تحلیل فضایی زمانی سوانح آتش‌سوزی در سطح شهر اردبیل در دوره زمانی سال‌های 1394-1398

نوع مقاله : پژوهشی - کاربردی

نویسندگان

1 گروه جغرافیا و برنامه‌ریزی شهری، دانشکده برنامه‌ریزی محیطی، دانشگاه تبریز، تبریز

2 گروه جغرافیا و برنامه‌ریزی شهری، دانشکده علوم اجتماعی، دانشگاه محقق اردبیلی، اردبیل

10.22059/jurbangeo.2023.348371.1732

چکیده

رویکرد پژوهش تحلیل فضا زمانی، حوادث آتشسوزی اتفاق افتاده در شهر اردبیل را طی دوره پنج‌ساله 1394-1398 موردمطالعه قرار داده است. برای کاهش خطرات و آسیبهای ناشی از آتش‌سوزی برای شهروندان، اتخاذ اقدامات پیشگیرانه و اختصاص بهینه منابع، تحلیلهای فضا زمانی این پدیده، ضروری است. تعداد 2894 مورد حادثه آتشسوزی، ازنظر زمانی، فضایی، نقشهبرداری و تحلیل‌شده‌اند. از نمودارهای راداری در اکسل و فنون تحلیل فضا- زمانی در محیط سامانه اطلاعات جغرافیای (GIS) برای انجام تحلیلهای موردنظر استفاده‌شده است. پارامترهای مهمی مانند تاریخ و زمان وقوع حوادث، تعداد فوت‌شدگان و مصدومان و آدرس محل وقوع حوادث، برای تحلیل استفاده‌شده است. مطالعه نشان میدهد که الگوهای فضایی-زمانی آتش‌سوزی بسته به زمان، انواع و علل آن‌ها متفاوت است. نتایج نشان می‌دهد که بیشتر آتش‌سوزی‌ها در واحدهای مسکونی با (888 مورد) و فضاهای باز و سبز (565 مورد) اتفاق افتاده است که بیشترین عامل وقوع آن‌ها آتش زدن عمدی و وندالیسم با 47/44 درصد می‌باشد. اوج آتش‌سوزی درست بعدازظهر، ساعت 13:00 و روزهای سه‌شنبه، پنج‌شنبه و جمعه و در هفته چهارم هرماه بالاترین فراوانی آتش‌سوزی رادارند طبق این مطالعه، تابستان دارای بیشترین تعداد حوادث آتش‌سوزی است. الگوی پراکنش فضایی، از نوع خوشه‌ای بوده و شدت تراکم حوادث آتش‌سوزی در بخش‌های مرکزی و لکه‌هایی از حاشیه شهر بیشتر است همچنین نتایج تحلیل خوشه‌ها نشان می‌دهد به‌طور قابل‌توجهی در محدوده موردمطالعه حوادث آتش‌سوزی با ارزش زیاد (54/194) و یا ارزش کم (0/0) به‌صورت خوشه‌های داغ و یا سرد تجمع یافته است در پایان‌بر مبنای یافته‌های پژوهش، پیشنهادهایی برای بهبود مدیریت و پیشگیری از حوادث آتش‌سوزی ارائه‌شده‌اند.

کلیدواژه‌ها


عنوان مقاله [English]

Spatio-temporal analysis of fire accidents in Ardabil in 2015-2019

نویسندگان [English]

  • Hassan Mahmoudzadeh 1
  • sepideh noori 2
  • Alireza Mohammadi 2
1 Department of Geography and Urban Planning, Faculty of Environmental Planning, University of Tabriz, Tabriz, Iran
2 Department of Geography and Urban Planning, Faculty of Social Sciences,Mohaghegh Ardabili University, Ardabil, Iran
چکیده [English]

