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Received: 2024/10/4 | Accepted: 2025/01/22 | Published: 2025/01/29
Received: 2024/10/4 | Accepted: 2025/01/22 | Published: 2025/01/29
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Dadkhah N, Seyed Al-Hosseini S, Daneshvar M, Saghatoleslami A. Evaluation of Building Density Criteria in Urban Development Plans; Mashhad. GeoRes 2025; 40 (1) :1-9
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1- Department of Urban Planning, Mashhad Branch, Islamic Azad University, Mashhad, Iran
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Background
The weakness in the design and implementation of urban development plans has led to uncoordinated urban growth, depletion of natural resources, increased social and economic problems, and the uneven expansion of services. These issues highlight the importance of considering building density as a key tool in managing sustainable urban development.
Previous Studies
Previous studies have emphasized the importance of accurately determining building density for sustainable urban development. For instance, Massoud et al. (2020) and Abbasi et al. (2022) highlighted the consequences of unbalanced urban growth, such as urban sprawl and one-sided development. Abedini & Karimi (2019) identified density as one of the most critical issues in urban planning. Ghorbani & Jafari (2015) pointed to the failure of development plans in integrating practical realities with conceptual ideals. Afsharnia et al. (2021) and Marzban et al. (2018) called for a revision of traditional approaches and operational criteria in determining density. Additionally, Allies and Morrison (2021) considered building density and height as effective tools for policymaking. Other studies have addressed the social and economic impacts of high density (Azhodi, 2023) and the importance of aligning with market indicators (Darbanian & Siyami, 2017), both of which have a direct influence on urban decision-making.
Aim(s)
This study was conducted with the aim of evaluating the criteria for determining building density in urban development plans in District 9 of Mashhad city.
Research Type
The present study was applied in terms of its objective.
Research Society, Place, and Time
The present study was conducted in District 9 of the city of Mashhad in 2024. The statistical population of this research included the native residents of District 9 in Mashhad, comprising approximately 327,000 individuals according to the most recent census.
Sampling Method and Number
Using the Morgan formula and a cluster sampling method, a total of 384 individuals were selected as the statistical sample.
Used Devices & Materials
In this study, the main data collection tool was a researcher-made questionnaire, developed based on indicators extracted from both domestic and international research literature. The questionnaire consisted of 16 items and was designed using a 5-point Likert scale (ranging from 1 = very low to 5 = very high). To ensure content validity, the questionnaire was reviewed by faculty members from the Urban Planning Department at Islamic Azad University of Mashhad. Its reliability was assessed using Cronbach's alpha test, yielding a value of 0.840, indicating a good level of internal consistency. The collected data were analyzed using Smart PLS version 4 and Structural Equation Modeling (SEM), which was applied to model the causal relationships among the study variables and to test the research hypotheses.
Findings by Text
The data analysis of 384 residents from District 9 of Mashhad was conducted using Structural Equation Modeling (SEM) via Smart PLS software. Results revealed four key factors influenced urban development in relation to building density: land-to-space ratio, access to urban services, spatial quality, and environmental impact. These were assessed using 16 questionnaire items.
Path coefficient analysis showed that spatial quality had the strongest effect on urban development (path coefficient = 0.821), followed closely by access to services (coefficient = 0.793; Table 1).
Table 1. Composite Reliability and Cronbach's Alpha for the Research Indicators
All factor loadings exceeded 0.7, indicating strong correlations between each item and its associated construct (Table 2).
Table 2. T-Statistic and standard deviation among the research participants
T-values for all relationships were above 1.96 at the 0.05 significance level, confirming the statistical significance of the paths. Notably, the effect of spatial quality on development had a t-value of 10.12 (Table 3).
Table 3. Q² Predict and R Square Results
Reliability and construct validity were supported by acceptable AVE (>0.5) and CR (>0.7) values (Table 4).
Table 4. Path Coefficients, Influencing and Affected Factors
The final conceptual model, derived from statistical analysis, illustrated the direct and causal relationships between these four factors and urban development (Figure 1).
Figure 1. Factor Loading Model for Evaluating Building Density Criteria in Urban Development Plans (District 9, Mashhad City)
Overall, the findings suggested that building density, when strategically managed to enhance space quality, service accessibility, and environmental sustainability, can act as a catalyst for positive urban growth. Otherwise, it risks yielding adverse consequences.
Main Comparisons to Similar Studies
Unlike the study by Azhodi (2023), which focuses on high-rise construction outside the master development plan and broadly examined the role of building density in urban development plans, the present research utilized structural equation modeling and quantitative analysis to explore a more precise relationship between four key factors of building density (land-to-space ratio, access to urban services, space quality, and environmental impact) and urban development.
