Assessment of the Effects of Social Vulnerability Indicators on Exposure and Physical Vulnerability

مقالات آماده انتشار

نوع مقاله : مقاله پژوهشی

نویسندگان
مهناز کشاورز 1
محمد محمدی 2
شایان گدری 3
عبدالسلام اسمعیل زاده 4
1 گروه جغرافیا، دانشکده حقوق و علوم اجتماعی، دانشگاه پیام نور، تهران، ایران.
2 گروه سنجش از دور و GIS، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران.
3 گروه برنامه‌ریزی شهری، دانشگاه آزاد اسلامی، کرمان، ایران.
4 گروه برنامه‌ریزی شهری و منطقه‌ای، دانشگاه علامه طباطبائی، تهران، ایران.
10.22034/he.2026.583730.1217
چکیده
The purpose of this research is to investigate the effects of social vulnerability indicators on exposure and physical vulnerability indicators in Masjed Soleyman, identified as a multi-hazard city. The study was carried out in three stages. In the first stage, both natural and human-induced hazards, including floods, earthquakes, landslides, and oil pollution, were identified and spatially analyzed. A composite exposure indicator was calculated for the city’s census tracts. In the second stage, social and physical vulnerabilities were weighted and ranked using multi-criteria decision-making techniques. In the third stage, the geographically weighted regression (GWR) model was employed to examine the effects of social indicators—including household density, illiteracy rate, unemployment rate, and the proportion of rental housing units—on the exposure and physical vulnerability indicators across the study area's census tracts. The results indicated that the central and southern parts of the city have the highest levels of exposure, while physical vulnerability is spatially dispersed across the city. In contrast, social vulnerability is most concentrated in the central and northern areas. The results of the GWR model reveal that social indicators have a positive and significant effect on exposure and physical vulnerability levels. The findings can guide municipal and provincial authorities in designing targeted risk-reduction strategies, optimizing resource allocation, and informing urban development decisions that account for social and physical vulnerabilities, while enhancing public awareness and fostering community engagement in hazard preparedness.
کلیدواژه‌ها
Multi-Hazard Assessment
Social Vulnerability
Physical vulnerability
Risk Reduction
GIS
موضوعات

عنوان مقاله English

Assessment of the Effects of Social Vulnerability Indicators on Exposure and Physical Vulnerability

نویسندگان English

Mahnaz Keshavarz 1
Mohammad Mohammadi 2
Shayan Gadari 3
Abdolsalam Esmailzadeh 4
1 Department of Geography, Faculty of Law and Social Sciences, Payame Noor University, Tehran, Iran
2 Department of Remote Sensing and GIS, Science and Research Branch, Islamic Azad University, Tehran, Iran.
3 Department of Urban Planning, Islamic Azad University, Kerman, Iran.
4 Department of Urban and Regional Planning, Allameh Tabataba’i University, Tehran, Iran.
چکیده English

The purpose of this research is to investigate the effects of social vulnerability indicators on exposure and physical vulnerability indicators in Masjed Soleyman, identified as a multi-hazard city. The study was carried out in three stages. In the first stage, both natural and human-induced hazards, including floods, earthquakes, landslides, and oil pollution, were identified and spatially analyzed. A composite exposure indicator was calculated for the city’s census tracts. In the second stage, social and physical vulnerabilities were weighted and ranked using multi-criteria decision-making techniques. In the third stage, the geographically weighted regression (GWR) model was employed to examine the effects of social indicators—including household density, illiteracy rate, unemployment rate, and the proportion of rental housing units—on the exposure and physical vulnerability indicators across the study area's census tracts. The results indicated that the central and southern parts of the city have the highest levels of exposure, while physical vulnerability is spatially dispersed across the city. In contrast, social vulnerability is most concentrated in the central and northern areas. The results of the GWR model reveal that social indicators have a positive and significant effect on exposure and physical vulnerability levels. The findings can guide municipal and provincial authorities in designing targeted risk-reduction strategies, optimizing resource allocation, and informing urban development decisions that account for social and physical vulnerabilities, while enhancing public awareness and fostering community engagement in hazard preparedness.

