Bilingual
En/Fa
Geographical Research is Published in both Persian and English Full-text.
Volume 37, Issue 3 (2022)
GeoRes 2022, 37(3): 391-398 |
Back to browse issues page
Article Type:
Subject:
History
Received: 2022/02/14 | Accepted: 2022/05/12 | Published: 2022/07/1
Received: 2022/02/14 | Accepted: 2022/05/12 | Published: 2022/07/1
How to cite this article
Mohagheghi P, Ghadami M, Azimi Amoli J, Janbaz Ghobadi G. Physical-Economic Resilience Assessment of District 12 of Tehran City Confronting Earthquake. GeoRes 2022; 37 (3) :391-398
URL: http://georesearch.ir/article-1-1295-en.html
URL: http://georesearch.ir/article-1-1295-en.html
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Rights and permissions
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
1- Noor Branch, Islamic Azad University, Noor, Iran
2- Mazandaran University, Babolsar, Iran
2- Mazandaran University, Babolsar, Iran
Full-Text (HTML) (106 Views)
Introduction
The most effective approach to addressing hazards is to conceptualize the relationship between resilience and natural disasters, particularly earthquakes. This involves understanding how social, economic, institutional, and political capacities influence the enhancement of settlement resilience across multiple dimensions [Rezaie et al., 2016]. Urban resilience is a development strategy applicable in geographical, social, economic, and other domains with potential for growth. This perspective introduces a new and compelling dimension to planning policies, offering a fresh outlook for urban planning practices [Zandmoghaddam & Mullaie, 2020]. The significance of natural disasters, especially earthquakes has been widely acknowledged; notably, the United Nations General Assembly designated 1990–2000 as the International Decade for Natural Disaster Reduction [Mavadat et al., 2019].
Iran, due to its environmental–human characteristics and geographical setting, is among the most vulnerable seismically active countries in the world [Amanpoor et al., 2018]. According to the UNDP Disaster Risk Index, Iran ranks second after Armenia in earthquake vulnerability, and 31 of the 40 types of natural disasters have occurred within the country [Nasiri Hendkhaleh, 2019]. Considering that more than 60% of the national population lives in urban areas and that many Iranian cities suffer from inadequate building quality, aging urban fabric, and nonstandard construction materials assessing the potential damages from natural hazards becomes imperative. With proper foresight regarding the potential behavior of urban structures during earthquakes, preventive measures can be undertaken to minimize losses. Therefore, addressing factors that can enhance urban resilience is essential for fostering more sustainable cities.
The concept of resilience was introduced by Holling, the “father of resilience,” in 1973 as a descriptive term in ecology and has since been widely employed in various scientific fields, including urban planning, disaster management, and ecology [Habibi et al., 2013; Ebrahimzadeh et al., 2018]. According to Karrholm, resilience refers to the extent of disturbance a system can absorb before its structure transforms into a different configuration through changes in controlling parameters and processes [Jazayeri et al., 2018].
Resilience comprises four main dimensions: Physical, economic, social, and institutional. The social dimension reflects differences in social capacity among communities and includes indicators such as knowledge, skills, attitudes, health, well-being, and demographic characteristics. The economic dimension reflects economic stability and includes indicators such as income sources, capital, savings, household assets, and insurance. The physical dimension evaluates community response and recovery capacity after disasters, including shelters, health facilities, and infrastructure such as pipelines and roads. The institutional dimension encompasses risk-reduction characteristics, planning capacity, and past disaster experience [Ebrahimzadeh et al., 2018].
Generally, two primary strategies exist for coping with natural hazards: predictive strategies and resilience strategies. Predictive strategies address known risks, whereas resilience strategies focus on strengthening a community’s capacity for preparedness, absorption, recovery, and successful adaptation following adverse events [Bastaminya et al., 2015].
