Identifying suitable areas for locating multi-purpose urban green spaces for temporary housing after the crisis: the case study of Rasht city

Document Type : Research Paper

Authors

Department of Urban Planning, Faculty of Architecture and Art, University of Guilan, Rasht, Iran

Abstract

ABSTRACT
Redefining the concept of urban green space not only as a place for recreation but also as a flexible and multi-purpose use in different conditions can be effective in the resilience of life and urban life after disasters. Therefore, one of the main goals in the construction of multi-purpose green spaces is to promote urban resilience and temporary accommodation. The aim of the current research is the optimal placement of multi-purpose green spaces with an emphasis on temporary accommodation in Rasht city. The method used in this research combines the best-worst approach (BWM) and fuzzy functions in GIS. By determining the final weight of effective criteria and sub-criteria in locating multi-purpose green spaces and comparing them using the best-worst method, the highest weight of sub-criteria was determined as "natural" and "compatible." The criteria of "incompatibility" and "efficiency" are "distance from the fault," "close to residential areas," "distance from high-risk facilities," and "population density," respectively. Then, the zoning of Rasht was done using the fuzzy method, and the optimal ranges were determined in five districts of Rasht. The results show that the most suitable place for the construction of multi-purpose green spaces and temporary accommodation is in Districts 3 and 1, with an area of 967.01 and 718.6 hectares, respectively, in the north and east of Rasht city. However, regarding the ratio of optimal levels to areas, District 2 has the highest ratio of 0.64.
Extended Abstract
Introduction
Redefining the concept of urban green space not only as a place for recreation but as a flexible and multi-purpose use in different conditions can be effective in the resilience of urban living and life after disasters. In this regard, the current research is an attempt to optimize urban green spaces in Rasht city, which, in addition to the social, welfare, and recreational functions, examines the hidden capacities of these spaces to reduce the risks caused by disasters. Spaces that, in addition to providing various types of services under normal conditions, can turn into places for citizens to settle in the shortest time after a crisis, and access to other services is also easier in these places than in other areas. Moreover, they have the highest safety conditions. Among these capacities is the establishment of temporary accommodation bases in multi-purpose green sites, and the optimization of suitable locations for these bases and their spatial analysis are on the agenda of the present research.
 
Methodology
The current research is applied based on the purpose and descriptive survey regarding the data collection method. The spatial territory of the research is Rasht. The number of 4 criteria and 26 sub-criteria effective in locating multi-purpose green spaces has been extracted through library studies and confirmation by experts. In the next stage, with experts' opinions, the weight of criteria and sub-criteria was determined using the "best-worst" multi-criteria decision-making method by distributing a multi-stage questionnaire among 15 experts and specialists. The inconsistency coefficient calculated for all 15 experts in all pairwise comparisons was less than 0.1, which shows the reliability of the questionnaire and compatibility. Next, in order to perform spatial analysis, the information layers of the indicators are digitized in GIS software, and by converting the information layers into a raster and standardizing them, the final composition of the layers is discussed. Then, the fuzzy areas were divided into five classes by reclassifying the final overlap map. After classifying the zones and optimal areas for the construction of multi-purpose green spaces in Rasht, the area of optimal zones was calculated separately to check the capacity and capabilities of each area of Rasht.
 