کلیدواژه‌ها English

Multi-Hazard Assessment
Social Vulnerability
Physical vulnerability
Risk Reduction
GIS
1.      Ahmadi, F., Nazeri Tahroudi, M., Mirabbasi, R., & Kumar, R. (2022). Spatiotemporal analysis of precipitation and temperature concentration using PCI and TCI: a case study of Khuzestan Province, Iran. Theoretical and Applied Climatology, 149(1–2), 743–760. https://doi.org/10.1007/s00704-022-04077-6
2.      Aksha, S. K., Resler, L. M., Juran, L., & Carstensen, L. W. (2020a). A geospatial analysis of multi-hazard risk in Dharan, Nepal. Geomatics, Natural Hazards and Risk, 11(1), 88–111. https://doi.org/10.1080/19475705.2019.1710580
3.      Aksha, S. K., Resler, L. M., Juran, L., & Carstensen, L. W. (2020b). A geospatial analysis of multi-hazard risk in Dharan, Nepal. Geomatics, Natural Hazards and Risk, 11(1), 88–111. https://doi.org/10.1080/19475705.2019.1710580
4.      Alam, M. S., Haque, S. M., Alam, M. S., & Haque, S. M. (2018). Assessment of Urban Physical Seismic Vulnerability Using the Combination of AHP and TOPSIS Models: A Case Study of Residential Neighborhoods of Mymensingh City, Bangladesh. Journal of Geoscience and Environment Protection, 6(2), 165–183. https://doi.org/10.4236/GEP.2018.62011
5.      Alikaei, S., Rahmani, M., Jamalabadi, F., Akdogan, M. E., & Khoshnevis, S. (2023). Multi-hazard based land use planning in isolated area; learning from the experience of Pul-e-Khumri City, Afghanistan. Sustainable Cities and Society, 99, 104873. https://doi.org/10.1016/J.SCS.2023.104873
6.      Alizadeh, M., Alizadeh, E., Kotenaee, S. A., & Shahabi, H. (2018). Social Vulnerability Assessment Using Artificial Neural Network ( ANN ) Model for Earthquake Hazard in Tabriz City , Iran. Sustainability. https://doi.org/10.3390/su10103376
7.      Alizadeh, M., Alizadeh, E., Kotenaee, S. A., Shahabi, H., Pour, A. B., Panahi, M., Bin Ahmad, B., & Saro, L. (2018). Social vulnerability assessment using artificial neural network (ANN) model for earthquake hazard in Tabriz city, Iran. Sustainability (Switzerland), 10(10), 3376. https://doi.org/10.3390/su10103376
8.      Amini, M., Sanderson, D. R., Cox, D. T., Barbosa, A. R., & Rosenheim, N. (2023). Methodology to incorporate seismic damage and debris to evaluate strategies to reduce life safety risk for multi-hazard earthquake and tsunami. Natural Hazards, 1–36. https://doi.org/10.1007/S11069-023-05937-8/METRICS
9.      Araya-Muñoz, D., Metzger, M. J., Stuart, N., Wilson, A. M. W., & Carvajal, D. (2017). A spatial fuzzy logic approach to urban multi-hazard impact assessment in Concepción, Chile. Science of The Total Environment, 576, 508–519. https://doi.org/10.1016/J.SCITOTENV.2016.10.077
10.   Arvin, M., Beiki, P., Hejazi, S. J., Sharifi, A., & Atashafrooz, N. (2023). Assessment of infrastructure resilience in multi-hazard regions: A case study of Khuzestan Province. International Journal of Disaster Risk Reduction, 88, 103601. https://doi.org/10.1016/J.IJDRR.2023.103601
11.   Ba, R., Deng, Q., Liu, Y., Yang, R., & Zhang, H. (2021). Multi-hazard disaster scenario method and emergency management for urban resilience by integrating experiment–simulation–field data. Journal of Safety Science and Resilience, 2(2), 77–89. https://doi.org/10.1016/J.JNLSSR.2021.05.002
12.   Bai, X., Song, K., Liu, J., Mohamed, A. K., Mou, C., & Liu, D. (2019). Health Risk Assessment of Groundwater Contaminated by Oil Pollutants Based on Numerical Modeling. International Journal of Environmental Research and Public Health 2019, Vol. 16, Page 3245, 16(18), 3245. https://doi.org/10.3390/IJERPH16183245