Previous research has extensively examined various dimensions of resilience in Iranian cities. Rezaie et al. [2016] have reported that, in assessing the physical resilience of urban communities against earthquakes, building resistance and accessibility were the most and least influential indicators, respectively. Norozi et al. [2017], in evaluating social resilience in District 12 of Tehran, observed generally low levels of community preparedness, with demographic characteristics exerting the greatest positive influence on neighborhood resilience. Pashapour and Pourakrami [2017] have assessed physical resilience in the same district and found that only 1.03% of the area exhibited high resilience, while 74.64% demonstrated moderate resilience and 24.33% low resilience. Bagheri Maragheh et al. [2022] have reported that 17 of 26 neighborhoods in Shirvan city possess low resilience to seismic hazards. Similarly, Salehipour et al. [2021] have demonstrated that none of the neighborhoods in Razan city exhibited high or very high earthquake preparedness, attributing low resilience to weak institutional structures and limited economic capacity among residents. International studies further reinforce these findings: Kusumastuti et al. [2014] have developed resilience indices for two Indonesian cities and found both to be generally resilient, though still in need of improvement. Suarez et al. [2016] have assessed resilience in 50 Spanish cities and concluded that many remain distant from achieving acceptable resilience levels, calling for reduced resource consumption, support for local commerce, enhanced citizen participation, and economic diversification.
Given that post-disaster management in Iran remains inadequate and that earthquakes such as those in Bam and Rudbar have resulted in severe social and economic losses examining resilience dimensions, approaches, and concepts within urban communities exposed to natural hazards is essential [Bastami Nia et al., 2015]. Tehran’s District 12, which contains numerous administrative functions and some of the city’s most valuable historical structures and urban fabrics, faces significant spatial imbalance. Its vulnerability is exacerbated by deteriorated and historic urban fabric, making resilience planning a necessary priority. Accordingly, this study focuses on evaluating the physical–economic dimensions of resilience in District 12 of Tehran.
Methodology
District 12 is one of the oldest areas and the commercial core of Tehran, located in the city center. Its population growth rate is nearly half that of the city as a whole, while the growth rate of households significantly exceeds population growth. The concentration of traditional bazaars, ministries, and administrative offices is a defining feature of this district, resulting in a daytime population of nearly one million people, whereas the resident population is approximately 200,000 [Bavand Consulting Engineers, 2006]. This situation is noteworthy for two reasons: the daytime population density generates various disturbances for permanent residents and reduces the district’s residential appeal, and in the event of an earthquake during peak activity hours, the magnitude of human and economic losses would be substantially greater. Accordingly, District 12 is considered highly vulnerable to natural hazards, particularly earthquakes, during critical situations [Statistical Center of Iran, 2017], and a strong earthquake in Tehran would cause irreversible losses in this district.
District 12 consists of six subdistricts and fourteen neighborhoods, bounded by Districts 6 and 7 to the north, Districts 15 and 16 to the south, District 11 to the west, and Districts 13 and 14 as well as Shahid Mahallati Highway to the east [Karami et al., 2016].
This descriptive–analytical research employed library studies and expert consultation to identify the criteria influencing physical–economic resilience against earthquakes in District 12. Data collection was conducted through documentary methods and a survey using a structured questionnaire. After identifying the relevant indicators and gathering the required spatial and statistical data, the resilience indicators were weighted by experts through 100 completed questionnaires, and the Analytic Network Process (ANP) was used for analysis. Factor analysis and ArcGIS were applied to identify spatial patterns, while spatial statistics tools, including Anselin Local Moran’s I and Cluster & Outlier Analysis, were used to examine the spatial distribution of resilience indicators within the district. Based on these procedures, the final resilience map of the district was produced.
To assess physical–economic resilience, six main criteria and nineteen subcriteria were considered. The selection of indicators was based on four principles: relevance to resilience and urban form according to existing literature; availability of qualitative and quantitative data; review of national and international research and comparable experiences; and expert interviews. Accordingly, the components of urban form affecting earthquake resilience were identified.
To evaluate the level of physical–economic resilience in District 12, a questionnaire was designed to determine the relative importance of each indicator and distributed among specialists. The weighting of the criteria and subcriteria in the ANP model was performed using the Super Decisions software. In this stage, pairwise comparisons were conducted to determine the relative significance of the main criteria based on the study objectives.