Results and discussion
The results of the implementation of the BWM model showed that at the level of comparison of criteria, the "efficiency" criterion with a weight of "0.3088" is the most important criterion among other criteria. After determining the layers' weights by multiplying the criteria' weights in the sub-criteria, their ranking was done separately for each dimension. Therefore, at the sub-criteria level, "population density" with a weight of "0.120" was identified as the most important sub-criteria in the efficiency dimension. In the dimension of incompatibility, "distance from high-risk facilities" with a final weight of "0.023" was determined as the most important sub-criterion. "Proximity to residential areas" with a final weight of "0.137" and "distance from the fault" with a final weight of "0.137" were also determined as the most important sub-criteria in the criteria of "compatible uses" and "natural features." After the weighted final layers were standardized and analyzed based on fuzzy functions, the final combination of weighted layers was attempted to reach the zoning map of the optimal locations of multi-purpose green spaces in Rasht. Then, by reclassifying the final overlap map of gamma 0.9, the specified areas were classified into five categories as very suitable, suitable, relatively suitable, unsuitable, and very unsuitable. Finally, this research identified two suitable and very suitable floors as optimal ranges for multi-purpose green spaces in five districts of Rasht. After classifying the zones and optimal areas, the area of the optimal zones was calculated separately to check the capacity and capabilities of each district of Rasht.
 
Conclusion
In this research, by emphasizing the capabilities of green spaces to improve the management of residential areas after the crisis, especially planning for temporary accommodation and creating secondary shelters for residents, the optimization of the location of multi-purpose urban green spaces in Rasht was done. For the final zoning of the optimal areas for the construction of multi-purpose green spaces and temporary accommodation, by extracting and scoring the essential sub-criteria in the form of four criteria as "efficiency," "closeness to compatible uses," "away from incompatible elements," and "natural features," using the integration of the new BWM multi-criteria decision making approach and fuzzy functions in the GIS environment, it was determined that the largest area of the optimal area with an area of 413.64 very suitable hectares and 553.86 suitable hectares is related to the District 3 of Rasht. Also, District 1, with 262.59 hectares of very suitable area and 455.98 hectares of suitable area, was ranked second among the five districts of Rasht. The lowest area of the optimal zones, with an area of "312.866" hectares, is related to District 5 of Rasht. After re-evaluating the optimal areas according to field observations and analysis of satellite images, it was determined that there are many empty and barren lands, proximity to residential, healthcare, and sports areas, distance from incompatible uses such as polluting industries, high-risk facilities, lines electricity and energy transmission, safety and efficiency levels such as proximity to roads and densely populated areas in Districts 1 and 3 are higher than other areas. In other words, it can be acknowledged that the criteria used in the research, the analysis done on them, and the research results are consistent with the real field of the studied area. Therefore, based on the findings of this research, Districts 1 and 3 of Rasht have the most significant ability to build urban multi-purpose green spaces and establish temporary accommodation sites.
 
Funding
There is no funding support.
 
Authors’ Contribution
Authors contributed equally to the conceptualization and writing of the article. All of the authors approved thecontent of the manuscript and agreed on all aspects of the work declaration of competing interest none.
 
Conflict of Interest
Authors declared no conflict of interest.
 
Acknowledgments
We are grateful to all the scientific consultants of this paper.

