure, such as high-value land boundaries, activity types, job densities, residential densities, and socio-demographic structures. The city’s structure is the cumulative result of all such forces operating within urban space [Dezert & Bastie, 2003].
Several relevant studies have examined these dynamics. Cai et al. (2017), using large-scale geographic data, identified polycentric structures in Chinese cities such as Beijing, Shanghai, and Chongqing. Their findings indicated that each city contained one primary core and several secondary subcenters. Amjad et al. (2019) analyzed Peshawar’s core using indicators such as land value, rental prices, retail sales, vehicle and pedestrian flows, and land area. Their results identified Saddar Bazaar as the city’s central core, though its characteristics differed from the old city. Similarly, Parvez and Sadat (2020), applying the AHP model and GIS data including land, population distribution, water supply, waste management, and road networks assessed potential central cores in Bangladesh. Their findings revealed urban expansion trends and identified ideal locations for future metropolitan centers with necessary commercial preconditions. Razaghi et al. (2011) emphasized the complexity of urban structures in large cities and argued for a polycentric development model. They concluded that such a model optimized service provision and reduced unnecessary trips to the main core.
Since identifying central areas (here, in the case of Zahedan) continues to shape the city’s economic vitality and holds substantial historical, cultural, social, and political significance, recognizing urban centers enhances urban environmental quality and, most importantly, promotes sustainable urban development. Therefore, this study aims to investigate this issue.
Methodology
The present study is applied in nature and was conducted in Zahedan city in 2023. Zahedan, the capital of Sistan and Baluchestan Province, is the largest province in Iran. Geographically, Zahedan County is bordered by Sistan to the north, Kerman Province to the west, Pakistan to the east, and Khash County to the south. According to the 2016 census, the population of Zahedan was 592,968. The total area of the city is 8,123 hectares. The southern and southwestern parts of the city are located at higher elevations, while the altitude decreases toward the north. Zahedan is divided into five urban districts [Statistical Centre of Iran, 2022].
Data collection methods included library research and documentary review. The indices under investigation comprised the density of educational centers, banks, healthcare facilities, administrative offices, sports complexes, commercial centers, green spaces, religious institutions, military facilities, parking lots, catering facilities, recreational spaces, building density, population density, street quality, and land use in Zahedan. Due to constraints such as costs, time limitations, shortage of human resources, and the aim of minimizing potential errors, the study was limited to the mentioned indices.
Data related to these indices were obtained through the National Portal of the Statistical Centre of Iran, statistical yearbooks, and block-level data layers acquired from the Urban Planning and Management Center. After preparing the statistical blocks and collecting the required data, the information was integrated into the urban block layer of Zahedan using ArcGIS 10.3 software. Based on expert judgment, suitable ranges of distances from the studied facilities were determined using a five-point Likert scale and the Reclassify tool in ArcGIS 10.3. For this purpose, 12 urban studies experts including faculty members and researchers from Payame Noor University of Tehran were selected through purposive sampling. The number of experts was validated using Cronbach’s alpha.
The valuation of data was based on their impact on individuals and physical spaces, categorized into five zones ranging from “completely unsuitable” to “completely suitable”. To identify the urban cores of Zahedan, two analytical approaches were employed: Network Analysis and the Analytic Hierarchy Process (AHP).
Findings
The weights assigned to each informational layer, based on the analysis of criteria in Expert Choice software, were as follows: educational centers (0.12), banks (0.08), healthcare centers (0.12), administrative offices (0.05), sports facilities (0.09), commercial centers (0.09), green spaces (0.07), religious sites (0.04), military sites (0.06), parking lots (0.04), street quality (0.05), tourist reception facilities (0.04), recreational spaces (0.07), building density (0.05), and population density (0.03).
The examination of Zahedan’s spatial layers revealed that most administrative offices were concentrated in Districts 5, 2, and 3, which form the core of the study area. The largest number of recreational centers was located in the northern part of District 5. Similarly, the distribution of banks showed a concentration in the city center, particularly in Districts 2 and 5. Another influential factor in determining urban cores was the distribution of parking lots, which was densest in the central part of Zahedan. Some land uses, such as educational centers and religious facilities, had a wider distribution across the city.