Findings
The analysis revealed that among the indicators, the movement and accessibility network had the greatest impact on resilience, while the characteristics of the land base had the least influence. There was a significant correlation between earthquake resilience in District 12 and the physical (r=0.729) and economic (r=0.767) dimensions (p<0.001). Six factors were identified as the most influential on resilience in the study area. The eigenvalues of all six factors were greater than one, and collectively, they explained 96.01% of the variance in the district’s resilience.
To examine the spatial distribution of resilience indicators within District 12, Anselin Local Moran’s I, Cluster & Outlier Analysis, and related tools in the Spatial Statistics suite of ArcGIS were used. These methods allowed identification of areas with high or low values of geographic features and highlighted features that deviated significantly from their surroundings. Local Moran’s I was calculated as a function of each feature’s attribute, the mean attribute, and the final weight between features.
The spatial analysis showed that large portions of the built environment in District 12 fall within low-to-medium resilience ranges. The central part of the district, characterized by non-standard structural systems and aging buildings, exhibited low to relatively low resilience, which would exacerbate human and economic losses in the event of natural disasters. Only limited areas in the northern parts of the district demonstrated high to relatively high resilience.
From an economic perspective, neighborhoods such as Bazaar, Baharestan, and Mokhtari displayed the best resilience conditions, whereas Pamenar and Harandi were the least resilient. Global Moran’s I spatial autocorrelation analysis, which assesses the spatial distribution and clustering of features, indicated that the overall pattern of resilience in the study area was not clustered (I=0.1875; Z=15.1349; p<0.00001). Approximately 53.13% of the district’s area was classified as very low resilience, while only 7.19% of the area exhibited very high resilience.
Discussion
This study aimed to assess the physical and economic resilience of District 12 in Tehran. As the commercial heart of the city, District 12 is exposed to high risk due to its unique location and environmental conditions. Accordingly, evaluating resilience is a critical component of urban management. To assess resilience in this district, various influential indicators were analyzed using Anselin Local Moran’s I and FANP models.
The results indicate that large portions of the built environment in District 12 fall within low to medium resilience ranges. In the central areas, where standard structural systems are lacking, aging and deteriorated buildings exhibit low to relatively low resilience, which would exacerbate human and economic losses during natural disasters. Only limited areas in the northern parts of the district demonstrate high to relatively high resilience. Overall, regarding physical resilience, Districts 6 and 1 display the highest levels, while District 3 shows the lowest. Economically, neighborhoods such as Bazaar, Baharestan, and Mokhtari have the best resilience, whereas Pamenar and Harandi exhibit the poorest conditions. Spatial analysis using the Anselin Local Moran’s I model revealed that approximately 53.13% of the study area falls under very low resilience, while only 7.19% is classified as very high resilience.
Today, both natural and human-induced hazards cause extensive damage to urban areas, making the concept of resilience crucial for mitigating disaster impacts. Physical and economic resilience are among the most significant dimensions, allowing for evaluation of communities based on their structural and geographical characteristics that influence their response to hazards. Due to the country’s natural tectonic features, earthquakes are among the most destructive threats to human life, and historical analyses show that certain regions have suffered significant casualties and economic losses from these disasters.
Resilience zoning enables targeted interventions in each neighborhood of District 12 to reduce vulnerability during crises. The findings of this study are consistent with previous research by Pashapur and Pourakrami (2017), Bagherimaragheh et al. (2020), and Salehipour et al. (2021).
Based on the analysis and the identified indicators of physical and economic resilience in District 12, the following practical recommendations are proposed:
Conclusion
Based on the present study, District 12, as the area under investigation, exhibits physical and economic resilience below the optimal level. The extent to which each district meets the key resilience criteria is neither uniform nor consistent, and there are significant differences in resilience indicators among the neighborhoods of District 12, Tehran. These disparities should be prioritized by urban managers to enhance overall resilience in the district.
Acknowledgments: The authors sincerely thank all the esteemed professors and officials at Islamic Azad University, Noor Branch, who supported this study.
Ethical Permission: No ethical issues were reported by the authors.
Conflict of Interest: This article has no conflicts of interest with any organizations or individuals.