Keywords

Main Subjects

References

  1. Azarkish, M., Hafez Rezazadeh, M., & Miri,. Gh. (2017). Application of Analytic Hierarchy Process (AHP) and Geographic Information System (GIS) in locating temporary settlements after natural disasters (Case Study: Region Two of Zahedan Municipality). Journal of Geographical Space Research, 17(58), 169-189. [in Persian]
  2. Avand, M. T., Moradi, H. R., & Ramezanzadeh Lesboei, M. (2021). Assessing the vulnerability of Tajan watershed to flooding using the BWM method. Journal of Watershed Management Research, 13(26), 20-10. ‌ doi:10.52547/JWMR.13.26.10. [in Persian]
  3.  Bazi, K., Khosravi, S., & Hossein Nejad, M. (2012). Investigating the current situation and locating the required green space in Zabol city using GIS. Spatial Planning (Geography), 1(4), 74-39. https://dorl.net/dor/20.1001.1.22287485.1391.1.4.3.6. [in Persian]
  4. Hatami-Nejad, H., Waysian, M., Mohammadi Varzaneh, N., & Alizadeh, A. (2014). Analysis and prioritization of urban green space using TOPSIS and GIS techniques. Case study: Dehgolan city. Environmental Planning, 7(26), 65-88.. [in Persian]
  5. Khazaei, S., & Roustaei-Hosseinabadi, S. (2016). Locating multipurpose urban shelters using geographic information systems (case study: District 1 of Tehran Municipality). Journal of Passive Defense, 7(4), 12-1. [in Persian]
  6. Sabzi, M. (2017). Application of GIS based on ANP-FUZZY model in multi-purpose location of urban hazards with emphasis on temporary housing and green space (case study: north of Tabriz city). Master's thesis, University of Tabriz. [in Persian]
  7. Sartiak, Sh., Rahimi, A. M., Zaeemdar, M., Jozi, S. A., & Khalidi, H. R. (2023). Evaluation of urban transportation system in times of crisis using Transcode software, case study: Isfahan city. Journal of Human Geography Research, 55(3), 37-66. https://doi.org/10.22059/jhgr.2022.324644.1008311. [in Persian]
  8. Shojaian, A., & Alizadeh, H. (2014). Locating multipurpose spaces for the purpose of post-earthquake crisis management. Case study: the dilapidated fabric of Shushtar city. Geography and Regional Urban Planning, 4(11), 127-140. https://doi.org/10.22111/gaij.2014.1546. [in Persian]
  9. Shafizadeh, M., & Movahedikozani, H. (2019). Identifying safe places for emergency accommodation of Rasht city citizens during crises. Journal of New Research Approaches to Management and Accounting, 4(13), 116-134. [in Persian]
  10. Abedini, M., Piroozi, E., Amini, Z., & Parast, S. (2017). Optimal location of green space in Ardabil city using the Analytical Network Process (ANP) model and Geographic Information System. Journal of Urban Ecology Research, 12(23), 1-20. https://doi.org/10.30473/grup.2021.8615. [in Persian]
  11. Ghadermarzi, H., Kashfi Doost, Sh., Ghadermarzi, J., & Kashfi Doost, D. (2016). An analysis of the spatial distribution pattern of green space and optimal location of urban parks using the ANP model and network analysis. Case study: Piranshahr city. Journal of Geography and Development, 14(42), 145-160. https://doi.org/10.22111/gdij.2016.2348. [in Persian]
  12. Kazeminia, A. (2019). Location of emergency housing events in Kerman city using GIS, Management and Crisis Bi-Quarterly, 48(16), 47-59. Https://Dor.Isc.Ac/Dor/20.1001.1.23453915.1398.8.2.4.2. [in Persian]
  13. Roshani, M., & Pourramazan, I. (2016). Spatial analysis of natural hazards in rural settlements of Guilan province using GIS. First International Conference on Natural Hazards and Environmental Crises of Iran, Solutions and Challenges, Ardabil. [in Persian]