Tourist reception facilities were mainly concentrated in the city center, as well as in Districts 1 and 2, but overall, they showed limited distribution throughout the city. Green spaces, however, were more widely distributed, with the highest concentration observed in Districts 4 and 5. The distribution of green spaces in these districts reflected limited availability of such land uses in the central city, where high building density and limited land accessibility hindered the development of green areas. The lowest presence of green spaces was noted in the northwestern part of the city.
The distribution of educational and healthcare centers had a significant impact on the formation of urban cores. Healthcare centers were spread relatively evenly across Zahedan, with the highest concentrations in northern District 5 and District 2. Educational facilities were most concentrated in Districts 1 and 2. As illustrated in the educational centers map, the northern areas had fewer educational facilities, while the city center had the greatest density of this land use.
The highest concentration of commercial centers was located in the central area of Zahedan, strongly contributing to the city’s polycentric structure. Religious facilities were distributed relatively evenly throughout the districts, though with greater concentration in the northern part of the city. Military and sports facilities were also more concentrated in the city center.
Street quality, building density, and population density are presented. The analysis of these three layers indicated that street quality was highest in the city center, while it was generally poor in the peripheral areas in all four directions. Streets in the northern part of the study area were of relatively lower quality.
After calculating the weights of criteria and sub-criteria, the respective layers were generated. Following existing standards and expert judgment, informational layers were created and weighted according to their importance. Through overlaying these weighted layers, composite maps were generated, and urban vulnerability was assessed based on each criterion. Finally, a comprehensive urban land-use vulnerability map was produced. The standardized maps of informational layers are presented. By combining these standardized layers and applying criteria weights, the final raster-based zoning map of urban vulnerability in Zahedan was obtained after applying minimum elimination and classification functions.
Results of Network Analysis
The central core of Zahedan was located in the city center, particularly in Districts 1, 2, and 5. Additionally, several sub-centers were identified across the city. In southern parts of Districts 1 and 5, new sub-centers were emerging, while in other districts, evidence of core formation was not clearly observed. According to the network analysis results, Zahedan had one main central core and several sub-cores. The existence of the main core in northern District 5 and Districts 1 and 2 was primarily due to the concentration of diverse infrastructures in these areas.
Results of the Analytic Hierarchy Process (AHP)
The results of the AHP method, similar to the network analysis, showed that Zahedan has one main central core located in the middle of the city, along with several sub-cores around the city and leaning toward the central area. Using this method, four sub-cores were identified across different parts of the city, while the network analysis revealed five sub-cores.
Discussion
In mono-centric cities, all workplaces are concentrated in a single location in close proximity to one another. In this model, transportation costs and the exchange of services are reduced. Specialized services and products are provided within this core. The firms and organizations located in this nucleus can benefit from economies of scale in the provision of public services and welfare facilities, as well as from the exchange of knowledge and ideas. Historically, the mono-centric development pattern of Zahedan is consistent with the original core of its older neighborhoods. In this model, there is a strong dependency on the city center for services from all parts of the city, making it more vulnerable in terms of transportation and traffic, and reliant on the public transportation system. In contrast, the polycentric development model of Zahedan is more compatible and aligned with the city’s spatial form, economy, and overall conditions. This model is more closely associated with realizing the concept of equity in urban planning, urban economy, and employment. Establishing a polycentric urban model has reduced centralization in commercial and service activities, leading to the emergence of new commercial and service cores on the city’s periphery. Such initiatives naturally result in a rational distribution of urban trips, a more efficient distribution of transportation across the road network, and a more effective penetration of major services into multiple neighborhoods in a coordinated manner. Furthermore, decentralization of commercial activities reduces both economic and time costs, which in turn contributes to the balanced development of peripheral settlements. Therefore, with proper planning and designing of a polycentric development model, it can be argued that citizens’ needs and services are met in optimal conditions. The communication structure and transportation network within this model also reduce the volume of inter-sectional connections between urban sub-cores and the central core, thereby lowering congestion not only at intersections but also within different urban cores, particularly in the central core of Zahedan [Razaghi et al., 2011].
