جغرافیا  (نشریۀ انجمن جغرافیایی ایران)

جغرافیا (نشریۀ انجمن جغرافیایی ایران)

آسیب پذیری روستاهای گردشگری ایران از لحاظ مخاطره زمین لغزش با استفاده از GIS

نوع مقاله : علمی - پژوهشی

نویسندگان
1 استادیاردانشکده علوم جغرافیایی و برنامه ریزی، دانشگاه اصفهان، اصفهان، ایران.
2 استادیار گروه مدیریت جهانگردی، دانشکده میراث فرهنگی، صنایع دستی و گردشگری، دانشگاه مازندران، بابلسر، ایران.
چکیده
زمین‌لغزش یکی از مهم‌ترین مخاطرات طبیعی است که تأثیرات مخربی بر سکونتگاه‌های انسانی، به‌ویژه در مناطق روستایی و گردشگری دارد. با توجه به ویژگی‌های جغرافیایی ایران و گسترش روستاهای گردشگری، شناسایی و تحلیل آسیب‌پذیری این روستاها در برابر زمین‌لغزش امری ضروری است. استفاده از سامانه اطلاعات جغرافیایی (GIS) ابزار قدرتمندی برای ارزیابی این مخاطره فراهم می‌کند. این پژوهش با هدف تعیین میزان آسیب پذیری روستاهای گردشگری ایران از لحاظ مخاطره زمین لغزش انجام شده است. روش پژوهش تحلیلی-کمی و مبتنی بر تحلیل داده های مکانی در چارچوب فرآیند تحلیل سلسله‌مراتبی و همپوشانی وزنی است. عملیات تعیین معیارها، وزن دهی و همپوشانی انجام و در نهایت نقشه آسیب پذیری روستاهای گردشگری از لحاظ مخاطره زمین لغزش تهیه شد. نتایج نشان داد که 59/62 درصد مساحت کشور به عنوان پهنه با خطر بسیار کم؛ 55/19 درصد، پهنه با خطر کم، 20/11 درصد پهنه با خطر متوسط، 21/5 درصد پهنه با خطر زیاد و 43/1 درصد پهنه با خطر بسیار زیاد در زمینه مخاطره زمین لغزش شناخته شده است. بر اساس نتایج از مجموع 980 روستا، 25 روستای گردشگری ایران با آسیب پذیری بسیار بالا و 113 روستا با آسیب پذیری بالا در معرض مخاطره زمین لغزش قرار دارند. همچین ارزیابی توزیع روستاهای گردشگری با نقاط زمین لغزش، از تطبیق نتایج این پژوهش با نقاط نمونه برداشت شده اشاره دارد. همچنین نتایج نشان داد که بین نقشه نهایی و معیارهای ارزیابی مخاطره زمین لغزش، ارتباط وجود دارد. در مجموع برخی از روستاهای گردشگری ایران در معرض مخاطره زمین لغزش هستند که با توجه به نتایج این پژوهش می توان برای آنها برنامه ریزی عملیاتی و موثری را اتخاذ نمود.
کلیدواژه‌ها

موضوعات


عنوان مقاله English

Vulnerability of Iranian tourism villages in terms of Landslide hazard using GIS

نویسندگان English

Hojat Sadeghi 1
Fahad Javan 2
1 Assistant professor. Faculty of Geographical Sciences and Planning, University of Isfahan, Isfahan, Iran.
2 Assistant professor, Department of Tourism Management, Faculty of Cultural Heritage, Handicrafts and Tourism, University of Mazandaran, Babolsar, Iran.
چکیده English