A B S T R A C T
The article has studied the fire incidents that happened in Ardabil city during the five-year period of 1394-1398 with the approach of time-space analysis. In order to reduce the risks and damages caused by fire for citizens, it is necessary to adopt preventive measures and optimal allocation of resources, space-time analyzes of this phenomenon. The number of 2894 fire incidents have been mapped and analyzed in terms of time, space. Radar charts in Excel and spatio-temporal analysis techniques in the geographic information system (GIS) environment have been used to perform the desired analysis. Important parameters such as the date and time of the accidents, the number of dead and injured, and the address of the place of the accidents, have been used for analysis.The study shows that the Spatio-temporal patterns of fires vary depending on the time, types and causes. The results show that most fires occur in residential units and open and green spaces, the most common causes of which are intentional arson and vandalism. The peak of fires is right in the afternoon, at 13:00, and on Tuesdays, Thursdays and Fridays, and in the fourth week of each month, they have the highest frequency of fires. According to this study, summer has the highest number of fires. The pattern of spatial distribution is cluster type and the intensity of fire incidents is higher in the central parts of the suburbs. In addition, the results of cluster analysis show that in the study area, fire incidents with large amounts or it is rarely accumulated in the form of hot or cold clusters. Finally, based on the research findings, suggestions for improving the management and prevention of fire accidents are presented.
Extended Abstract
Introduction
In order to face the problems, threats and damages caused by urban structural fire incidents, it is necessary to investigate, recognize, analyze and interpret the reasons and their temporal and spatial dynamics. Analyzing the space-time patterns of fire incidents is one of the important steps in the prevention and reduction of damages and crisis management. This recognition requires the use of appropriate tools such as GIS and space-time analyzes in GIS, which help decision makers to improve their resource allocation by recognizing critical areas and distribution patterns of fire incidents, and make appropriate decisions for incident management and crisis management. This research has been conducted with the aim of analyzing spatio-temporal fire patterns by considering the types, location, time and causes using the city of Ardabil as a case study. Therefore, conducting this research can be used to prevent damages and risks caused by fire. The main goal of this research is the spatial and temporal analysis of fire incidents in Ardabil city. We have tried to find answers to these questions: 1- What are the main causes of fire incidents? What is the hourly, daily and monthly pattern of fire incidents distribution? Which areas of the city have the highest spatial density of fire incidents? Which areas of the city have a critical situation in terms of accidents? What is the spatial distribution of fire incidents (regular, scattered, clustered)?
 
Methodology
The data used in this research includes 2,894 incidents that were collected from April 1, 2014 to April 29, 2018 by the fire department and security services of Ardabil municipality. The data were recorded traditionally and manually, and therefore, in the first step, these data were entered into the EXCEL software. Important parameters such as the date and time of the accidents, the number of dead and injured and the address of the place of the accidents have been used for analysis. Therefore, three categories of related techniques have been used for space-time analysis. The first category is the radar charts for the temporal analysis of fires. The second category is the multi-distance spatial cluster analysis technique to determine the spatial distribution pattern. From the third category, the kernel density estimation technique is selected to determine and identify the critical zones, and the hot spot technique is chosen to analyze clusters and non-clusters as well. It has been used to help identify neighborhoods and areas with the highest concentration or the lowest concentration of incidents.
 
Results and discussion
The study shows that the spatio-temporal patterns of fire are different depending on the time, their types and causes. The results show that most of the fires happened in residential units (888 cases) and open and green spaces (565 cases), the most common cause of which is deliberate arson and vandalism with 44.47%. According to this study, summer has the highest number of fire incidents. The pattern of spatial distribution is of cluster type and the density of fire incidents is higher in the central parts and spots of the outskirts of the city. In addition, the results of the cluster analysis show that fire incidents with high value (194.54) or low value (0.0) are significantly accumulated in the studied area in the form of hot or cold clusters.
 
Conclusion
The analysis of the intensity of the spatial density of fires using the Kernel method showed that the intensity of the spatial density of fires is completely different and dynamic based on the cause of the fires. For example, while accidents caused by deliberate and vandalistic actions are scattered throughout the city, accidents caused by children's play are more concentrated in the central part of the city. In addition, the results of the hot spot method showed that the spatial distribution pattern of fires in Ardabil city is of high cluster type. That each group of fires formed a spatial clustering according to the type and cause of the fires. The concentration intensity of this clustering is high in some areas and low in others. The most important clusters have been formed in the central, northern and southern areas of the city.
 
Funding
There is no funding support.
 
Authors’ Contribution
All of the authors approved thecontent of the manuscript and agreed on all aspects of the work.
 
Conflict of Interest
Authors declared no conflict of interest.
 
Acknowledgments
We are grateful to all the scientific consultants of this paper.

کلیدواژه‌ها [English]