Despite the expansion of Zahedan into a polycentric urban structure, this process appears to be in its initial stages since the main core, corresponding to the old fabric of the city, continues to retain its primacy as the primary urban nucleus within a hierarchical structure. According to Jun’s findings, in such polycentric cities, multiple sub-centers of employment exist, but one core is typically more concentrated and stronger than the others. Nevertheless, these newly emerging urban centers derive agglomeration economies through clustering of activities, which are not confined to a single center but distributed across a set of centers that maintain a degree of functional differentiation [Jun, 2020]. Consistent with these findings, Montazer, Hu and colleagues also emphasized lower land and rental costs, accessibility, reduced trips to the central business district, equitable distribution of land uses, and ease of urban center expansion [Montazer, 2016; Hu et al., 2018]. Arvin and colleagues similarly highlighted the potential for achieving desirable spatial development in Ahvaz through its transformation into a polycentric city [Arvin et al., 2020].
Cai and colleagues also introduced Beijing, Shanghai, and Chongqing as polycentric cities, characterized by one central core and several sub-cores [Cai et al., 2017]. Likewise, the results of the present study are aligned with those of Amjad and colleagues, who identified factors such as land and rental values, retailing, vehicle and pedestrian flows as influential in the formation of polycentric cities [Amjad et al., 2019].
Among the limitations of this study is the lack of examination of a broader range of indicators due to insufficient data and financial constraints. Accordingly, future studies are recommended to investigate urban cores with consideration of a wider spectrum of economic and service-related indicators.
Conclusion
The findings of this study indicate that Zahedan is in the process of transitioning toward a polycentric urban structure. Nevertheless, despite its physical growth over the past several decades, the central core (mono-centric structure) continues to maintain its priority over other emerging sub-cores in terms of service provision and employment.
Acknowledgments: The authors would like to express their gratitude to all individuals who participated in this study.
Ethical Permission: None declared by the authors.
Conflict of Interest: None declared by the authors.
Authors’ Contributions: Raesi MK (First Author): Introduction writer/Methodologist/Statistical analyst (50%); Mohammadi M (Second Author): Discussion writer/Methodologist/Statistical analyst (50%)
Funding: None declared by the authors.
Urbanization is a socio-spatial process that is directly associated with the expansion of urban areas and the growth of the urban population. Developed countries such as the United States, Japan, and the United Kingdom have already completed their urbanization processes. The spatial structure of cities plays a significant role in their sustainable development. One of the key stages in analyzing the urban spatial structure is identifying the urban centers. A central assumption in most urban economic models is that all jobs in a city are located in the Central Business District (CBD), which constitutes the city’s core, where employment is concentrated and workers from all over the city commute for jobs. Another implicit assumption is that the city is circular and concentric. In this model, residents are distributed across a circular city and access the city center through radial routes. Since any point can potentially hold these conditions, identifying the core center of each city becomes essential [Wong, 2004; Chandio et al., 2011].
If we assume cities to be living, dynamic organisms, their central area functions as the heart [Shakoei, 2009]. Accordingly, the city center serves as the driving engine of urban development and hosts the most concentrated and significant urban functions. It seems that the city center is more of a functional concept rather than merely a physical one [Lin et al., 2012; Deswal & Laura, 2018].
The central area of a city encompasses a wide range of functions, and its position within the urban form and spatial structure is determined accordingly. The very concept of urban space depends on land occupation patterns and land uses, which in turn reflect activities and functions. Therefore, in order to understand the central area of a city, it must be analyzed from multiple perspectives and related concepts should be identified. Concepts such as the city center, the old city center, the civic or administrative center, the commercial center, the inner-city zone, and the community center are frequently referenced in discussions of urban centers [Dezert & Bastie, 2003]. Considering these concepts and terminologies, the central area of cities carries a broad semantic load and encompasses a wide range of meanings, which must be applied according to urban functions, spatial structures, and forms.
The central area plays an important economic role, perhaps the most prominent function of all. When the functional roles of different urban zones are not clearly defined, the center of a large city is often regarded as the commercial core [Ahlfeldt & Wendland, 2013]. The economic role of the urban center is so significant that, despite suburban employment growth, many urban cores continue to host dense concentrations of jobs. This indicates that economic agglomeration (the benefits derived from the clustering of economic activities) still matters in many markets [Voith, 1988; Romein et al., 2009].