Extended Abstract
Introduction
Landslide is one of the most important natural hazards that can have devastating effects on human settlements, especially in rural and tourism areas. Considering the geographical characteristics of Iran and the expansion of tourism villages in Iran, it is essential to identify and analyze the vulnerability of these villages to landslides. The use of Geographic Information Systems (GIS) provides a powerful tool for assessing and managing these risks. The purpose of this research is to investigate and analyze the vulnerability of Iran tourism villages to landslide hazard using GIS. The results of this study can provide appropriate solutions for crisis management and increasing the resilience of tourism villages, as well as reducing damage to these villages and prioritizing them in terms of hazard at the macro level. In addition to contributing to the sustainable development of tourism, this research can help planners make optimal decisions to reduce landslide risks, considering the situation of villages in each region or province. Considering the importance of the issue, it seems necessary to address this issue from a scientific and practical point of view. Therefore, the basic question of the research is how vulnerable are the tourism villages of Iran in terms of the landslide hazard?
 
Methodology
The research method is applied in terms of purpose and based on nature, analytical-quantitative. Data analysis was performed based on spatial data in Arc GIS software. To assess the vulnerability of Iran tourism villages in terms of landslide hazard, in the first stage, the most important criteria in the field of zoning and identifying landslide areas were identified. Based on previous research, 9 criteria including slope (percentage), height (meters), erosion (degrees), soil type, land use type, precipitation (millimeters), distance from fault (meters), distance from waterways (meters), and distance from road (meters) were selected for this study. In the second stage, maps related to each criterion were prepared. In the third stage, according to the purpose of the research, weighting operations were applied to the maps within the framework of the analytic hierarchy process and layer standardization was performed. Next, the weight and importance of the criteria relative to each other were evaluated. Then, the weighted maps were combined by applying the weight of each layer using a weighted overlap algorithm, and the final map that identified the vulnerability and landslide risk zones was obtained.
 
Results and discussion
Explanation and analysis of the results indicate that slope and erosion are known as the most important factors affecting the occurrence of landslide. This indicates a direct dependence of ground instability on topographic conditions, especially in high-altitude areas with steep slopes where the potential for landslide is greater. The high impact of these factors indicates the need for land use management in susceptible areas and imposing restrictions on human activities such as road building and construction in such areas. On the other hand, the distribution of criteria weights shows that other environmental factors also play a significant role, but their impact is meaningful in combination and not independently. For example, in areas where heavy rainfall is accompanied by steep slopes, the probability of landslides increases significantly.
The results showed that 62.59 percent of the country's area is known as a very low risk area; 19.55 percent is a low risk area; 11.20 percent is a medium risk area; 21.5 percent is a high risk area; and 1.43 percent is a very high risk area in terms of landslide hazard. Based on the results, 25 Iran tourism villages with very high vulnerability and 113 villages with high vulnerability are at risk of landslides. Analysis of the area of ​​various vulnerable zones shows that 62 percent of the area of ​​tourism villages is located in very low-risk zones, but more than 13 percent of the villages are located in high- and very high-risk zones that require special attention and preventive measures. These villages, which are located in high and very high risk zones, include 25 villages, mainly located in the western and northern regions of the country and are at risk of more serious landslides due to specific climatic and geographical conditions. The results of a study of the vulnerability of Iran tourism villages to landslide risk indicate the unequal distribution of this hazard throughout the country. Most of the areas with high and very high vulnerability are located in the western and northern regions of the country, which have favorable characteristics for the development of tourism villages in terms of climate and environmental conditions. This indicates the co-occurrence of high density of tourism villages with high-risk areas, which is especially evident in areas with steep slopes and high rainfall. On the contrary, by moving towards the central and southern regions of the country, the level of vulnerability decreases, which is due to features such as drier climatic conditions, Less erosion, soil type and gentler slope in these areas.
 
Conclusion
Overall, to protect tourism villages and reduce landslide risks, it is essential to adopt management and preventive measures for these areas, especially high- and very high-risk villages. These measures can include appropriate programs to stabilize slopes, control soil erosion, enhance vegetation cover, as well as restrictions on the development of certain human activities in these sensitive areas. It is suggested that in addition to single-factor analysis, a comprehensive and multi-criteria approach be adopted in risk management studies to achieve more accurate results for reducing landslide losses.

