الگوی فضایی میزان تاب‌آوری کالبدی سکونتگاه‌های روستایی شهرستان املش در برابر زمین‌لغزش

نوع مقاله : مقاله برگرفته از پایان نامه

نویسندگان

1 دانشجوی دکتری، گروه جغرافیا، دانشکده علوم انسانی، واحد رشت، دانشگاه آزاد اسلامی، رشت، ایران.

2 استادیار، گروه جغرافیا، دانشکده علوم انسانی، واحد رشت، دانشگاه آزاد اسلامی، رشت، ایران.

3 استاد، گروه جغرافیا، دانشکده علوم انسانی، واحد رشت، دانشگاه آزاد اسلامی، رشت، ایران.

چکیده

در این پژوهش میزان تاب‌آوری کالبدی سکونتگاه‌های روستایی شهرستان املش در برابر زمین‌لغزش به سه روش تحلیل سلسله‌مراتبی، جمع وزنی و شاخص هم‌پوشانی بررسی شد و سپس با استفاده از شاخص‌های آمار مکانی، الگوی فضایی میزان تاب‌آوری روستاها تعیین گردید. بدین منظور از 10 معیار شیب، فاصله از گسل، کیفیت ابنیه، مواد و مصالح، عمر ساختمان، لرزه‌خیزی، زمین‌شناسی، جهت شیب، عرض معابر و ارتفاع به ترتیب اهمیت استفاده شد. همچنین از دو روش آماره I موران محلی و تحلیل نقاط داغ (G* گتیس-اورد) برای شناسایی الگوها استفاده شد. نتایج نشان داد که میزان تاب‌آوری کالبدی سکونتگاه‌های روستایی در مقابل زمین‌لغزش بین تاب‌آوری خیلی کم تا خیلی زیاد متغیر بوده و روستاهای با تاب‌آوری خیلی بالا در محدوده شمال شرقی و روستاهای با تاب‌آوری خیلی پایین در محدوده شمال غربی و در بخش جلگه‌ای و کوهپایه‌ای شهرستان املش قرار دارند. در ناحیه کوهستانی شهرستان نیز روستاهای با تاب‌آوری کم و متوسط در هر سه مدل موردبررسی قابل‌مشاهده بودند. در این راستا نتایج آماره I موران محلی بیانگر وجود خوشه بالا - بالا (HH) و پایین - پایین (LL) در شمال شرقی و شمال غربی ناحیه موردمطالعه است که این الگوها در روستاهای ناحیه جلگه‌ای و کوهپایه‌ای نیز پدیدار شده‌اند. همچنین وجود نقاط داغ گرم و سرد در شمال شرق و شمال غرب شهرستان به اثبات رسیده و با 3 انحراف معیار مثبت و منفی در سطح اطمینان 99 درصد در ناحیه جلگه‌ای و کوهپایه‌ای نمایان شده‌اند. اکثر روستاهای شهرستان دارای تاب‌آوری متوسط نسبت به پدیده زمین‌لغزش بوده و رفتار تصادفی آن‌ها توسط دو آماره I موران محلی و تحلیل نقاط داغ مورد تأیید قرار گرفت. درمجموع نقاط روستاهای با تاب‌آوری بالا و پایین با الگوی خوشه‌ای بالا - بالا و پایین - پایین I موران محلی و نقاط داغ و سرد G* گتیس-اورد در هر سه مدل تحلیل سلسله‌مراتبی، جمع وزنی و شاخص هم‌پوشانی منطبق بودند.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Spatial Pattern of Physical Resilience of Rural Settlements in Amlash County Against Landslides

نویسندگان [English]

  • Khalil Mehrzad 1
  • Eisa Pourramzan 2
  • Nasrollah MolaeiHashjin 3
1 PhD Candidate, Department of Geography, Faculty of Humanities, Rasht Branch, Islamic Azad University, Rasht, Iran.
2 Assistant Professor, Department of Geography, Faculty of Humanities, Rasht Branch, Islamic Azad University, Rasht, Iran.
3 Professor, Department of Geography, Faculty of Humanities, Rasht Branch, Islamic Azad University, Rasht, Iran.
چکیده [English]