  • Spatial Analysis
  • Fire
  • Ardabil
  • GIS
  1. بیلانی، یداله؛ حکیم دوست، سیدیاسر؛ علیجانی، بهلول. (1393). اصول و مبانی پردازش داده‌های مکانی (فضایی) با استفاده از روش‌های تحلیل فضایی. چاپ اول، تهران: آزاد پیما.
  2. تقوایی، مسعود و کریمی، هادی. (1390). نقش آموزش و مشارکت شهروندان در کنترل حریق‌های شهری به‌منظور برنامه‌ریزی و مدیریت بحران شهری. فضای جغرافیایی، 11(36)، 25-46.
  3. سازمان آتش‌نشانی و خدمات ایمنی شهرداری اردبیل (1400).
  4. عسگری، علی. (1390). تحلیل‌های آمار فضایی با آرک جی‌ای اس. چاپ اول، تهران: انتشارات سازمان فناوری اطلاعات و ارتباطات شهرداری.
  5. مجتهدزاده، غلامحسین و روستا، مجید. (1399). مدیریت ایمنی محیط شهری. کتاب سبز 1400 سازمان شهرداری و دهیاری کشور.
  6. مرکز آمار ایران. (1395). سرشماری عمومی نفوس و مسکن، نتایج تفصیلی سرشماری استان اردبیل، مطالعات جمعیتی به تفکیک شهرستان، شهرستان اردبیل، شهر اردبیل.
  7. منصوری، نبی‌اله؛ نظری، رحیم؛ نصیری، پروین و قراگوزلو، علیرضا. (1390). تدوین برنامه مدیریت بحران آتش‌سوزی جنگل با تکنولوژی GIS & RS. کاربرد سنجش‌ازدور و سیستم اطلاعات جغرافیایی در برنامه‌ریزی، 2(3)، 63-73.
  8. وی. کی. جین. (1400). سازمان‌های آتش‌نشانی و آتش‌سوزی. صنعت حفاظت، 11(82)، 1-45
  9. Agbola, S. B., & Falola, O. J. (2021). Seasonal and locational variations in fire disasters in Ibadan, Nigeria. International Journal of Disaster Risk Reduction, 54, 102035.
  10. Ardebil Municipality Fire and Safety Services (2022). [In Persian].
  11. Asgari, A. (2011). Spatial Statistics Analysis with Arc GIS. First Edition, Tehran: Municipal Information and Communication Technology Publications. [In Persian].
  12. Balahadia, F. F., & Trillanes, A. O. (2017, July). Improving fire services using Spatio-temporal analysis: Fire incidents in manila. In 2017 IEEE Region 10 Symposium (TENSYMP) (pp. 1-5). IEEE.
  13. Beal-Neves, M., Vogel Ely, C., Westerhofer Esteves, M., Blochtein, B., Lahm, R.A., Quadros, E.L. & Abreu Ferreira, P.M. (2020). The influence of urbanization and fire disturbance on plant-floral visitor mutualistic networks. Diversity, 12(4), 1-41.
  14. Bilany, Y., Hakimdost, S.Y., & Alijani, B. (2014). Principles and Principles of Spatial Data Processing Using Spatial Analysis Methods. First Edition, Tehran: Azad Pima. [In Persian].
  15. Bulai, A.-T., Roşu, L., & Bănică, A. (2019). Patterns of urban fire occurrence in Iasi City (Romania). Present Environment and Sustainable Development (2), 87-102.
  16. Ceyhan, E., Ertuğay, K., & Düzgün, Ş. (2013). Exploratory and inferential methods for Spatio-temporal analysis of residential fire clustering in urban areas. Fire safety journal, 58, 226-239.
  17. Cheng, L., Li, S., Ma, L., Li, M., & Ma, X. (2015). Fire spread simulation-using GIS: Aiming at urban natural gas pipeline. Safety science, 75, 23-3
  18. Chhetri, P., Corcoran, J., Ahmad, S., & Kiran, K. C. (2018). Examining Spatio-temporal patterns, drivers and trends of residential fires in South East Queensland, Australia. Disaster Prevention and Management, 27 (5), 586-603
  19. Corcoran, J., Higgs, G., & Higginson, A. (2011). Fire incidence in metropolitan areas: A comparative study of Brisbane (Australia) and Cardiff (United Kingdom). Applied Geography, 31(1), 65-75.
  20. Diaz, L. B., He, X., Hu, Z., Restuccia, F., Marinescu, M., Barreras, J. V., & Rein, G. (2020). Meta-review of fire safety of lithium-ion batteries: Industry challenges and research contributions. Journal of  The Electrochemical Society, 167(9), 090559.‌
  21. ESRI (2021). Arc GIS 10.3 Tutorials
  22. Ferreira, T. M., Vicente, R., da Silva, J. A. R. M., Varum, H., Costa, A., & Maio, R. (2016). Urban fire risk: Evaluation and emergency planning. Journal of Cultural Heritage, 20, 739-745.
  23. Ghajari, Y. E., Alesheikh, A. A., Modiri, M., Hosnavi, R., & Abbasi, M. (2017). Spatial modelling of urban physical vulnerability to explosion hazards using GIS and fuzzy MCDA. Sustainability, 9(7), 1274.
  24. Guldåker, N., & Hallin, P. O. (2014). Spatio-temporal patterns of intentional fires, social stress and socio-economic determinants: A case study of Malmö, Sweden. Fire Safety Journal, 70, 71-80.