The advantages of economic agglomeration are so strong that, despite vast physical urban sprawl, the central core and the broader central area continue to attract activities into a defined territory. The central area also plays a vital historical role, as in many cases the central zone of contemporary cities coincides with their original nucleus and historic core, where urban transformations can be traced. Central areas typically host historic buildings with diverse uses: private residences, grand mansions, heritage structures, corporate headquarters, and governmental offices such as post and customs administrations. Moreover, historically, many native communities have resided in what is now regarded as the city center [Razzu, 2005]. From this perspective, the historical identity of the central area provides the city with a distinctive character, so much so that many cities are recognized through their central areas.
Indeed, city centers embody collective memory and serve as valuable public realms familiar to residents. This has made residential redevelopment of city centers a key component of contemporary urban regeneration strategies [Tallon & Bromley, 2004; Mokarram & Hojati, 2017; Mohit & Ali, 2006]. Consequently, central areas increasingly attract middle- and upper-income groups, leading to their revitalization and flourishing. Administrative-political functions are also concentrated in city centers. Historically, as cities formed and governance systems emerged, the initial administrative complexes were established in the urban core. Many cities and their centers were initially founded with this purpose. Furthermore, given the significance of city centers across various domains, they have always been politically prominent. The concentration of a substantial share of administrative-political activities in the central area demonstrates its critical role in urban functional spaces.
Another essential function of city centers lies in transportation. Accessibility is the defining feature of the urban core, and it plays the most influential role in land-use decisions within city centers, ensuring economic sustainability and functional efficiency [Kazemian, 2001]. High accessibility attracts diverse activities, fosters land-use competition, and maximizes density in central zones. Public transportation systems are typically most concentrated in city centers, with networks converging toward them. Thus, the central area serves as a major hub for generating and attracting intra- and intercity trips.
According to Jean-Paul Lacaze, the structure of a city emerges from the interplay of networks of poles, axes, and flows, including infrastructure networks (roads and other systems), built volumes, open spaces, economic and production flows, trade and consumption patterns, socio-cultural facilities, power relations, symbolic landmarks, and meanings. Other factors also shape urban structure, such as high-value land boundaries, activity types, job densities, residential densities, and socio-demographic structures. The city’s structure is the cumulative result of all such forces operating within urban space [Dezert & Bastie, 2003].
Several relevant studies have examined these dynamics. Cai et al. (2017), using large-scale geographic data, identified polycentric structures in Chinese cities such as Beijing, Shanghai, and Chongqing. Their findings indicated that each city contained one primary core and several secondary subcenters. Amjad et al. (2019) analyzed Peshawar’s core using indicators such as land value, rental prices, retail sales, vehicle and pedestrian flows, and land area. Their results identified Saddar Bazaar as the city’s central core, though its characteristics differed from the old city. Similarly, Parvez and Sadat (2020), applying the AHP model and GIS data including land, population distribution, water supply, waste management, and road networks assessed potential central cores in Bangladesh. Their findings revealed urban expansion trends and identified ideal locations for future metropolitan centers with necessary commercial preconditions. Razaghi et al. (2011) emphasized the complexity of urban structures in large cities and argued for a polycentric development model. They concluded that such a model optimized service provision and reduced unnecessary trips to the main core.
Since identifying central areas (here, in the case of Zahedan) continues to shape the city’s economic vitality and holds substantial historical, cultural, social, and political significance, recognizing urban centers enhances urban environmental quality and, most importantly, promotes sustainable urban development. Therefore, this study aims to investigate this issue.
Methodology
The present study is applied in nature and was conducted in Zahedan city in 2023. Zahedan, the capital of Sistan and Baluchestan Province, is the largest province in Iran. Geographically, Zahedan County is bordered by Sistan to the north, Kerman Province to the west, Pakistan to the east, and Khash County to the south. According to the 2016 census, the population of Zahedan was 592,968. The total area of the city is 8,123 hectares. The southern and southwestern parts of the city are located at higher elevations, while the altitude decreases toward the north. Zahedan is divided into five urban districts [Statistical Centre of Iran, 2022].