In this research, the physical resilience of the rural settlements of Amlash County against landslides was investigated using hierarchical analysis, weighted summation, and overlap index. Then, the spatial pattern of the resilience of the villages was determined using spatial statistics indicators. For this purpose, ten criteria of slope, distance from fault, building quality, materials and materials, building life, seismicity, geology, the direction of slope, width of passages, and height were used in order of importance. Also, two methods of local Moran's I statistic and hot spot analysis (G* Gettys-Ord) were used to identify patterns. The results showed that the physical resilience of rural settlements against landslides varies from very low to very high. Villages with very high resilience are in the northeastern region, and towns with very low resilience are in the northwestern region and the plains. They are located in the foothills of Amlash County. In the mountainous area of the County, villages with low and medium resilience were also visible in all three investigated models. In this regard, the results of the local population statistics show the presence of high-high (HH) and low-low (LL) clusters in the northeast and northwest of the studied area, and these patterns have also appeared in the villages of the plains and foothills. Also, the existence of hot and cold hot spots in the northeast and northwest of the County has been proven, and with three positive and negative standard deviations at the 99% confidence level, they have been shown in the plains and foothills. Most of the counties' villages have moderate resilience to landslides, and their random behavior was confirmed by local Moran's I statistics and hot spot analysis. In total, the points of villages with high and low resilience with high-high and low-low cluster patterns of local Moran's I and hot and cold spots of G* Gettys-Ord in all three models of hierarchical analysis, weighted summation, and matching overlap index were. 

کلیدواژه‌ها [English]