Author Contributions: Mohagheghi P(first author), Introduction Writer/Discussion Writer/Methodologist/Main Researcher (50%); Ghadami M (second author), Introduction Writer/Discussion Writer (25%); Azimi Amoli J (third author), Statistical Analyst (15%); Janbaz Ghobadi Gh (fourth author); Methodologist (10%)
Funding: This article is derived from the PhD dissertation of Parisa Mohagheghi, and all expenses were covered by the student.
The most effective approach to addressing hazards is to conceptualize the relationship between resilience and natural disasters, particularly earthquakes. This involves understanding how social, economic, institutional, and political capacities influence the enhancement of settlement resilience across multiple dimensions [Rezaie et al., 2016]. Urban resilience is a development strategy applicable in geographical, social, economic, and other domains with potential for growth. This perspective introduces a new and compelling dimension to planning policies, offering a fresh outlook for urban planning practices [Zandmoghaddam & Mullaie, 2020]. The significance of natural disasters, especially earthquakes has been widely acknowledged; notably, the United Nations General Assembly designated 1990–2000 as the International Decade for Natural Disaster Reduction [Mavadat et al., 2019].
Iran, due to its environmental–human characteristics and geographical setting, is among the most vulnerable seismically active countries in the world [Amanpoor et al., 2018]. According to the UNDP Disaster Risk Index, Iran ranks second after Armenia in earthquake vulnerability, and 31 of the 40 types of natural disasters have occurred within the country [Nasiri Hendkhaleh, 2019]. Considering that more than 60% of the national population lives in urban areas and that many Iranian cities suffer from inadequate building quality, aging urban fabric, and nonstandard construction materials assessing the potential damages from natural hazards becomes imperative. With proper foresight regarding the potential behavior of urban structures during earthquakes, preventive measures can be undertaken to minimize losses. Therefore, addressing factors that can enhance urban resilience is essential for fostering more sustainable cities.
The concept of resilience was introduced by Holling, the “father of resilience,” in 1973 as a descriptive term in ecology and has since been widely employed in various scientific fields, including urban planning, disaster management, and ecology [Habibi et al., 2013; Ebrahimzadeh et al., 2018]. According to Karrholm, resilience refers to the extent of disturbance a system can absorb before its structure transforms into a different configuration through changes in controlling parameters and processes [Jazayeri et al., 2018].
Resilience comprises four main dimensions: Physical, economic, social, and institutional. The social dimension reflects differences in social capacity among communities and includes indicators such as knowledge, skills, attitudes, health, well-being, and demographic characteristics. The economic dimension reflects economic stability and includes indicators such as income sources, capital, savings, household assets, and insurance. The physical dimension evaluates community response and recovery capacity after disasters, including shelters, health facilities, and infrastructure such as pipelines and roads. The institutional dimension encompasses risk-reduction characteristics, planning capacity, and past disaster experience [Ebrahimzadeh et al., 2018].
Generally, two primary strategies exist for coping with natural hazards: predictive strategies and resilience strategies. Predictive strategies address known risks, whereas resilience strategies focus on strengthening a community’s capacity for preparedness, absorption, recovery, and successful adaptation following adverse events [Bastaminya et al., 2015].
Previous research has extensively examined various dimensions of resilience in Iranian cities. Rezaie et al. [2016] have reported that, in assessing the physical resilience of urban communities against earthquakes, building resistance and accessibility were the most and least influential indicators, respectively. Norozi et al. [2017], in evaluating social resilience in District 12 of Tehran, observed generally low levels of community preparedness, with demographic characteristics exerting the greatest positive influence on neighborhood resilience. Pashapour and Pourakrami [2017] have assessed physical resilience in the same district and found that only 1.03% of the area exhibited high resilience, while 74.64% demonstrated moderate resilience and 24.33% low resilience. Bagheri Maragheh et al. [2022] have reported that 17 of 26 neighborhoods in Shirvan city possess low resilience to seismic hazards. Similarly, Salehipour et al. [2021] have demonstrated that none of the neighborhoods in Razan city exhibited high or very high earthquake preparedness, attributing low resilience to weak institutional structures and limited economic capacity among residents. International studies further reinforce these findings: Kusumastuti et al. [2014] have developed resilience indices for two Indonesian cities and found both to be generally resilient, though still in need of improvement. Suarez et al. [2016] have assessed resilience in 50 Spanish cities and concluded that many remain distant from achieving acceptable resilience levels, calling for reduced resource consumption, support for local commerce, enhanced citizen participation, and economic diversification.