  14. Yaripour, M., & Hadizadeh Zargar, S. (2015). Study of effective quantitative and qualitative indicators in urban green space planning (case study: Mianeh city). Urban Economics and Management, 10, 37-57. http://dorl.net/dor/20.1001.1.23452870.1394.3.10.3.1. [in Persian]
  15. Yazdani, M. H., & Mohammadi Hamidi, S. (2017). Spatial analysis of multipurpose uses in the city with a passive defense approach, case study: religious use of the city of Miandoab. Geography and Urban Space Development, 4(2), 221-242. DOI: 10.22067/gusd.v4i2.63099. [in Persian]
  16. Ramazan Kiasaj Mahalle, R., Esmaeili Alavijeh, E., & Amiri, M. J. (2019). Locating urban green space using multi-criteria evaluation methods, case study: Tehran District 4. Journal of Urban Ecology Research, 11(2), 13-28. https://doi.org/10.30473/grup.2021.7618. [in Persian]
  17. Qaysari, Hadiseh, Ahadnejad, Mohsen and Ahar, Hassan. (2015). Locating safe multipurpose urban spaces in times of crisis using the weighted overlap index method. Quarterly Journal of Emdad and Nejat, 7(1), pp. 35-50. [in Persian]
  18. Nasiri Hinde Khaleh, I., Rostami, Sh., & Shirini, M. (2023). Locating the Central Crisis Management Support Base in Karaj Metropolitan Area. Journal of Human Geography Research, 55(3), 83-96. https://doi.org/10.22059/jhgr.2022.333053.1008403. [in Persian]
  19. Administration USGS. The National Response Framework [cited 2 May 2021]. Available from: https://www.gsa.gov/governmentwide-initiatives/emergency-response/the-national-response framework
  20. Allan, P., & Bryant, M. (2011). Resilience as a framework for urbanism and recovery. J Landsc Archit, 6(2), 34–45. https://doi.org/10.1080/18626033.2011.9723453.
  21. Allan, P., Bryant, M., Wirsching, C., Garcia, D., and Rodriguez, M. T. (2013). The Influence of Urban Morphology on the Resilience of Cities Following an Earthquake. Journal of Urban Design, 18, 242–262. https://doi.org/10.1080/13574809.2013.772881
  22. Bauwelinck, M., Casas, L., Nawrot, T. S., Nemery, B., Trabelsi, S., Thomas, I., Aerts, R., Lefebvre, W., Vanpoucke, C., Van Nieuwenhuyse, A., Deboosere, P., & Vandenheede, H., (2021). Residing in urban areas with higher green space is associated with lower mortality risk: A census-based cohort study with ten years of follow-up. Environment International., 148, 106365, https://doi.org/10.1016/j.envint.2020.106365
  23. Borland, J., (2019). Small parks, big designs: reconstructed Tokyo’s new green spaces, 1923–1931. Urban History, 47, 106–125. https://doi.org/10.1017/S0963926819000567
  24. Boulton, C., Dedekorkut-Howes, A., & Byrne, J. (2018). Factors shaping urban greenspace provision: A systematic review of the literature. Landscape Urban Plan., 178, 82–101, https://doi.org/10.1016/j.landurbplan.2018.05.029
  25. Colding, J., & Barthel, S. (2013). The potential of “Urban Green Commons” in the resilience building of cities, Ecol. Econ., 86, 156–166. https://doi.org/10.1016/j.ecolecon.2012.10.016.
  26. Galasso, C., McCloskey, J., Pelling, M., Hope, M., Bean, C. J., Cremen, G., Guragain, R., Hancilar, U., Menoscal, J., Mwang’a, K., Phillips, J., Rush, D., & Sinclair, H. (2021). Editorial. Risk-based, Pro-poor Urban Design and Planning for Tomorrow’s Cities, Int. J. Disast. Risk Re., 58, 102158. https://doi.org/10.1016/j.ijdrr.2021.102158.
  27. García-Lamarca, M., Connolly, J., & Anguelovski, I. (2020). Green gentrification and displacement in Barcelona, in: Housing Displacement, Routledge, 156–170
  28. Jeong, D., Kim, M., Song, K., & Lee, J. (2021). Planning a Green Infrastructure Network to Integrate Potential Evacuation Routes and the Urban Green Space in a Coastal City: The Case Study of Haeundae District, Busan, South Korea, Science of The Total Environment., 761, 143179. https://doi.org/10.1016/j.scitotenv.2020.143179