  • Physical resilience
  • Criteria
  • Hierarchical analysis model
  • Spatial pattern
  • Amlash County
Alijani, B. (2018). Quantitative methodology in geography. Tehran: Samt Publications. (In Persian)
Anabestani, A., Javanshiri, M., Mahmoudi, H., Darban Astaneh, M. (2016). Spatial Analysis of Villagers’ Resilience Against Environmental Hazards (A Case Study of Central District of  Faruj County). Journal of Spatial Analy-sis Environmental Hazards, 5(1), 17-38.  (In Persian) doi:10.29252/jsaeh.5.1.17.
Asghari Saraskanrood, S., Emami, R., & Piroozi, E. (2021). Evaluation and zonation of Landslide hazard with using OWA and ANN methods (Case study: Paveh Township). Journal of Natural Environmental Hazards, 10(28), 131-150.  (In Persian) doi: 10.22111/jneh.2021.33729.1645.
Badri, S A., Karimzadeh, H., Saadi, S., Kazemi, N. (2019). Analysis of Rural Settlements Resilience against Earth-quake (Case Study: Marivan County). Journal of Spatial Analysis Environmental Hazards, 6(1),1-16. ‎(In Per-sian) doi:10.29 252/jsaeh.6.1.1.
Berry, R., Vigani, M., & Urquhart, J. (2022). Economic resilience of agriculture in England and Wales: a spatial analysis. Journal of Maps, 18(1), 70-78. doi.org/10.1080/17445647.2022.2072242.
Chirisa, I., & Nel, V. (2022). Resilience Thinking in the Rural Human Settlements’ Development and Management. International Journal of Rural Management, 18 (1), 146–160. doi:10.1177/0973005221100 1674.
Cutter, S.L., Barnes, L., Berry, M., Burton, C., Evans, E., Tate, E., & Webb, J. (2008). A place-based model for un-derstanding community resilience to natural disasters. Glob. Environ, 18, 598–606. doi.org/10.1016/j.gloenvcha.2008.07.013.
Eidsvig, U.M.K., McLean, A., Vangelsten, B.V., Kalsnes, B., Ciurean, R.L., Argyroudis, S., Winter, M.G., Mavrouli, O.C., Fotopoulou, S., Pitilakis, K., et al. (2014). Assessment of socioeconomic vulnerability to landslides using an indicator-based approach: Methodology and case studies. Bull. Eng. Geol. Environ. 73, 307–324. doi:10.1007/s10064-014-0571-2.
Entezari, M., & Kordavani, M. (2022). Landslide hazard zoning using GIS-based methods and radar data (Case study: Fereydoon Shahr). Journal of Natural Environmental Hazards, 11(33), 177-196. (In Persian) doi:10.22111/jneh.2022.38660.1810.
Fakhrghazi, M., Pourramzan, E., & Molaei Hashtjin, N. (2022). Spatial Analysis of Social Resilience of Rural Set-tlements against Earthquake Risk (Case study: villages of Avaj County). Geographical Engineering of Territory, 6(2), 309-325. (In Persian) dor: 20.1001.1.25381490.1401.6.11.1.8.
Farzad Behtash, M. R., Keynejhad, M. A., Taghi Pirbabaei, M., & Asgary, A. (2013). Evaluation and Analysis of Dimensions and Components of Tabriz Metropolis Resiliency. Journal of Fine Arts: Architecture & Urban Planning, 18(3), 33-42. (In Persian) doi: 10.22059/jfaup.2013.51316.
Frazier, T.G., Thompson, C.M., Dezzani, R.J., & Butsick, D. (2013). Spatial and temporal quantification of resilience at the community scale. Applied Geography, 42, 95–107. doi: 10.1016/j.apgeog.2013.05.004.
Frigerio, I., Ventura, S., Strigaro, D., Mattavelli, M., Amicis, M.D., Mugnano, S., Boffi, M. (2016). A GIS-based ap-proach to identify the spatial variability of social vulnerability to seismic hazard in Italy. Applied  Geography, 74, 12–22. doi: 10.1016/j.apgeog.2016.06.014.
Fotohi, S., Alinia, H., Firozi, F., Bakhshipoor, J., & Rakhshani, Z. (2013). The Positioning of Areas Susceptible of Landslide (A Case Study: The North of Neyshaboor). Journal of Natural Environmental Hazards, 2(3), 61-75. (In Persian) doi: 10.22111/jneh.2013.2462.
Ge, D., Zheng, Y., Zhang, Sh., Fu, J., & Su, F. (2022). Spatio-Temporal Pattern and Influence Mechanism of Rural Human Settlements System Resilience: Case from China. Sustainability, 14, 1-24. doi.org/10.3390/su142114533.
Heidarimozaffar, M., & TajBakhshian, M. (2022). Zoning the Vulnerability of Nahavand Settlements to Earth-quakes. Journal of Natural Environmental Hazards, 11(34), 57-78. (In Persian) doi: 10.22111/ jneh.2022.39334.1830.
Keikha, Z., Bazrafshan, J., Ghanbari, S., & Keikha, A. (2022). Spatial analysis of the extent to which the local com-munity has effective physical-environmental indicators resilience to environmental hazards (Case study: villag-es of Sistan region). Village and Space Sustainable Development, 3(3), 20-34. (In Persian) doi: 10.22077/vssd.2022.5054.1075.
Kor, A., Balali, H., Movahedi, R., & Sharifzadeh, M. (2023). Examining the Components and Indicators of Eco-nomic Resilience of Farmers Against Climate Disasters. Journal of Rural Research, 14(2), 200-217. doi: 10.22059/jrur.2023.92915.