13.   Banihashemi, A., Khalilzadeh, M., Zavadskas, E. K., Antucheviciene, J., Banihashemi, C. :, Khalilzadeh, S. A. ;, & Zavadskas, M. ; (2021). Investigating the Environmental Impacts of Construction Projects in Time-Cost Trade-Off Project Scheduling Problems with CoCoSo Multi-Criteria Decision-Making Method. Sustainability 2021, Vol. 13, Page 10922, 13(19), 10922. https://doi.org/10.3390/SU131910922
14.   Bixler, R. P., Yang, E., Richter, S. M., & Coudert, M. (2021). Boundary crossing for urban community resilience: A social vulnerability and multi-hazard approach in Austin, Texas, USA. International Journal of Disaster Risk Reduction, 66, 102613. https://doi.org/10.1016/J.IJDRR.2021.102613
15.   Chakraborty, L., Rus, H., Henstra, D., Thistlethwaite, J., & Scott, D. (2020). A place-based socioeconomic status index: Measuring social vulnerability to flood hazards in the context of environmental justice. International Journal of Disaster Risk Reduction, 43, 101394. https://doi.org/10.1016/J.IJDRR.2019.101394
16.   Chen, C., Zhao, D., He, F., & Sun, F. (2023). A comprehensive multi‐hazard risk assessment model for an urban agglomeration with multiple factors. Journal of Safety Science and Resilience, 4(1), 43–51. https://doi.org/10.1016/J.JNLSSR.2022.09.008
17.   De Brito, M. M., Evers, M., & Delos Santos Almoradie, A. (2018). Participatory flood vulnerability assessment: A multi-criteria approach. Hydrology and Earth System Sciences, 22(1), 373–390. https://doi.org/10.5194/hess-22-373-2018
18.   de Loyola Hummell, B. M., Cutter, S. L., & Emrich, C. T. (2016). Social Vulnerability to Natural Hazards in Brazil. International Journal of Disaster Risk Science, 7(2), 111–122. https://doi.org/10.1007/s13753-016-0090-9
19.   Depietri, Y., Dahal, K., & McPhearson, T. (2018). Multi-hazard risks in New York City. Natural Hazards and Earth System Sciences, 18(12), 3363–3381. https://doi.org/10.5194/NHESS-18-3363-2018
20.   Dintwa, K. F., Letamo, G., & Navaneetham, K. (2019). Measuring social vulnerability to natural hazards at the district level in Botswana. Jamba: Journal of Disaster Risk Studies, 11(1). https://doi.org/10.4102/JAMBA.V11I1.447
21.   Drakes, O., & Tate, E. (2022a). Social vulnerability in a multi-hazard context: a systematic review. Environmental Research Letters, 17(3), 033001. https://doi.org/10.1088/1748-9326/AC5140
22.   Drakes, O., & Tate, E. (2022b). Social vulnerability in a multi-hazard context: a systematic review. Environmental Research Letters, 17(3), 033001. https://doi.org/10.1088/1748-9326/AC5140
23.   Ebert, A., Kerle, N., & Stein, A. (2009). Urban social vulnerability assessment with physical proxies and spatial metrics derived from air- and spaceborne imagery and GIS data. Natural Hazards, 48(2), 275–294. https://doi.org/10.1007/S11069-008-9264-0/METRICS
24.   Fang, Z., Liu, Z., Zhao, S., Ma, Y., Li, X., & Gao, H. (2022). Assessment of Groundwater Contamination Risk in Oilfield Drilling Sites Based on Groundwater Vulnerability, Pollution Source Hazard, and Groundwater Value Function in Yitong County. Water 2022, Vol. 14, Page 628, 14(4), 628. https://doi.org/10.3390/W14040628
25.   Fatemi, F., Ardalan, A., Aguirre, B., Mansouri, N., & Mohammadfam, I. (2017). Social vulnerability indicators in disasters: Findings from a systematic review. International Journal of Disaster Risk Reduction, 22, 219–227. https://doi.org/10.1016/J.IJDRR.2016.09.006
26.   Ferreira, T. M., & Santos, P. P. (2023). An Introduction to Multi-hazard Risk Interactions Towards Resilient and Sustainable Cities. 1–14. https://doi.org/10.1007/978-981-99-0745-8_1
