پهنهبندی حساسیت زمینلغزش با استفاده از روش ترکیبی جدید در محیط GIS
محورهای موضوعی :
مدیریت بلایای طبیعی
مجید محمدی
1
,
حمزه نور
2
1 - استادیار دانشکده مهندسی منابع طبیعی دانشگاه سمنان، سمنان، ایران، *(مسوول مکاتبات).
2 - استادیار بخش تحقیقات حفاظت خاک و آبخیزداری، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی استان خراسان رضوی، سازمان تحقیقات، آموزش و ترویج کشاورزی، مشهد، ایران
تاریخ دریافت : 1396/04/13
تاریخ پذیرش : 1396/09/01
تاریخ انتشار : 1398/12/01
کلید واژه:
تراکم سطح,
فرآیند تحلیل سلسله مراتبی,
پهنهبندی حساسیت زمینلغزش,
مدل تلفیقی,
زمینلغزش,
چکیده مقاله :
زمینه و هدف: زمین لغزش از جمله مهم ترین سوانح طبیعی در مناطق شیبدار با خسارات انسانی و اقتصادی زیاد است. ایران به خاطر شرایط خاص آب و هوایی و فیزیوگرافی همواره در معرض خطر زمین لغزش قرار دارد. هدف از این تحقیق تهیه نقشه حساسیت زمینلغزش با استفاده از مدل تلفیقی فرآیند تحلیل سلسله مراتبی-تراکم سطح در محیط GIS، در بخشی از حوزه آبخیز هراز است.
روش بررسی: ابتدا با مطالعات میدانی نقشه پراکنش زمین لغزش های حوزه و سپس نقشه عوامل موثر بر زمین لغزش تهیه گردید. وزندهی فاکتور های موثر با استفاده از فرآیند تحلیل سلسله مراتبی و نرمافزار Expert Choice انجام شد. وزن کلاسههای هر فاکتور با استفاده از مدل تراکم سطح در محیط GIS محاسبه گردید. در نهایت وزن کلاسهها در وزن فاکتور ضرب شد. وزنها در محیط GIS با هم تلفیق شده و نقشه نهایی حساسیت زمینلغزش به دست آمد.
یافتهها: بررسی ها نشان داد که خصوصیات سنگ شناسی، فاصله از جاده، شیب، فاصله از آبراهه، کاربری اراضی، ارتفاع و جهت شیب عوامل اصلی موثر در وقوع زمین لغزش در منطقه هستند. نتایج نشان داد که شیب 50-15 درصد، جهت های شیب شمالی و غربی، ارتفاع 2100-1500، کاربریهای مسکونی و باغ-کشاورزی، فاصله 500 متری از جاده و 400 متری از آبراهه، سازندهای شمشک و پادگانه های آبرفتی بیشترین حساسیت را نسبت به زمین لغزش از خود نشان دادند.
بحث و نتیجهگیری: به طور کلی منطقه مورد مطالعه مطالعه به وقوع زمینلغزش حساسیت زیادی داشته و تهیه نقشه حساسیت زمینلزش در این منطقه بسیار ضروری است. نقشه تهیه شده ابزار مفیدی در برنامه ریزی کاربری اراضی خواهد بود.
چکیده انگلیسی:
Introduction: Landslides are one of the most natural hazards in hilly regions with great human and economic losses in the worldwide. Iran is always exposed to landslide susceptibility because of climatic and physiographic conditions. The purpose of this research is landslide susceptibility mapping using AHP-Density area model in GIS environment in the part of Haraz Watershed.
Methods: Landslide inventory map was created using field surveys, and then conditioning factors were prepared. Using AHP model and Expert Choice software, weight of each factor was calculated. Weight of classes for each factor was calculated using the density area model in the GIS environment. Finally, weight of classes and weight of factors was multiplied. Weighted map was integrated in GIS environment and the final zoning map created.
Results: Results indicated that lithology, distance from road, slope angle, distance from drainage network, land use, elevation, and slope aspect are the main landslide controlling factors in the area. Results showed that slope of 15-50 percent, north and west facing, altitude of 1,500–2,100 m, residential and mixing orchard and agriculture area types of land use, distance of 500 meter from road and 400 meter from drainage network, Shemshak formation and fluvial terraces are very susceptible to landslide.
Discussion and conclusion: In general, study area is very susceptible to landslide occurrence and landslide susceptibility mapping is very essential in this region. The resultant map would be useful for general land use planning.
منابع و مأخذ:
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- Feizizadeh, B.,Blaschke,T., 2013. GIS-multicriteria decision analysis for landslide susceptibility mapping: comparing three methods for the Urmia Lake basin Iran. Natural Hazard, 65, 2105–2128.
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- Sarvati, M.R., Nosrati, K., Hasanvandi, S., Mirbagheri, B., 2014. Prediction of Landslide Hazard in Sikan River Basin Using Logistic Regression Model, 67(1), 17-29 (In Persian).
- Sangchini Karimi, E., Ownegh, M., Sadoddin, A., 2013. Assessment of landslide hazard, risk in Chehel - Chay Watershed, Golestan Province, Iran. Watershed management research, 98, 74-84. (In Persian).
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- Shadfar, P., Yamani, M., Namaki, M., 2005. Landslide hazard zonation using information value models, surface density, and LNRE in the Chalker field. Journal of Water and Watershed, 3, 62-68. (In Persian).
- Feiznia, S., Kalarstaghi, A., Ahmadi, H., Safaei, M., 2002. Investigating the factors affecting the occurrence of landslides and zoning of the land slide risk of Shirin-rood-Dam Tajan watershed. Journal of Natural Resources of Iran, 57 (1), 3-20. (In Persian).