Given that post-disaster management in Iran remains inadequate and that earthquakes such as those in Bam and Rudbar have resulted in severe social and economic losses examining resilience dimensions, approaches, and concepts within urban communities exposed to natural hazards is essential [Bastami Nia et al., 2015]. Tehran’s District 12, which contains numerous administrative functions and some of the city’s most valuable historical structures and urban fabrics, faces significant spatial imbalance. Its vulnerability is exacerbated by deteriorated and historic urban fabric, making resilience planning a necessary priority. Accordingly, this study focuses on evaluating the physical–economic dimensions of resilience in District 12 of Tehran.
Methodology
District 12 is one of the oldest areas and the commercial core of Tehran, located in the city center. Its population growth rate is nearly half that of the city as a whole, while the growth rate of households significantly exceeds population growth. The concentration of traditional bazaars, ministries, and administrative offices is a defining feature of this district, resulting in a daytime population of nearly one million people, whereas the resident population is approximately 200,000 [Bavand Consulting Engineers, 2006]. This situation is noteworthy for two reasons: the daytime population density generates various disturbances for permanent residents and reduces the district’s residential appeal, and in the event of an earthquake during peak activity hours, the magnitude of human and economic losses would be substantially greater. Accordingly, District 12 is considered highly vulnerable to natural hazards, particularly earthquakes, during critical situations [Statistical Center of Iran, 2017], and a strong earthquake in Tehran would cause irreversible losses in this district.
District 12 consists of six subdistricts and fourteen neighborhoods, bounded by Districts 6 and 7 to the north, Districts 15 and 16 to the south, District 11 to the west, and Districts 13 and 14 as well as Shahid Mahallati Highway to the east [Karami et al., 2016].
This descriptive–analytical research employed library studies and expert consultation to identify the criteria influencing physical–economic resilience against earthquakes in District 12. Data collection was conducted through documentary methods and a survey using a structured questionnaire. After identifying the relevant indicators and gathering the required spatial and statistical data, the resilience indicators were weighted by experts through 100 completed questionnaires, and the Analytic Network Process (ANP) was used for analysis. Factor analysis and ArcGIS were applied to identify spatial patterns, while spatial statistics tools, including Anselin Local Moran’s I and Cluster & Outlier Analysis, were used to examine the spatial distribution of resilience indicators within the district. Based on these procedures, the final resilience map of the district was produced.
To assess physical–economic resilience, six main criteria and nineteen subcriteria were considered. The selection of indicators was based on four principles: relevance to resilience and urban form according to existing literature; availability of qualitative and quantitative data; review of national and international research and comparable experiences; and expert interviews. Accordingly, the components of urban form affecting earthquake resilience were identified.
To evaluate the level of physical–economic resilience in District 12, a questionnaire was designed to determine the relative importance of each indicator and distributed among specialists. The weighting of the criteria and subcriteria in the ANP model was performed using the Super Decisions software. In this stage, pairwise comparisons were conducted to determine the relative significance of the main criteria based on the study objectives.
Findings
The analysis revealed that among the indicators, the movement and accessibility network had the greatest impact on resilience, while the characteristics of the land base had the least influence. There was a significant correlation between earthquake resilience in District 12 and the physical (r=0.729) and economic (r=0.767) dimensions (p<0.001). Six factors were identified as the most influential on resilience in the study area. The eigenvalues of all six factors were greater than one, and collectively, they explained 96.01% of the variance in the district’s resilience.
To examine the spatial distribution of resilience indicators within District 12, Anselin Local Moran’s I, Cluster & Outlier Analysis, and related tools in the Spatial Statistics suite of ArcGIS were used. These methods allowed identification of areas with high or low values of geographic features and highlighted features that deviated significantly from their surroundings. Local Moran’s I was calculated as a function of each feature’s attribute, the mean attribute, and the final weight between features.