کلیدواژه‌ها English

Hazards
landslide
tourism villages
GIS
  1. اصغری سرسکانرود، صیاد و پیروزی، الناز . (1403). شناسایی و پهنه بندی مناطق مستعد وقوع خطر زمین لغزش با استفاده از روش تحلیل چندمعیارۀ (منطقۀ مورد مطالعه: حوضۀ آبخیز قرنقوچای در جنوب شرق استان آذربایجان شرقی). جغرافیا و برنامه ریزی محیطی، 35(3)، 65-94.https://doi.org/10.22108/gep.2024.140985.1639
  2. آتش افروز، نسرین و صفائی پور، مسعود. (1400). ریز پهنه بندی زمین لغزش با استفاده از تکنیک دیمتل و AHP فازی (مطالعه موردی: بخش دهدز استان خوزستان). فصلنامه مطالعات توسعه پایدار شهری و منطقه ای،2(2)، 61-81.https://www.srds.ir/article_134524.html
  3. جمینی، داود؛ جوان، فرهاد و حیدریان، بیتا. (1403). شناسایی چالش‌ها و راهکارهای توسعه ژئوتوریسم در سکونتگاه‌های روستایی منتخب در استان‌های کردستان، کرمانشاه و همدان. برنامه‌ریزی و توسعه گردشگری، 13(51): 237-215.https://doi.org/10.22080/jtpd.2024.28159.3943
  4. جمینی، داود؛ شهابی، هیمن؛ نظری، حمید و آتش بهار، رامین . (1402). شناسایی سکونتگاه های روستایی در معرض خطر وقوع زمین لغزش در زیست بوم های عشایری (مطالعه موردی: شهرستان پاوه). مطالعات برنامه ریزی قلمرو کوچ نشینان. 3(1)، 107-122.https://doi.org/10.22034/jsnap.2023.410697.1066
  5. حسین زاده، سیدرضا؛ قربانی شورستانی، علی؛ نورمحمدی، علی محمد و رضائی عارف، محسن. (1394). بررسی عوامل مؤثر بر وقوع زمین لغزش با استفاده از GIS و RS (مطالعه: موردی سد دوستی).  هیدروژئومورفولوژی،2(4)، 21-38.https://dor.org/20.1001.1.23833254.1394.2.4.2.5
  6. درویشی، یوسف و موسوی ندوشن، سید معین. (1402). تحلیل فضایی حساسیت وقوع زمین لغزش در محدوده های روستایی و شهری (مطالعه موردی: حریم مناطق تابع شهرستان گرگان در حوضه آبخیز زرین گل). مهندسی جغرافیایی سرزمین،7(2)، 333-350.https://doi.org/10.22034/jget.2023.147993
  7. رضوانی، محمدرضا؛ دربان آستان، علیرضا و ترابی، ذبیح الله. (1401). طرح ارزیابی، اعتبارسنجی و رتبه بندی روستاهای هدف گردشگری، تهران: پژوهشگاه میراث فرهنگی، گردشگری و صنایع دستی، وزارت میراث فرهنگی، گردشگری و صنایع دستی.https://www.imna.ir/
  8. روستایی، شهرام؛ مختاری، داود و اشرفی فینی، زهرا. (1399). پهنه بندی خطر زمین لغزش در حوضه آبریز طالقان با استفاده از شاخص آنتروپی شانون. جغرافیا و برنامه‌ریزی،24(71)، 125-150.https://doi.org/10.22034/gp.2020.10631
  9. شادفر، صمد؛ نصیری هنده خاله، اسماعیل؛  گلمهر، احسان و نصیری، محمد. (1401). پهنه بندی خطر وقوع زمین لغزش در قلمرو کوچ نشینان (مطالعه موردی: حوضه طالقان). مطالعات برنامه ریزی قلمرو کوچ نشینان، 2(2)، 65-76.https://doi.org/10.22034/jsnap.2023.380450.1040
  10. شریفی، حسین؛ رمضانی پور، مهرداد؛ ابراهیمی، لیلا و حق زاد، آمنه. (1400). پهنه بندی خطر زمین لغزش شهرستان نور با استفاده از مدل تحلیل شبکه. پژوهش‌های جغرافیای اقتصادی،2(6)، 40-55.https://doi.org/20.1001.1.27173747.1400.2.6.4.0
  11. صابر چناری، کاظم؛ واحد بردی، شیخ و سلمانی، حسین. (1395). ارزیابی مدل LNRF در تهیه نقشه خطر زمین لغزش با استفاده از GIS در حوزه آبخیز زیارت گرگان. پژوهش های آبخیزداری،29(3)، 14-23.https://doi.org 10.22092/wmej.2016.113506
  12. صادقی، حجت الله.(1402). ارزیابی تطبیقی مدل‌های هم‌پوشانی فازی جهت تعیین پهنه‌های مستعد ایجاد اماکن اقامتی-گردشگری در منطقۀ دزپارت با مدل‌های Gamma، برنامه ریزی فضایی، 13(4)، 1-22.