27.   Gentile, R., Cremen, G., Galasso, C., Jenkins, L. T., Manandhar, V., Menteşe, E. Y., Guragain, R., & McCloskey, J. (2022). Scoring, selecting, and developing physical impact models for multi-hazard risk assessment. International Journal of Disaster Risk Reduction, 82, 103365. https://doi.org/10.1016/J.IJDRR.2022.103365
28.   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 2017, Vol. 9, Page 1274, 9(7), 1274. https://doi.org/10.3390/SU9071274
29.   Guo, S., Zhang, W., & Gao, X. (2020). Business Risk Evaluation of Electricity Retail Company in China Using a Hybrid MCDM Method. Sustainability 2020, Vol. 12, Page 2040, 12(5), 2040. https://doi.org/10.3390/SU12052040
30.   Hadipour, V., Vafaie, F., & Kerle, N. (2020). An indicator-based approach to assess social vulnerability of coastal areas to sea-level rise and flooding: A case study of Bandar Abbas city, Iran. Ocean & Coastal Management, 188, 105077. https://doi.org/10.1016/J.OCECOAMAN.2019.105077
31.   Hejazi, S. J., Sharifi, A., & Arvin, M. (2022). Assessment of social vulnerability in areas exposed to multiple hazards: A case study of the Khuzestan Province, Iran. International Journal of Disaster Risk Reduction, 78, 103127. https://doi.org/10.1016/J.IJDRR.2022.103127
32.   Highfield, W. E., Peacock, W. G., & Van Zandt, S. (2014). Mitigation Planning. Http://Dx.Doi.Org/10.1177/0739456X14531828, 34(3), 287–300. https://doi.org/10.1177/0739456X14531828
33.   Ikram, Q. D., Jamalzi, A. R., Hamidi, A. R., Ullah, I., & Shahab, M. (2023). Flood risk assessment of the population in Afghanistan: A spatial analysis of hazard, exposure, and vulnerability. Natural Hazards Research. https://doi.org/10.1016/J.NHRES.2023.09.006
34.   Jena, R., Pradhan, B., & Beydoun, G. (2020). Earthquake vulnerability assessment in Northern Sumatra province by using a multi-criteria decision-making model. International Journal of Disaster Risk Reduction, 46, 101518. https://doi.org/10.1016/J.IJDRR.2020.101518
35.   Kalaycıoğlu, M., Kalaycıoğlu, S., Çelik, K., Christie, R., & Filippi, M. E. (2023). An analysis of social vulnerability in a multi-hazard urban context for improving disaster risk reduction policies: The case of Sancaktepe, İstanbul. International Journal of Disaster Risk Reduction, 91, 103679. https://doi.org/10.1016/J.IJDRR.2023.103679
36.   Kappes, M. S., Papathoma-Köhle, M., & Keiler, M. (2012). Assessing physical vulnerability for multi-hazards using an indicator-based methodology. Applied Geography, 32(2), 577–590. https://doi.org/10.1016/J.APGEOG.2011.07.002
37.   Karami, S., Mousavi, S. M., & Antucheviciene, J. (2023). Enhancing Contractor Selection Process by a New Interval-Valued Fuzzy Decision-Making Model Based on SWARA and CoCoSo Methods. Axioms 2023, Vol. 12, Page 729, 12(8), 729. https://doi.org/10.3390/AXIOMS12080729
38.   Kassiri, H., Kasiri, A., & Fardin-Mohammadjani, M. (2014). A cross-sectional study on scorpionism in Masjed Soleyman County, Southwestern Iran. Journal of Entomology, 11(4), 238–247. https://doi.org/10.3923/JE.2014.238.247
39.   Khan, S. U., Qureshi, M. I., Rana, I. A., & Maqsoom, A. (2019). An empirical relationship between seismic risk perception and physical vulnerability: A case study of Malakand, Pakistan. International Journal of Disaster Risk Reduction, 41, 101317. https://doi.org/10.1016/J.IJDRR.2019.101317
40.   Khavarian-Garmsir, A. R., Pourahmad, A., Hataminejad, H., & Farhoodi, R. (2019). Climate change and environmental degradation and the drivers of migration in the context of shrinking cities: A case study of Khuzestan province, Iran. Sustainable Cities and Society, 47. https://doi.org/10.1016/j.scs.2019.101480