  25. Guldåker, N., Hallin, P. O., Klubien, M. T., & Nilsson, J. (2021). Residential Fires in Metropolitan Areas-Living Conditions and Fire Prevention.
  26. Iran Statistics Center. (2016). Population and Housing Census, Detailed Results of Ardebil Province Census, Democratic Studies by Ardebil City, Ardebil City. [In Persian].
  27. Kiran, K. C. (2015). Temporal and spatial patterns of fire incident response time: a case study of residential fires in Brisbane. 7th State of Australian Cities Conference, 9-11 December 2015, Gold Coast, Australia.
  28. Li, G., Kessler, J., Cheramy, J., Wu, T., Poopari, M. R., Bouř, P., & Xu, Y. (2019). Transfer and Amplification of Chirality Within the “Ring of Fire” Observed in Resonance Raman Optical Activity Experiments. Angewandte Chemie, 131(46), 16647-16650.
  29. Li, Y., & Rong, W. (2021, May). Analysis of Subway Fire Accident Based on Bayesian Network. In Journal of Physics: Conference Series,  1910(1), 012039, IOP Publishing.
  30. Maghsoodi Tilaki, M.J. & Hedayati, M. (2015). Exploring barriers to the implementation of city development strategies (CDS) in Iranian cities: A qualitative debate. Journal of Place Management and Development, 8(2), 123-141.
  31. Makui, A., Ashouri, F. & Barzinpour, F. (2019). Assignment of injuries and medical supplies in urban crisis management. Journal of Applied Research on Industrial Engineering, 6(3), 232-250
  32. Mansouri, Nabi., Nazari, R., Nasiri, P., Gharaguzloo, A. (2011). Developing a forest fire crisis management program with GIS & RS technology. Application of Geographic Information System and System in Planning, 2(3), 73-63. [In Persian].
  33. Mojtahedzadeh, Gh., & Rousta, M. (2021). Urban environment safety management. Green Book of 1400 Municipal and Dehydration Organization. [In Persian].
  34. Popelínský, J., Vachuda, J., & Veselý, O. (2017). Geographical modelling based on spatial differentiation of fire brigade actions: A case study of Brno, Czech Republic. Bulletin of Geography. Socio-economic Series, 35(35), 81-92.
  35. Rush, D., Bankoff, G., Cooper-Knock, S. J., Gibson, L., Hirst, L., Jordan, S., & Walls, R. S. (2020). Fire risk reduction on the margins of an urbanizing world. Disaster Prevention and Management: An International Journal, 35(53), 91-102
  36. Singh, P. P., Sabnani, C. S., & Kapse, V. S. (2021). Hotspot Analysis of Structure Fires in Urban Agglomeration: A Case of Nagpur City, India. Fire, 4(3), 1- 38.
  37. Song, C., Kwan, M. P., Song, W., & Zhu, J. (2017). A comparison between spatial econometric models and random forest for modeling fire occurrence. Sustainability, 9(5), 819.
  38. Taqami, M., Karimi, H. (2011). The Role of Citizens' Education and Participation in Urban Fire Controls for Planning and Management of Urban Crisis. Geographical Space, 11 (36), 25-46. [In Persian].
  39. Vallières, R. D. (2018). Pourquoi tant de malls à Téhéran?. Éléments d’économie politique des centres commerciaux en République islamique (1987-2017). EchoGéo, (45), 1-12.‌
  40. K. J. (2022). Fire and Fire Organizations. Protection Industry, 11 (82),1-45. [In Persian].
  41. Wang, Z., Zhu, G., Zhou, Y., Chu, T., Chai, G., & Tian, Z. (2020, April). Spatial and Temporal Analyses of Fire Incidents in San Francisco from 2010 to 2019. In 2020 IEEE 5th International Conference on Cloud Computing and Big Data Analytics (ICCCBDA) (537-541). IEEE.
  42. Wuschke, K., Clare, J., & Garis, L. (2013). Temporal and geographic clustering of residential structure fires: A theoretical platform for targeted fire prevention. Fire Safety Journal, 62, 3-12.
  43. www.esri.com.
  44. Yao, J., & Zhang, X. (2016). Spatial-temporal dynamics of urban fire incidents: a case study of Nanjing, China. ISPRS-International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 63-69.
  45. Zhang, X., Yao, J., Sila-Nowicka, K., & Jin, Y. (2020). Urban fire dynamics and its association with urban growth: Evidence from Nanjing, China. ISPRS International Journal of Geo-Information, 9(4), 218.