The spatial analysis showed that large portions of the built environment in District 12 fall within low-to-medium resilience ranges. The central part of the district, characterized by non-standard structural systems and aging buildings, exhibited low to relatively low resilience, which would exacerbate human and economic losses in the event of natural disasters. Only limited areas in the northern parts of the district demonstrated high to relatively high resilience.
From an economic perspective, neighborhoods such as Bazaar, Baharestan, and Mokhtari displayed the best resilience conditions, whereas Pamenar and Harandi were the least resilient. Global Moran’s I spatial autocorrelation analysis, which assesses the spatial distribution and clustering of features, indicated that the overall pattern of resilience in the study area was not clustered (I=0.1875; Z=15.1349; p<0.00001). Approximately 53.13% of the district’s area was classified as very low resilience, while only 7.19% of the area exhibited very high resilience.
Discussion
This study aimed to assess the physical and economic resilience of District 12 in Tehran. As the commercial heart of the city, District 12 is exposed to high risk due to its unique location and environmental conditions. Accordingly, evaluating resilience is a critical component of urban management. To assess resilience in this district, various influential indicators were analyzed using Anselin Local Moran’s I and FANP models.
The results indicate that large portions of the built environment in District 12 fall within low to medium resilience ranges. In the central areas, where standard structural systems are lacking, aging and deteriorated buildings exhibit low to relatively low resilience, which would exacerbate human and economic losses during natural disasters. Only limited areas in the northern parts of the district demonstrate high to relatively high resilience. Overall, regarding physical resilience, Districts 6 and 1 display the highest levels, while District 3 shows the lowest. Economically, neighborhoods such as Bazaar, Baharestan, and Mokhtari have the best resilience, whereas Pamenar and Harandi exhibit the poorest conditions. Spatial analysis using the Anselin Local Moran’s I model revealed that approximately 53.13% of the study area falls under very low resilience, while only 7.19% is classified as very high resilience.
Today, both natural and human-induced hazards cause extensive damage to urban areas, making the concept of resilience crucial for mitigating disaster impacts. Physical and economic resilience are among the most significant dimensions, allowing for evaluation of communities based on their structural and geographical characteristics that influence their response to hazards. Due to the country’s natural tectonic features, earthquakes are among the most destructive threats to human life, and historical analyses show that certain regions have suffered significant casualties and economic losses from these disasters.
Resilience zoning enables targeted interventions in each neighborhood of District 12 to reduce vulnerability during crises. The findings of this study are consistent with previous research by Pashapur and Pourakrami (2017), Bagherimaragheh et al. (2020), and Salehipour et al. (2021).
Based on the analysis and the identified indicators of physical and economic resilience in District 12, the following practical recommendations are proposed:
- Maintain adequate buffer zones around high-risk land uses such as gas and fuel stations.
- Ensure proper distribution of critical infrastructure throughout the district.
- Comply with building codes and update standards regularly.
- Maintain sufficient street widths, particularly in deteriorated urban areas.
Conclusion
Based on the present study, District 12, as the area under investigation, exhibits physical and economic resilience below the optimal level. The extent to which each district meets the key resilience criteria is neither uniform nor consistent, and there are significant differences in resilience indicators among the neighborhoods of District 12, Tehran. These disparities should be prioritized by urban managers to enhance overall resilience in the district.
Acknowledgments: The authors sincerely thank all the esteemed professors and officials at Islamic Azad University, Noor Branch, who supported this study.
Ethical Permission: No ethical issues were reported by the authors.
Conflict of Interest: This article has no conflicts of interest with any organizations or individuals.
Author Contributions: Mohagheghi P(first author), Introduction Writer/Discussion Writer/Methodologist/Main Researcher (50%); Ghadami M (second author), Introduction Writer/Discussion Writer (25%); Azimi Amoli J (third author), Statistical Analyst (15%); Janbaz Ghobadi Gh (fourth author); Methodologist (10%)
Funding: This article is derived from the PhD dissertation of Parisa Mohagheghi, and all expenses were covered by the student.