  13. https://doi.org/10.22108/sppl.2023.138669.1759
  14. صفایی پور، مسعود؛ شجاعیان، علی و آتش افروز، نشرین. (1395). پهنه بندی زمین لغزش با استفاده از مدل AHP در محیط GIS (منطقه مورد مطالعه روستای دره گز قلندران شهر دهدز). جغرافیای طبیعی، 9(1): 105-118 https://www.sid.ir/paper/185046/fa
  15. غلامی، یونس و شفیعی، زهرا. (1400). بررسی عوامل موثر بر توسعه گردشگری روستایی با تاکید بر روستای هدف گردشگری(مطالعه موردی، روستای فشن، شهرستان کنگاور). جغرافیا و روابط انسانی، 4(2)، 371-398.https://doi.org/10.22034/gahr.2021.299682.1598
  16. لجم اورک، مرتضی و پیری، زهرا. (1402). پهنه‌بندی خطر وقوع زمین‌لغزش با استفاده از مدل تحلیل سلسله مراتبی (AHP) و فن GIS (مطالعۀ موردی: شهرستان باغملک. جغرافیا و مخاطرات محیطی. 12(3)، 193-215. https://doi.org/10.22067/geoeh.2022.77009.1239
  17. مکرم، مرضیه و شایگان، مهران . (1397). ارزیابی خطر زمین لغزش و ارتباط آن با نوع لندفرم در محیطپژوهشهای ژئومورفولوژی کمّی،6(4)، 17-31.https://doi.org/20.1001.1.22519424.1397.6.4.2.9
  18. Ahmed, B. (2021). The root causes of landslide vulnerability in Bangladesh. Landslides, 18(5), 1707-1720.‏https://link.springer.com/article/10.1007/s10346-020-01606-0
  19. Aji, R. R., Faniza, V. & Damayanti, V. (2021). Landslide Disaster Engineering in Tourism Potential Area. In IOP Conference Series: Earth and Environmental Science (Vol. 830, No. 1, p. 012036). IOP Publishing.‏https://doi.org/10.1088/1755-1315/830/1/01203
  20. Asmare, D. (2022). Landslide hazard zonation and evaluation around Debre Markos town, NW Ethiopia—a GIS-based bivariate statistical approach. Scientific African, 15(2), 1-20. https://doi.org /10.1016/j.sciaf.2022.e01129
  21. Bachri, S., Shrestha, R. P., Sumarmi, S., Aksa, F. I., Prastiwi, M. R., Putri, N. R. & Hidiyah, T. M. (2024). Optimizing Tourism Development Through Landslide Hazard Mapping in Raung Volcano. Jurnal Geografi-Vol, 16(1), 1-16.‏ https://doi.org/10.24114/jg.v16i1.50118
  22. Chen, L., Yang, H., Song, K., Huang, W., Ren, X. & Xu, H. (2021). Failure mechanisms and characteristics of the Zhongbao landslide at Liujing Village, Wulong, China. Landslides, 18(4), 1445-1457.‏https://link.springer.com/article/10.1007/s10346-020-01594-
  23. Chen, S., Law, R. & Zhang, M. (2021). Review of research on tourism-related diseases. Asia Pacific Journal of Tourism Research, 26(1), 44-58.‏https://doi.org/abs/10.1080/10941665.2020.1805478
  24. Das, S., Sarkar, S. & Kanungo, D. P. (2022). GIS-based landslide susceptibility zonation mapping using the analytic hierarchy process (AHP) method in parts of Kalimpong Region of Darjeeling Himalaya. Environmental Monitoring and Assessment, 194(4), 234-251. https://link.springer.com/article/10.1007/s10661-022-09851-7
  25. Dastranj A, Noor H. & Bagherian Kalat A. (2022).GIS-based Landslide Susceptibility Zoning Using Multi-Criteria Decision-making Method: A Case Study in Binalood Mountains, Iran. journal of Rescue and Relief, 14 (1) :19-29. http://jorar.ir/article-1-726-en.html