While the study by Rezaei et al. (2017) addresses the challenges of abstract decision-making in the field of density planning, it lackes a defined geographical focus, limiting its applicability to District 9 of Mashhad. In contrast, the current study specifically targeted this district and employs cluster sampling for accurate participant selection. Darbanian and Siyami (2017) also focus on District 9, analyzing the relationship between detailed urban plans and sustainable municipal revenue, but use a qualitative approach. In comparison, this research adopted a quantitative and structural method, offering more precise insights into the impact of building density. Likewise, Bagherizadeh et al. (2022) employ a descriptive-analytical method for density optimization, whose methodology could be localized for the present study. On the international level, studies by Allies and Morrison (2021) and Kurvinen & Saari (2020) explore the relationship between density, urban development, and infrastructure costs. Although their environmental contexts differ, their quantitative and analytical approaches serve as useful methodological models for the current research. Additionally, policy guidelines provided by the Government of Ireland (2018) and the study by Kickert et al. (2014) on development capacity in station areas offer complementary resources for effectively managing building density in District 9 of Mashhad.
Suggestions
The recommendations presented in this study include establishing clear regulations to control building density (FAR), expanding public transportation to reduce reliance on private vehicles, creating green and public spaces to enhance quality of life, conducting balanced assessments of urban service needs such as schools and healthcare centers, and providing environmental education programs to raise residents’ awareness of sustainable construction practices, especially in high-density areas.
Conclusion
In terms of parameters related to building density, the indicators of environmental impact and access to urban services have a stronger influence on the dependent parameter (urban development plans). In contrast, the parameters of floor area ratio (FAR) and spatial quality show comparatively lower levels of influence. Additionally, the sub-indicators of social participation and environmental sustainability reflect favorable conditions for achieving effective urban development plans and optimal building density.
Acknowledgments: We express our sincere gratitude to the experienced urban planning experts and municipal managers who supported us throughout this study.
Ethical Approval: There is no ethical issue to report by the authors.
Conflict of Interest: The present article is extracted from the dissertation titled “Assessment of Building Density Criteria in Urban Development Plans Based on Development Capacities with Emphasis on Balancing Social and Economic Components – Case Study: District 9 of Mashhad City”.
Authors' Contributions: Neda Dadkhah (First Author): Main Researcher (60%); Seyed Moslem Seyedhosseini (Second Author): Introduction Writer / Methodologist (30%); Maryam Daneshvar (Third Author): Statistical Analyst (5%); Amidoleslam Sogholeslami (Fourth Author): Assistant Researcher (5%)
Funding: The research expenses were fully covered by the first author.
The weakness in the design and implementation of urban development plans has led to uncoordinated urban growth, depletion of natural resources, increased social and economic problems, and the uneven expansion of services. These issues highlight the importance of considering building density as a key tool in managing sustainable urban development.
Previous Studies
Previous studies have emphasized the importance of accurately determining building density for sustainable urban development. For instance, Massoud et al. (2020) and Abbasi et al. (2022) highlighted the consequences of unbalanced urban growth, such as urban sprawl and one-sided development. Abedini & Karimi (2019) identified density as one of the most critical issues in urban planning. Ghorbani & Jafari (2015) pointed to the failure of development plans in integrating practical realities with conceptual ideals. Afsharnia et al. (2021) and Marzban et al. (2018) called for a revision of traditional approaches and operational criteria in determining density. Additionally, Allies and Morrison (2021) considered building density and height as effective tools for policymaking. Other studies have addressed the social and economic impacts of high density (Azhodi, 2023) and the importance of aligning with market indicators (Darbanian & Siyami, 2017), both of which have a direct influence on urban decision-making.
Aim(s)
This study was conducted with the aim of evaluating the criteria for determining building density in urban development plans in District 9 of Mashhad city.
Research Type
The present study was applied in terms of its objective.
Research Society, Place, and Time
The present study was conducted in District 9 of the city of Mashhad in 2024. The statistical population of this research included the native residents of District 9 in Mashhad, comprising approximately 327,000 individuals according to the most recent census.
Sampling Method and Number
Using the Morgan formula and a cluster sampling method, a total of 384 individuals were selected as the statistical sample.
Used Devices & Materials
In this study, the main data collection tool was a researcher-made questionnaire, developed based on indicators extracted from both domestic and international research literature. The questionnaire consisted of 16 items and was designed using a 5-point Likert scale (ranging from 1 = very low to 5 = very high). To ensure content validity, the questionnaire was reviewed by faculty members from the Urban Planning Department at Islamic Azad University of Mashhad. Its reliability was assessed using Cronbach's alpha test, yielding a value of 0.840, indicating a good level of internal consistency. The collected data were analyzed using Smart PLS version 4 and Structural Equation Modeling (SEM), which was applied to model the causal relationships among the study variables and to test the research hypotheses.