References
1. Amanpoor S, Hosseini Amini H, Ebadi H (2018). Explaining strategic crisis management with urban resilience approach case study: The worn-out texture of Ahvaz city. Journal of Geography and Environmental Hazards. 8(2):183-209. [Persian] [Link]
2. Asadzadeh A, Kötter T, Zebardast E (2015). An augmented approach for measurement of disaster resilience using connective factor analysis and analytic network process (F'ANP) model. International Journal of Disaster Risk Reduction. 14(4):504-518. [Persian] [Link] [DOI:10.1016/j.ijdrr.2015.10.002]
3. Bahraini SH, Masaeli S (1996). Land use planning in earthquake affected areas, sample of manjil, Rudbar and Lushan cities of Iran. 2nd Edition. Tehran: Iranian Center for Natural Disaster Study. [Persian]. [Link]
4. Bagheri Maragheh N, Motamedi M, Mafi E (2022). Evaluation of resilience of Shirvan city in the face of earthquake. Scientific Journals Management System. 22(64):329-347. [Persian] [Link] [DOI:10.52547/jgs.22.64.329]
5. Bastami Nia A, Rezaei MR, Fakhraeipour O (2015). A study of dimensions, approaches and concepts of resilience in urban communities with emphasis on natural disasters. International Conference on Research in Science and Technology, Organizations and Non-governmental Centers. Yazd: Yazd University. [Persian] [Link]
6. Burton CG (2012). The Development of Metrics for Community Resilience to Natural Disasters [dissertation]. South Carolina: University of South Carolina. [Link]
7. Cutter SL, Burton CG, Emrich CT (2010). Disaster resilience indicators for benchmarking baseline conditions. Journal of Homeland Security and Emergency Management. 7(1):1-22. [Link] [DOI:10.2202/1547-7355.1732]
8. Bavand Inc, (2006). Development model and detailed plan of Tehran Region 12. Tehran: Bavand Consulting Engineers. [Persian] Available From: https://shop.kargosha.com/ [Link]
9. Ebrahimzadeh E, Kashefi Doost D, Hosseini SA (2018). Evaluation of physical resilience of city against earthquake (Case study: Piranshahr city). Journal of Natural Environment Hazards. 8(20):131-146. [Persian] [Link]
10. Habibi K, Pourahmad A, Meshkini A (2013). Improvement and renovation of ancient urban textures. Tehran: Entekhab; 334-339. [Persian] [Link]
11. Habibi K, Pourahmad A, Meshkini A, Askari A, Nazari Adli S (2008). Allocation of building & structure factor effective in old fabrics vulnerability with fuzzy logic & gis (Case study: Zanjan city). Honar-Ha-Ye-Ziba. 33:27-36. [Persian] [Link]
12. Jazayeri E, Samadzadeh R, Hatami Nejad H (2018). Assessing the urban resilience against the seismic risks with emphasis on economic, physical, and infrastructural dimensions (a case study of the dist. 12 of Tehran). Environmental Based Territorial Planning (Amayesh). 12(45):183-198. [Persian] [Link]
13. Karami J, Mohammadi A, Sharifi Kia M (2016). Urban spatial resilience zonation after earthquake in part of Tehran metropolis (District 12), using owa algorithm. Journal of Spatial Analysis Environmental Hazarts. 3(2):23-34. [Persian] [Link] [DOI:10.18869/acadpub.jsaeh.3.2.23]
14. Kusumastuti RD, Husodo ZA, Suardi L, Danarsari DN (2014). Developing a resilience index towards natural disasters in Indonesia. International Journal of Disaster Risk Reduction. 10:327-340. [Link] [DOI:10.1016/j.ijdrr.2014.10.007]
15. Mavedat E, Garmsiri P, Momeni K (2019). Estimated distribution of urban resilience from the perspective of the earthquake crisis using the spatial stats model (case study of Ilam). Journal of Regional Planning. 9(36):119-134. [Persian] [Link]
16. Norozi A, Mahdavi S, Hajiloui M (2017). Evaluation of Effective Social Components in Resilience of District 12 of Tehran. Geographical Research. 32(4):86-104. [Persian] [Link] [DOI:10.29252/geores.32.4.86]