  26. Diara, I. W., Wahyu Wiradharma, I., Suyarto, R., Wiyanti, W. & Saifulloh, M. (2023). Spatio-temporal of landslide potential in upstream areas, Bali tourism destinations: remote sensing and geographic information approach. Journal of Degraded & Mining Lands Management, 10(4).‏ 4769-4777. https://doi.org/10.15243/jdmlm.2023.104.4769
  27. Hosenuzzaman, M., Kibria, M. G., Sarkar, R. & Abedin, M. A. (2022). Landslide, agricultural vulnerability, and community initiatives: a case study in South-East part of Bangladesh. Impact of climate change, land use and land cover, and socio-economic dynamics on landslides,18(3), 123-145.‏ https://link.springer.com/chapter/10.1007/978-981-16-7314-6_5
  28. Ietto, F., Conforti, M., Tolomei, C. & Cianflone, G. (2022). Village relocation as solution of the landslide risk, is it always the right choice? The case study of Cavallerizzo ghost village (Calabria, southern Italy). International Journal of Disaster Risk Reduction, 81(2),34-49.https://doi.org/10.1016/j.ijdrr.2022.103267
  29. Jallayu, P. T., Sharma, A. & Singh, K. (2024). Vulnerability of highways to landslide using landslide susceptibility zonation in GIS: Mandi district, India. Innovative Infrastructure Solutions, 9(9), 1-18. https://link.springer.com/article/10.1007/s41062-024-01653-9
  30. Ji, J., Cui, H., Zhang, T., Song, J. & Gao, Y. (2022). A GIS-based tool for probabilistic physical modelling and prediction of landslides: GIS-FORM landslide susceptibility analysis in seismic areas. Landslides, 19(9), 2213-2231.‏ https://link.springer.com/article/10.1007/s10346-022-01885-9
  31. Krisandika, K. & Sutrisno, A. J. (2023). Analysis of land use factor on landslide using modified frequency ratio. Proceeding Sustainable Agricultural Technology Innovation (SATI), 2(1), 53-65.‏ https://www.ojs.unkriswina.ac.id/index.php/semnas-FST/article/view/532
  32. Kumar, A., Sharma, R. K. & Bansal, V. K. (2022). Spatial prediction of landslide hazard using GIS-multi-criteria decision analysis in kullu district of Himachal Pradesh, India. Journal of Mining and Environment, 13(4), 943-956.‏ https://doi.org/10.22044/jme.2022.12235.2222
  33. Mani, A., Kumari, M. & Badola, R. (2024). Landslide hazard zonation (LHZ) mapping of Doon Valley using multi-criteria analysis method based on remote sensing and GIS techniques. Discover Geoscience, 2(1), 1-21. https://link.springer.com/article/10.1007/s44288-024-00044-y
  34. Mekonnen, A. A., Raghuvanshi, T. K., Suryabhagavan, K. V. & Kassawmar, T. (2022). GIS-based landslide susceptibility zonation and risk assessment in complex landscape: A case of Beshilo watershed, northern Ethiopia. Environmental Challenges, 8(3),1-23.https://doi.org/10.1016/j.envc.2022.100586
  35. Mirdda, H. A., Bera, S. & Chatterjee, R. (2022). Vulnerability assessment of mountainous households to landslides: A multidimensional study in the rural Himalayas. International Journal of Disaster Risk Reduction, 71(2),1-17.https://doi.org/10.1016/j.ijdrr.2022.102809