41.   Lee, Y. J. (2014). Social vulnerability indicators as a sustainable planning tool. Environmental Impact Assessment Review, 44, 31–42. https://doi.org/10.1016/J.EIAR.2013.08.002
42.   Malakar, S., & Rai, A. K. (2023). Estimating seismic vulnerability in West Bengal by AHP-WSM and AHP-VIKOR. Natural Hazards Research. https://doi.org/10.1016/J.NHRES.2023.06.001
43.   Malekian, A., & Azarnivand, A. (2016). Application of Integrated Shannon’s Entropy and VIKOR Techniques in Prioritization of Flood Risk in the Shemshak Watershed, Iran. Water Resources Management, 30(1), 409–425. https://doi.org/10.1007/S11269-015-1169-6/METRICS
44.   Mengal, A., Goda, K., Ashraf, M., & Murtaza, G. (2021). Social vulnerability to seismic-tsunami hazards in district Gwadar, Balochistan, Pakistan. Natural Hazards, 108(1), 1159–1181. https://doi.org/10.1007/S11069-021-04724-7/METRICS
45.   Mitra, R., & Das, J. (2022). A comparative assessment of flood susceptibility modelling of GIS-based TOPSIS, VIKOR, and EDAS techniques in the Sub-Himalayan foothills region of Eastern India. Environmental Science and Pollution Research 2022 30:6, 30(6), 16036–16067. https://doi.org/10.1007/S11356-022-23168-5
46.   Mladineo, N., Mladineo, M., Benvenuti, E., Kekez, T., & Nikolić, Ž. (2022). Methodology for the Assessment of Multi-Hazard Risk in Urban Homogenous Zones. Applied Sciences 2022, Vol. 12, Page 12843, 12(24), 12843. https://doi.org/10.3390/APP122412843
47.   Morales, F., & Vries, W. T. de. (2021). Establishment of Land Use Suitability Mapping Criteria Using Analytic Hierarchy Process (AHP) with Practitioners and Beneficiaries. Land 2021, Vol. 10, Page 235, 10(3), 235. https://doi.org/10.3390/LAND10030235
48.   Mousavi, S., Geology, M. R.-A. A., & 2020,  undefined. (n.d.). The zonation and assessment of slope instability hazard in Masjed Soleyman city using analytical hierarchy process and frequency ratio methods. Aag.Scu.Ac.IrSS Mousavi, M RahimiAdvanced Applied Geology, 2020•aag.Scu.Ac.Ir. Retrieved October 18, 2023, from https://aag.scu.ac.ir/article_15867.html?lang=en
49.   Pourghasemi, H. R., Gayen, A., Edalat, M., Zarafshar, M., & Tiefenbacher, J. P. (2020). Is multi-hazard mapping effective in assessing natural hazards and integrated watershed management? Geoscience Frontiers, 11(4), 1203–1217. https://doi.org/10.1016/J.GSF.2019.10.008
50.   Rusk, J., Maharjan, A., Tiwari, P., Chen, T. H. K., Shneiderman, S., Turin, M., & Seto, K. C. (2022). Multi-hazard susceptibility and exposure assessment of the Hindu Kush Himalaya. Science of The Total Environment, 804, 150039. https://doi.org/10.1016/J.SCITOTENV.2021.150039
51.   Saadat, M., Bahaoddini, A., Mohabatkar, H., & Noemani, K. (2004). High incidence of suicide by burning in Masjid-i-Sulaiman (southwest of Iran), a polluted area with natural sour gas leakage. Burns, 30(8), 829–832. https://doi.org/10.1016/j.burns.2004.06.003
52.   Saadat, M., Zendeh-Boodi, Z., & Ali Goodarzi, M. (2006). Environmental exposure to natural sour gas containing sulfur compounds results in elevated depression and hopelessness scores. Ecotoxicology and Environmental Safety, 65(2), 288–291. https://doi.org/10.1016/j.ecoenv.2005.07.024
53.   Safari, H. O., Pirasteh, S., Pradhan, B., & Gharibvand, L. K. (2010). Use of remote sensing data and GIS tools for seismic hazard assessment for shallow oilfields and its impact on the settlements at Masjed-i-Soleiman area, Zagros Mountains, Iran. Remote Sensing, 2(5), 1364–1377. https://doi.org/10.3390/rs2051364
54.   Sani, R. M., Shotorbani, P. M., & Doratli, N. (2015). Exploring the semiotic meaning of the first oil city in the Middle East: Masjed Soleyman. Social Semiotics, 25(3), 342–363. https://doi.org/10.1080/10350330.2015.1021552