Data collection methods included library research and documentary review. The indices under investigation comprised the density of educational centers, banks, healthcare facilities, administrative offices, sports complexes, commercial centers, green spaces, religious institutions, military facilities, parking lots, catering facilities, recreational spaces, building density, population density, street quality, and land use in Zahedan. Due to constraints such as costs, time limitations, shortage of human resources, and the aim of minimizing potential errors, the study was limited to the mentioned indices.
Data related to these indices were obtained through the National Portal of the Statistical Centre of Iran, statistical yearbooks, and block-level data layers acquired from the Urban Planning and Management Center. After preparing the statistical blocks and collecting the required data, the information was integrated into the urban block layer of Zahedan using ArcGIS 10.3 software. Based on expert judgment, suitable ranges of distances from the studied facilities were determined using a five-point Likert scale and the Reclassify tool in ArcGIS 10.3. For this purpose, 12 urban studies experts including faculty members and researchers from Payame Noor University of Tehran were selected through purposive sampling. The number of experts was validated using Cronbach’s alpha.
The valuation of data was based on their impact on individuals and physical spaces, categorized into five zones ranging from “completely unsuitable” to “completely suitable”. To identify the urban cores of Zahedan, two analytical approaches were employed: Network Analysis and the Analytic Hierarchy Process (AHP).
Findings
The weights assigned to each informational layer, based on the analysis of criteria in Expert Choice software, were as follows: educational centers (0.12), banks (0.08), healthcare centers (0.12), administrative offices (0.05), sports facilities (0.09), commercial centers (0.09), green spaces (0.07), religious sites (0.04), military sites (0.06), parking lots (0.04), street quality (0.05), tourist reception facilities (0.04), recreational spaces (0.07), building density (0.05), and population density (0.03).
The examination of Zahedan’s spatial layers revealed that most administrative offices were concentrated in Districts 5, 2, and 3, which form the core of the study area. The largest number of recreational centers was located in the northern part of District 5. Similarly, the distribution of banks showed a concentration in the city center, particularly in Districts 2 and 5. Another influential factor in determining urban cores was the distribution of parking lots, which was densest in the central part of Zahedan. Some land uses, such as educational centers and religious facilities, had a wider distribution across the city.
Tourist reception facilities were mainly concentrated in the city center, as well as in Districts 1 and 2, but overall, they showed limited distribution throughout the city. Green spaces, however, were more widely distributed, with the highest concentration observed in Districts 4 and 5. The distribution of green spaces in these districts reflected limited availability of such land uses in the central city, where high building density and limited land accessibility hindered the development of green areas. The lowest presence of green spaces was noted in the northwestern part of the city.
The distribution of educational and healthcare centers had a significant impact on the formation of urban cores. Healthcare centers were spread relatively evenly across Zahedan, with the highest concentrations in northern District 5 and District 2. Educational facilities were most concentrated in Districts 1 and 2. As illustrated in the educational centers map, the northern areas had fewer educational facilities, while the city center had the greatest density of this land use.
The highest concentration of commercial centers was located in the central area of Zahedan, strongly contributing to the city’s polycentric structure. Religious facilities were distributed relatively evenly throughout the districts, though with greater concentration in the northern part of the city. Military and sports facilities were also more concentrated in the city center.
Street quality, building density, and population density are presented. The analysis of these three layers indicated that street quality was highest in the city center, while it was generally poor in the peripheral areas in all four directions. Streets in the northern part of the study area were of relatively lower quality.
After calculating the weights of criteria and sub-criteria, the respective layers were generated. Following existing standards and expert judgment, informational layers were created and weighted according to their importance. Through overlaying these weighted layers, composite maps were generated, and urban vulnerability was assessed based on each criterion. Finally, a comprehensive urban land-use vulnerability map was produced. The standardized maps of informational layers are presented. By combining these standardized layers and applying criteria weights, the final raster-based zoning map of urban vulnerability in Zahedan was obtained after applying minimum elimination and classification functions.
Results of Network Analysis
The central core of Zahedan was located in the city center, particularly in Districts 1, 2, and 5. Additionally, several sub-centers were identified across the city. In southern parts of Districts 1 and 5, new sub-centers were emerging, while in other districts, evidence of core formation was not clearly observed. According to the network analysis results, Zahedan had one main central core and several sub-cores. The existence of the main core in northern District 5 and Districts 1 and 2 was primarily due to the concentration of diverse infrastructures in these areas.