  29. Liu,, Xu, H., Wu, J., Li, W., & Hu, H. (2022). Measuring spatial accessibility to refuge green space after earthquakes: A case study of Nanjing, China. PLOS ONE https://doi.org/10.1371/journal.pone.0270035
  30. Marselle, M. R., Bowler, D. E., Watzema, J., Eichenberg, D., Kirsten, T., & Bonn, A. (2020). Urban street tree biodiversity and antidepressant prescriptions. Scientific Reports, 10, 22445, https://doi.org/10.1038/s41598-020-79924-5.
  31. Masuda,. (2014). Disaster refuge and relief urban park system in Japan. Landsc Archit Front, 2(4), 52–61.
  32. McDonald, R. I., Mansur, A. V., Ascensão, F., Colbert, M. L., Crossman, K., Elmqvist, T., Gonzalez, A., Güneralp, B., Haase, D., Hamann, M., Hillel, O., Huang, K., Kahnt, B., Maddox, D., Pacheco, A., Pereira, H. M., Seto, K. C., Simkin, R., Walsh, B., Werner, A. S., & Ziter, C. (2020). Research gaps in knowledge of the impact of urban growth on biodiversity. Nature Sustainability, 3, 16–24. https://doi.org/10.1038/s41893-019-0436-6.
  33. Muhammad, A., De Risi, R., De Luca, F., Mori, N., Yasuda, T., & Goda, K. (2021). “Are current tsunami evacuation approaches safe enough? Stochastic Environmental Research and Risk Assessment, 35, 759-779. https://link.springer.com/article/10.1007/s00477-021-02000-5
  34. - Ramazani, R., Ostadtaghizadeh, A., Yari, A., Hanafi-Bojd, A. A., Soltani, A., Rostami, S. B., and Heydari, A. (2022). Criteria for Locating Temporary Shelters for Refugees of Conflicts: A Systematic Review. Iranian Journal of Public Health, 51(4), 758-769.
  35. - Razzaghian, F., & Aghajani, H. (2016). Evaluating and Land-use locating of City Parks Using Network Analysis (Case Study: Mashhad Metropolis, Iran). International Technology, 6 (4): 18-24.
  36. Rezaie, J. (2015). Best- Worst Multi- Criteria Decision- Making Method, Omega, (53): 49-57
  37. Shi, W., & Woolley, H. (2014). Managing for multifunctionality in urban open spaces: Approaches for sustainable development. Journal of Urban Management, 3(1-2), 3-21.
  38. Shimpo, N., Wesener, A., & McWilliam, W. (2019). How community gardens may contribute to community resilience following an earthquake. Urban Forestry & Urban Greening, 38, 124–132. https://doi.org/10.1016/j.ufug.2018.12.002
  39. Tan, Z., Lau, K., & Ng, E. (2016). Urban tree design approaches for mitigating daytime urban heat island effects in a high-density urban environment. Energy and Buildings, 114: 265–274.
  40. Watson, C. S., Elliott, J. R., Ebmeier, S. K., Vásquez, M. A., Zapata, C., Bonilla-Bedoya, S., ... & Sevilla, E. (2022). Enhancing disaster risk resilience using greenspace in urbanising Quito, Ecuador. Natural Hazards and Earth System Sciences, 22(5), 1699-1721.
  41. Shi, W., & Woolley, H. (2014). Managing for multifunctionality in urban open spaces: Approaches for sustainable development. Journal of Urban Management, 3(1-2), 3-21.‌
  42. Uk COo. Evacuation and shelter guidance [cited 2 May 2021]. Available from: https://www.gov.uk/government/publications/evacuation-and-shelter-guidance.
  43. Wei,., Jin, L., Xu, M., Pan, S., Xu, Y., & Zhang, Y. (2020). Instructions for planning emergency shelters and open spaces in China: Lessons from global experiences and expertise. Int J Disaster Risk Reduct. DOI: 10.1016/j.ijdrr.2020.101813
  44. Yao,., Zhang Y, Yao T, Wong K, Tsou JY, Zhang Y. (2021). A GIS-based system for spatial-temporal availability evaluation of the open spaces used as emergency shelters: The case of Victoria, British Columbia, Canada. ISPRS Int Geo-Inf, 10(2), 63. https://doi.org/10.3390/ijgi10020063.
Human Geography Research
Volume 56, Issue 4
December 2024
Pages 247-265

Files

Share

How to cite

Statistics