17. Nasiri Hendkhaleh E (2019). Ranking of the spatial resilience of Karaj metropolitan areas using the Electre model.Journal of Studies of Human Settlements Planning. 14(3):641-660. [Persian] [Link]
18. Normandin JM, Therrien MC, Tanguay GA (2009). City strength in times of turbulence: Strategic resilience indicators. Madrid, In Proc. of the Joint Conference on City Futures. 4-6. [Link]
19. Pashapur H, Pourakarami M (2017). Assessment of the physical dimensions of urban resilience against natural hazards (earthquake) (Case study of district 12 of Tehran). Journal of Studies of Human Planning. 12(4):985-1002. [Persian] [Link]
20. Rezaei MR (2011). Explaining the resilience of urban communities to reduce the effects of natural disasters (earthquake) Case study of Tehran metropolis [Dissertation]. Tehran: Tarbiat Modares University. [Persian] [Link]
21. Rezaei MR, Rafieian M, Hosseini SM (2016). Measurement and evaluation of physical resilience of urban communities against earthquake (Case study: Tehran neighborhoods). Human Geography Research Quaterly. 47(4):609-623. [Persian] [Link]
22. Rusta M, Ebrahimzadeh E, Eastgoldi M (2018). The analysis of physical resilience against earthquake in old texture of city Zahedan boarder city. Journal of Geography and Development. 15(46):1-18. [Persian] [Link]
23. Statistics Center of Iran (2017). Population and housing census. results of the general census of population and housing. Tehran: Statistics Center of Iran. [Persian] Available From: https://www.semanticscholar.org/paper/1-CITY-STRENGTH-IN-TIMES-OF-TURBULANCE-%3A-STRATEGIC-Normandin-Therrien/bc1279bfcff7f084652b99614debf2c929643432 [Link]
24. Salehipour Milani A, Zamani M, Sadough SH (2021). Earthquake vulnerability and resilience assessment of Razan city. Environmental Hazards Management. 8(3):267-282. [Persian] [Link]
25. Salehi E, Aghababaei MT, Sarmadi H, Farzad Behtash MR (2012). Considering the environment resiliency by use of cause model, Journal of Environmental Studies. 37(59):99-112. [Persian] [Link]
26. Shamaei A, Sasanpour F, AliHosseini R (2019). The spatial analysis of resilience of old neighborhoods located in the central area of Tabriz city. Geographical Urban Planning Research. 7(2):349-374. [Persian] [Link]
27. Sharifnia F (2013). Investigating the Relationship between Urban Land Use and Earthquake Resilience and Providing Solutions in the Field of Urban Planning (Case Study: District 10 of Tehran) [dissertation]. Tehran: University of Tehran. [Persian] [Link]
28. Suárez M, Gómez-Baggethun E, Benayas J, Tilbury D (2016). Towards an urban resilience index: A case study in 50 Spanish cities. Sustainability. Urban Resilience and Urban Sustainability. 8(8):774. [Link] [DOI:10.3390/su8080774]
29. Verrucci E, Rossetto T, Twigg J, Adams BJ (2012). Multi-disciplinary indicators for evaluating the seismic resilience of urban areas. In Proceedings of 15th world Conference Earthquake Engineering, Lisbon 24. Kalyanpur: Indian Institute of Technology Kanpur. [Link]
30. ZandMoghaddam MR, Mullaie A (2021). Assessing the role of municipal incentive policies on the renovation of worn-out structures (Case study: Istrict 14 of Tehran). Geography and Human Relationships. 3(3):254-272. [Persian] [Link]
31. Zarghami S, Teymouri A, Mohammadian H, Shamaei A (2016). Measuring and evaluating urban neighborhood's resilience against earthquake: The case of Zanjan downtown. Research and Urban Planning. 7(27):77-92. [Persian] [Link]
32. Ziari K, Darabkhani R (2011). An investigation about urban textures vulnerability against earthquake (Case study: Reagion 11 municipality of Tehran). Geographical Research. 25(4):25-48. [Persian] [Link]