  36. Moragues, S., Lenzano, M. G., Jeanneret, P., Gil, V. & Lannutti, E. (2024). Landslide susceptibility mapping in the Northern part of Los Glaciares National Park, Southern Patagonia, Argentina using remote sensing, GIS and frequency ratio model. Quaternary Science Advances, 13, 100146.‏ https://doi.org/10.1016/j.qsa.2023.100146
  37. Sudmeier-Rieux, K., Paleo, U. F., Garschagen, M., Estrella, M., Renaud, F. G. & Jaboyedoff, M. (2015). Opportunities, incentives and challenges to risk sensitive land use planning: Lessons from Nepal, Spain and Vietnam. International Journal of Disaster Risk Reduction, 14, 205-224.‏ https://doi.org/10.1016/j.ijdrr.2014.09.009
  38. Tyagi, A., Tiwari, R. K. & James, N. (2021). GIS-based landslide hazard zonation and risk studies using MCDM. In Local Site Effects and Ground Failures: Select Proceedings of 7th ICRAGEE 2020 (pp. 251-266). Springer Singapore.‏https://link.springer.com/chapter/10.1007/978-981-15-9984-2_22
  39. Wang, P., Deng, H. & Liu, Y. (2024). GIS-based landslide susceptibility zoning using a coupled model: a case study in Badong County, China. Environmental Science and Pollution Research, 31(4), 6213-6231.‏https://link.springer.com/article/10.1007/s11356-023-31621-2
  40. Yang, Z., Lu, H., Zhang, Z., Liu, C., Nie, R., Zhang, W.& Zhang, D. (2023). Visualization analysis of rainfall-induced landslides hazards based on remote sensing and geographic information system-an overview. International Journal of Digital Earth, 16(1), 2374-2402.‏ org/10.1080/17538947.2023.2229797
  41. Ye, X., Wen, J., Zhu, Z. & Sun, R. (2022). Natural disaster risk assessment in tourist areas based on multi scenario analysis. Earth Science Informatics, 1-12.‏ https://link.springer.com/article/10.1007/s12145-020-00518-w
  42. Zahor, Z. & Yamungu, N. E. (2022). Geographical Information Systems (GIS) and Remote Sensing (RS) Analysis for Landslides Susceptibility Mapping. University of Dar es Salaam Library Journal, 17(2), 72-93.‏ https://doi.org/4314/udslj.v17i2.6
  43. Asghari Saraskanroud, S. & Piroozi, E. (2024). Identification and Zoning of Areas Prone to the Occurrence of Landslides Using the Aras Multi-Criteria Analysis Method (Study Area: Qaranqoochay Watershed in the Southeast of East Azarbaijan Province). Geography and Environmental Planning, 35(3), 65-94. https://doi.org/10.22108/gep.2024.140985.1639  [persian]
  44. Atashafrooz, N.& safaee, M. (2021). Landslide Micro-Zoning Using DEMATEL Technique and Fuzzy AHP (Case Study: the County of Dehdez in Khuzestan Province). Journal of Sustainable Urban & Regional Development Studies (JSURDS), 2(2), 61-81.https://www.srds.ir/article_134524.html  [persian]
  45. Darvishi, Y. & Moosavi nadoshan, S. M. (2023). Spatial analysis of landslide susceptibility in rural and urban areas using climatic and topographic indicators (Case study: boundaries of Gorgan city in Zarrin Gol watershed). Geographical Engineering of Territory, 7(2), 333-350.https://doi.org /10.22034.2023.147993  [persian]