55.   Santos-Reyes, J. (2020). Multi-hazard Awareness, Risk Perception and Fear to  Earthquakes: The Case of High-school Students in  Mexico City. Journal of Risk Analysis and Crisis Response, 10(3). https://doi.org/10.2991/jracr.k.200923.001
56.   Sevieri, G., Galasso, C., D’Ayala, D., De Jesus, R., Oreta, A., Grio, M. E. D. A., & Ibabao, R. (2020). A multi-hazard risk prioritisation framework for cultural heritage assets. Natural Hazards and Earth System Sciences, 20(5), 1391–1414. https://doi.org/10.5194/NHESS-20-1391-2020
57.   Shadmaan, M. S., & Popy, S. (2023). An assessment of earthquake vulnerability by multi-criteria decision-making method. Geohazard Mechanics, 1(1), 94–102. https://doi.org/10.1016/j.ghm.2022.11.002
58.   Soldati, A., Chiozzi, A., Nikolić, Ž., Vaccaro, C., & Benvenuti, E. (2022). A PROMETHEE Multiple-Criteria Approach to Combined Seismic and Flood Risk Assessment at the Regional Scale. Applied Sciences 2022, Vol. 12, Page 1527, 12(3), 1527. https://doi.org/10.3390/APP12031527
59.   Tasnuva, A., Hossain, M. R., Salam, R., Islam, A. R. M. T., Patwary, M. M., & Ibrahim, S. M. (2021). Employing social vulnerability index to assess household social vulnerability of natural hazards: an evidence from southwest coastal Bangladesh. Environment, Development and Sustainability, 23(7), 10223–10245. https://doi.org/10.1007/S10668-020-01054-9/METRICS
60.   Thakur, D. A., & Mohanty, M. P. (2023). A synergistic approach towards understanding flood risks over coastal multi-hazard environments: Appraisal of bivariate flood risk mapping through flood hazard, and socio-economic-cum-physical vulnerability dimensions. Science of The Total Environment, 901, 166423. https://doi.org/10.1016/J.SCITOTENV.2023.166423
61.   Thakur, P. K., Maiti, S., Kingma, N. C., Hari Prasad, V., Aggarwal, S. P., & Bhardwaj, A. (2012). Estimation of structural vulnerability for flooding using geospatial tools in the rural area of Orissa, India. Natural Hazards, 61(2), 501–520. https://doi.org/10.1007/s11069-011-9932-3
62.   Waly, N. M., Ayad, H. M., & Saadallah, D. M. (2021). Assessment of spatiotemporal patterns of social vulnerability: A tool to resilient urban development Alexandria, Egypt. Ain Shams Engineering Journal, 12(1), 1059–1072. https://doi.org/10.1016/J.ASEJ.2020.07.025
63.   Xofi, M., Domingues, J. C., Santos, P. P., Pereira, S., Oliveira, S. C., Reis, E., Zêzere, J. L., Garcia, R. A. C., Lourenço, P. B., & Ferreira, T. M. (2022). Exposure and physical vulnerability indicators to assess seismic risk in urban areas: a step towards a multi-hazard risk analysis. Geomatics, Natural Hazards and Risk, 13(1), 1154–1177. https://doi.org/10.1080/19475705.2022.2068457
64.   Yariyan, P., Karami, M. R., & Ali Abbaspour, R. (2019). EXPLOITATION OF MCDA TO LEARN THE RADIAL BASE NEURAL NETWORK (RBFNN) AIM PHYSICAL AND SOCIAL VULNERABILITY ANALYSIS VERSUS THE EARTHQUAKE (CASE STUDY: SANANDAJ CITY, IRAN). The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-4-W18(4/W18), 1071–1078. https://doi.org/10.5194/ISPRS-ARCHIVES-XLII-4-W18-1071-2019
65.   Zhang, T., Wang, D., & Lu, Y. (2023). Machine learning-enabled regional multi-hazards risk assessment considering social vulnerability. Scientific Reports 2023 13:1, 13(1), 1–14. https://doi.org/10.1038/s41598-023-40159-9
66.   Zou, Q., Cui, P., Zhang, Z., Sijimons, K., Titti, G., Li, S., & Jiang, H. (2022). A novel approach of multi-hazard integrated zonation on the ancient Silk Road. International Journal of Disaster Risk Reduction, 82, 103325. https://doi.org/10.1016/J.IJDRR.2022.103325
اکولوژی انسانی

مقالات آماده انتشار، پذیرفته شده
انتشار آنلاین از 09 خرداد 1405