Khosravi Mal Amiri, H., Soleimani, H., Ghaffari, S. R., & Khadem al-Hosseini, A. (2020). Explanation of resilience pattern of rural settlements in Izeh County (Dehdez district). Physical Social Planning, 7(1), 131-145. (In Per-sian) doi: 10.30473/psp.2020.6803.
Kwazu, G. C., & Chang Richards, A. (2022). A tool to assess livelihood preparedness for disasters: a study of Kaikoura earthquake in New Zealand. Natural Hazards, 113, 745–766. doi.org/10.1007/s11069-022-05322-x.
Li, Y., Song, C., & Huang, H. (2021). Rural Resilience in China and Key Restriction Factor Detection. Sustainabil-ity, 13(3), 1080. doi.org/10.3390/su13031080.
Liang, T.C., & Peng, S.H. (2017). Using Analytic Hierarchy Process to Examine the Success Factors of Autonomous Landscape Development in Rural Communities. Sustainability, 9(5), 729. doi: 10.3390/su9050729.
Mavhura, E., & Manyena, B. (2018). Spatial quantification of community resilience in contexts where quantitative data are scarce: The case of Muzarabani district in Zimbabwe. Geo: Geography and Environment, 5(2), 1-20. doi.org/10.1002/geo2.65.
Management and Planning Organization of Guilan Province. (2017). Statistical yearbook of Guilan province. Deputy of statistics and information. 
Mirsanjar, M. M. M., Ildoromi, A. I., Abedian, S. A., & Alimohamadi, A. A. (2018). Landslide hazard zonation using LNRF model (Case study: Ghomroud- Aligudarz basin). Journal of Natural Environmental Hazards, 7(18), 109-130. (In Persian)  doi: 10.22111/jneh.2018.20280.1253.
Nazari, A. H., Taleshi, M., Mirzaali, M. (2018). Analysis and Measurement of Environmental Resilience of Villages in Gorganrud Watershed against Flood (Golestan province, Iran). Journal of Spatial Analysis Environmental Hazards, 6(1), 31-50. ‎ (In Persian) doi: 10.29252/jsaeh.6.1.3.
Noori, S. H., & Sepahvand, F. (2016). Analysis of Rural Area Resilience against Earthquake; Case Study: Shirvan District (Boroujerd County). Journal of Rural Research, 7(2), 272-285. (In Persian) dor: 20.1001.1. 20087373.1395.7.2.1.4.
Noori, H., & Nowrozi Avargani, A. (2016). Basics of environmental planning for sustainable rural development. Isfahan: University of Isfahan Publications. (In Persian)
Rezaei, M R., & Kavianpour, G. (2015). Assessing the level of social and physical-environmental resilience of ur-ban neighborhoods in the face of natural disasters (earthquake), case study: Mashhad metropolis. The third national conference on crisis management and HSE in vital arteries, industries and urban management, Tehran. (In Persian)  https://civilica.com/doc/561760.
Roustaei, S., Hoseyni haghi, V., & Gedari, A. (2019). Assessing the physical resilience of urban environments against earthquakes (a case study of Tabriz metropolis). Social Research, 11(43), 121-141. (In Persian) https://jsr.riau.ac.ir/article_1582.html?lang=en.
Rudiarto, I., Handayani, W., Wijaya, H B., & Insani, T D. (2019). Rural Livelihood Resilience: An Assessment of Social, Economic, Environment, and Physical Dimensions. MATEC Web of Conferences 280. doi.org/10.1051/matecconf /201928001002.
Salehi, E., Aghababaei, M. T., Sarmadi, H., & Farzad Behtash, M. R. (2011). Considering the Environment Resilien-cy by Use of Cause Model. Journal of Environmental Studies, 37(59), 99-112. (In Persian) https://jes.ut.ac.ir/?_action=article&au.
Su, Q., Chang, H-Sh., & Pai, Sh-E. (2022). A Comparative Study of the Resilience of Urban and Rural Areas under Climate Change. International Journal of Environmental Research and Public Health, 19, 8911, doi.org/10.3390/ ijerph19158911.
Sung, C H., & Liaw, S.C. (2021). Using Spatial Pattern Analysis to Explore the Relationship between Vulnerability and Resilience to Natural Hazards. International Journal of Environmental Research and Public Health, 18, 5634. https://doi.org/10.3390/ijerph18115634.
Tayebnia, S. H., & Ebrahimipour, F. (2021). Measurement of resilience coefficient of rural areas against earth-quakes using multivariate model (FAHP) and (GIS) (Case study: Dolat Abad County, Jiroft Township). Village and Space Sustainable Development, 2(1), 59-80. (In Persian)  doi: 10.22077/vssd. 2021.4504.1033.
W.S, D., & J.L, W. (2005). Statistical analysis of geographic information with ArcView GIS& ArcGIS. Translation by: Mahmod Roshani; Parviz Rezaei & Sedighe Ganji, Rasht: Publications of the Environmental Research In-stitute of Jihad University. (In Persian)
Zhou, Y., Li, N., Wu, W., Wu, J., & Shi, P. (2014). Local spatial and temporal factors influencing population and societal vulnerability to natural disasters. Risk Anal, 34, 614–639. doi: 10.1111/risa.12193.