Results of the Analytic Hierarchy Process (AHP)
The results of the AHP method, similar to the network analysis, showed that Zahedan has one main central core located in the middle of the city, along with several sub-cores around the city and leaning toward the central area. Using this method, four sub-cores were identified across different parts of the city, while the network analysis revealed five sub-cores.
Discussion
In mono-centric cities, all workplaces are concentrated in a single location in close proximity to one another. In this model, transportation costs and the exchange of services are reduced. Specialized services and products are provided within this core. The firms and organizations located in this nucleus can benefit from economies of scale in the provision of public services and welfare facilities, as well as from the exchange of knowledge and ideas. Historically, the mono-centric development pattern of Zahedan is consistent with the original core of its older neighborhoods. In this model, there is a strong dependency on the city center for services from all parts of the city, making it more vulnerable in terms of transportation and traffic, and reliant on the public transportation system. In contrast, the polycentric development model of Zahedan is more compatible and aligned with the city’s spatial form, economy, and overall conditions. This model is more closely associated with realizing the concept of equity in urban planning, urban economy, and employment. Establishing a polycentric urban model has reduced centralization in commercial and service activities, leading to the emergence of new commercial and service cores on the city’s periphery. Such initiatives naturally result in a rational distribution of urban trips, a more efficient distribution of transportation across the road network, and a more effective penetration of major services into multiple neighborhoods in a coordinated manner. Furthermore, decentralization of commercial activities reduces both economic and time costs, which in turn contributes to the balanced development of peripheral settlements. Therefore, with proper planning and designing of a polycentric development model, it can be argued that citizens’ needs and services are met in optimal conditions. The communication structure and transportation network within this model also reduce the volume of inter-sectional connections between urban sub-cores and the central core, thereby lowering congestion not only at intersections but also within different urban cores, particularly in the central core of Zahedan [Razaghi et al., 2011].
Despite the expansion of Zahedan into a polycentric urban structure, this process appears to be in its initial stages since the main core, corresponding to the old fabric of the city, continues to retain its primacy as the primary urban nucleus within a hierarchical structure. According to Jun’s findings, in such polycentric cities, multiple sub-centers of employment exist, but one core is typically more concentrated and stronger than the others. Nevertheless, these newly emerging urban centers derive agglomeration economies through clustering of activities, which are not confined to a single center but distributed across a set of centers that maintain a degree of functional differentiation [Jun, 2020]. Consistent with these findings, Montazer, Hu and colleagues also emphasized lower land and rental costs, accessibility, reduced trips to the central business district, equitable distribution of land uses, and ease of urban center expansion [Montazer, 2016; Hu et al., 2018]. Arvin and colleagues similarly highlighted the potential for achieving desirable spatial development in Ahvaz through its transformation into a polycentric city [Arvin et al., 2020].
Cai and colleagues also introduced Beijing, Shanghai, and Chongqing as polycentric cities, characterized by one central core and several sub-cores [Cai et al., 2017]. Likewise, the results of the present study are aligned with those of Amjad and colleagues, who identified factors such as land and rental values, retailing, vehicle and pedestrian flows as influential in the formation of polycentric cities [Amjad et al., 2019].
Among the limitations of this study is the lack of examination of a broader range of indicators due to insufficient data and financial constraints. Accordingly, future studies are recommended to investigate urban cores with consideration of a wider spectrum of economic and service-related indicators.
Conclusion
The findings of this study indicate that Zahedan is in the process of transitioning toward a polycentric urban structure. Nevertheless, despite its physical growth over the past several decades, the central core (mono-centric structure) continues to maintain its priority over other emerging sub-cores in terms of service provision and employment.
Acknowledgments: The authors would like to express their gratitude to all individuals who participated in this study.
Ethical Permission: None declared by the authors.
Conflict of Interest: None declared by the authors.
Authors’ Contributions: Raesi MK (First Author): Introduction writer/Methodologist/Statistical analyst (50%); Mohammadi M (Second Author): Discussion writer/Methodologist/Statistical analyst (50%)
Funding: None declared by the authors.
References
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