  46. Gholami, Y. & shafiei, Z. (2021). vestigating the effective factors on rural tourism development with emphasis on toutarget village (Case study: Fash village; Kangavar city). Geography and Human Relationships, 4(2), 371-398. https://doi.org/10.22034/gahr.2021.299682.1598  [persian]
  47. Jamini, D., Javan, F. & Heydarian, B. (2024). Identification of Challenges and Solutions for The Development of Geotourism in Selected Rural Settlements in Kurdistan, Kermanshah and Hamedan Provinces. Journal of Tourism Planning and Development, 13(51), 215-237. https://doi.org/10.22080.2024.28159.3943 [persian]
  48. Jamini, D., Shahabi, H., Nazari, H. & Atashbahar, R. (2023). Identifying rural settlements at risk of landslides in nomadic ecosystems (case study: Paveh county). Nomadic Territory Planning Studies, 3(1), 107-122. https://doi.org/10.22034.2023.410697.1066 [persian]
  49. Lajmorak, M. & Piri, Z. (2023). Landslide Hazard Zoning Using Hierarchical Analysis Process (AHP) Model and GIS Technology (Case Study: Baghmalek County). Journal of Geography and Environmental Hazards, 12(3), 193-215. https://doi.org/10.22067/geoeh.2022.77009.1239  [persian]
  50. Makram, M. & Shaygan, M (2018). Landslide risk assessment and its relationship to the type of landform in the GIS. Quantitative Geomorphological Research, 6(4), 17-31.20.1001.1.22519424.1397.6.4.2.9  [persian]
  51. Rezvani, M.R., Darban Astan, A.R. & Torabi, Z. (202023). Evaluation, Validation and Ranking Plan for Tourism Target Villages, Tehran: Cultural Heritage, Tourism and Handicrafts Research Institute, Ministry of Cultural Heritage, Tourism and Handicrafts.  [persian]
  52. Roustaie, S., Mokhtari, D. & Ashrafi Fini, Z. (2020). Landslide hazard zonation in Taleghan watershed using Shannon entropy index. Journal of Geography and Planning, 24(71), 125-150. https://doi.org/10.22034/gp.2020.10631  [persian]
  53. Saber Chenari, K., Sheykh, V. & Salmani, H. (2016). Assessment of LNRF model in landslide Hazard mapping using GIS in Ziarat watershed, Gorgan. Watershed Management Research, 29(3), 14-23.https://doi.org/10.22092.2016.113506  [persian]
  54. Sadeghi, H. (2024). Comparative Evaluation of Fuzzy Overlay Models for Identifying Potential Sites for Tourist Accommodation in Dezpart Region Using Gamma and Sum Models. Spatial Planning, 13(4), 1-22.https://doi.org/10.22108.2023.138669.1759  [persian]
  55. Safaeipour, M., Shojaian, A. & Atashafrooz, N. (2016). Landslide zoning using the AHP model in a GIS environment (study area: Darreh Gaz Qalandran village, Dehdez city). Natural Geography, 9(1): 105-118.https://www.sid.ir/paper/185046/fa  [persian]
  56. Shadfar, S., Nasiri Hendehkhaleh, E. , Golmehr, E. & Nasiri, M. (2023). Landslide Hazard Modeling in Taleghan Watershed(Case study: Nomads area in Taleghan). Nomadic Territory Planning Studies, 2(2), 65-76.https://doi.org/10.22034.2023.380450.1040  [persian]
  57. Sharifi, H., Ramazanipore, M. , Ebrahimi, L. & Haghzad, A. (2022). Landslide hazard zoning of Noor city using network analysis model. Economic Geography Research, 2(6), 40-55.https://doi.org/20.1001.1.27173747.1400.2.6.4.0  [persian].