Findings by Text
The data analysis of 384 residents from District 9 of Mashhad was conducted using Structural Equation Modeling (SEM) via Smart PLS software. Results revealed four key factors influenced urban development in relation to building density: land-to-space ratio, access to urban services, spatial quality, and environmental impact. These were assessed using 16 questionnaire items.
Path coefficient analysis showed that spatial quality had the strongest effect on urban development (path coefficient = 0.821), followed closely by access to services (coefficient = 0.793; Table 1).
Table 1. Composite Reliability and Cronbach's Alpha for the Research Indicators
All factor loadings exceeded 0.7, indicating strong correlations between each item and its associated construct (Table 2).
Table 2. T-Statistic and standard deviation among the research participants
T-values for all relationships were above 1.96 at the 0.05 significance level, confirming the statistical significance of the paths. Notably, the effect of spatial quality on development had a t-value of 10.12 (Table 3).
Table 3. Q² Predict and R Square Results
Reliability and construct validity were supported by acceptable AVE (>0.5) and CR (>0.7) values (Table 4).
Table 4. Path Coefficients, Influencing and Affected Factors
The final conceptual model, derived from statistical analysis, illustrated the direct and causal relationships between these four factors and urban development (Figure 1).
Figure 1. Factor Loading Model for Evaluating Building Density Criteria in Urban Development Plans (District 9, Mashhad City)
Overall, the findings suggested that building density, when strategically managed to enhance space quality, service accessibility, and environmental sustainability, can act as a catalyst for positive urban growth. Otherwise, it risks yielding adverse consequences.
Main Comparisons to Similar Studies
Unlike the study by Azhodi (2023), which focuses on high-rise construction outside the master development plan and broadly examined the role of building density in urban development plans, the present research utilized structural equation modeling and quantitative analysis to explore a more precise relationship between four key factors of building density (land-to-space ratio, access to urban services, space quality, and environmental impact) and urban development.
While the study by Rezaei et al. (2017) addresses the challenges of abstract decision-making in the field of density planning, it lackes a defined geographical focus, limiting its applicability to District 9 of Mashhad. In contrast, the current study specifically targeted this district and employs cluster sampling for accurate participant selection. Darbanian and Siyami (2017) also focus on District 9, analyzing the relationship between detailed urban plans and sustainable municipal revenue, but use a qualitative approach. In comparison, this research adopted a quantitative and structural method, offering more precise insights into the impact of building density. Likewise, Bagherizadeh et al. (2022) employ a descriptive-analytical method for density optimization, whose methodology could be localized for the present study. On the international level, studies by Allies and Morrison (2021) and Kurvinen & Saari (2020) explore the relationship between density, urban development, and infrastructure costs. Although their environmental contexts differ, their quantitative and analytical approaches serve as useful methodological models for the current research. Additionally, policy guidelines provided by the Government of Ireland (2018) and the study by Kickert et al. (2014) on development capacity in station areas offer complementary resources for effectively managing building density in District 9 of Mashhad.
Suggestions
The recommendations presented in this study include establishing clear regulations to control building density (FAR), expanding public transportation to reduce reliance on private vehicles, creating green and public spaces to enhance quality of life, conducting balanced assessments of urban service needs such as schools and healthcare centers, and providing environmental education programs to raise residents’ awareness of sustainable construction practices, especially in high-density areas.
Conclusion
In terms of parameters related to building density, the indicators of environmental impact and access to urban services have a stronger influence on the dependent parameter (urban development plans). In contrast, the parameters of floor area ratio (FAR) and spatial quality show comparatively lower levels of influence. Additionally, the sub-indicators of social participation and environmental sustainability reflect favorable conditions for achieving effective urban development plans and optimal building density.
Acknowledgments: We express our sincere gratitude to the experienced urban planning experts and municipal managers who supported us throughout this study.
Ethical Approval: There is no ethical issue to report by the authors.
Conflict of Interest: The present article is extracted from the dissertation titled “Assessment of Building Density Criteria in Urban Development Plans Based on Development Capacities with Emphasis on Balancing Social and Economic Components – Case Study: District 9 of Mashhad City”.
Authors' Contributions: Neda Dadkhah (First Author): Main Researcher (60%); Seyed Moslem Seyedhosseini (Second Author): Introduction Writer / Methodologist (30%); Maryam Daneshvar (Third Author): Statistical Analyst (5%); Amidoleslam Sogholeslami (Fourth Author): Assistant Researcher (5%)
Funding: The research expenses were fully covered by the first author.
Keywords:
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