9. Yalcin, A., .2008. GIS-based landslide susceptibility mapping using analytical hierarchy process and bivariate statistics in Ardesen (Turkey): Comparisons of results and confirmations. Catena, 72, 1-12.
Ayalew, L., Yamagishi, H., Marui, H., Kanno, T., .2005. Landslides in Sado Island of Japan: Part II. GIS-based susceptibility mapping with comparisons of results from two methods and verifications. Engineering Geology, 81, 432– 445.
Ghodsipoor, H., 2003. Analytical Hierarchy Process (AHP). Amirkabir Publication. 4, 220p (In Persian).
Komac, M., 2006. A landslide susceptibility model using the analytical hierarchy process method and multivariate statistics in pri-alpine Slovenia. Geomorphology, 74, 17-28.
Mirnazari, J., Khezri, S., Shahabi, H., 2015. Assessment and zoning of landslide hazard sing AHP model and fuzzy logic operation in Posht tang watershed of sar pole zahab (Kermanshah province). Geography and development, 12 (37), 35-70 (In Persian).
Gee, M.D., .1991. Classification of landslide hazard zonation methods and a test of predictive capability, Landslides, Bell (ed.), Balkema, Rotterdam. pp. 947- 952.
Ohlmacher, G.C. Davis, J.C., .2003. Using multiple logistic regression and GIS technology to predict landslide hazard in Northeast Kansas, USA. Engineering Geology, 69, 331-343.
Yamani, M., Shamsipour, A., Goorabi, A., Rahmati, M., 2014. Determining landslide zones in Khoramabad-pole zaal freeway by using hierarchy analysis-fuzzy logic method. Journal of geographical sciences, 14(32), 27-44 (In Persian).
Chau, K.T., Chan, J.E., .2005. Regional bias of landslide data in generating susceptibility maps using logistic regression: Case of Hong Kong Island. Landslides, 2, 280-290.
Lee, S., Abdul Talib, J., .2005. Probabilistic landslide susceptibility and factor effect analysis. Environmental Geology, 47, 982-990.
Dymond, J.R., Ausseeil, A.G., Shepherd, J.D., Buettner, l., .2006. Validation of a Region- Wide Model of Landslide Susceptibility in the Manawatu- Wanganui Region of New Zealand. Geomorphology, 74, 70-79.
Duman, T. Y., Can, T., Gokceoglu, C., Nefeslioglu, H. A., Sonmez, H., .2006. Application of logistic regression for landslide susceptibility zoning of Cekmece Area, Istanbul, Turkey. Environmental Geology, 51, 241-256.
Lee, S., .2007. Application and verification of fuzzy algebraic operators to landslide susceptibility mapping. Environmental Geology, 52, 615-623.
Mohammady, M., Pourghasemi, H.R., Pradhan, B., .2012. Landslide susceptibility mapping at Golestan province, Iran: a comparison between frequency ratio, Dempster–Shafer, and weights-ofevidence models. Journal of Asian Earth Sciences, 61, 221–236.
Ahmadi, H., Mohammad Khan, S., Feiznia, S., Ghoddoosi. J., 2006. Landslide hazard zonation by AHP hierarchical analysis method in Taleghan basin, Natural Resources Journal. 58, 3-14 (In Persian).
Ercanoglu, M., Gokceoglu, C., .2004. Use of fuzzy relations to produce landslide susceptibility map of a landslide prone area (West Black Sea Region, Turkey). Engineering Geology, 75, 229–250.
Abedini, M., Ghasemian, B., Shirzadi, A., 2014. Modelling the Hazard of Landslides by Using Statistical Method of Logistic Regression. Geography and development Iranian journal, 37, 85-120 (In Persian).
Neuhauser, B., Terhorst, B., .2006. Landslide Susceptibility Assessment Using Weights-of- Evidence Applied to a Study Area at the Jurassic Escarpment (SW-Germany). Geomorphology, 1-13.
Mohammadi, M., Moradi, H. R., Feizenya, S., Pourghasemi, H. R., 2009. Prioritizing the factors affecting the landslide and preparing its hazard map using information value models and AHP in a part of the Haraz watershed. Journal of Geosciences, 19 (74), 27- 32 (In Persian).
Mohammadi, M., Moradi, H. R., Feizenya, S., Pourghasemi, H. R., 2009. Comparison of the Efficiency of Certainty Factor, Information Value and AHP Models in Landslide Hazard Zonation (Case study: Part of Haraz Watershed). Journal of Range and Watershed Management, 62(4), 539-551 (In Persian).
Hejazi, S.A., 2015. Landslide hazard mapping in Goijabel of Ahar using GIS. Journal of geography and planning, 18(50), 135-152 (In Persian).
Ayalew, L., Yamagishi, H., .2005. The Application of GIS – based logistic regression for landslide susceptibility mapping in the Kakuda–Yahiko Mountains, central Japan. Geomorphology, 65, 15-31.
Kayastha, P., Dhital, M.R., DeSmedt., .2013. Application of the analytical hierarchy process (AHP) for landslide susceptibility mapping: A case study from the Tinau watershed, west Nepal. Computers & Geosciences 52, 398–408.
Feizizadeh, B., Shadman Roodposhti, M., Blaschke, T., .2014. A GIS-based extended fuzzy multi-criteria evaluation for landslide susceptibility mapping. Computers & Geosciences, 73, 208–221.
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- Souri, S., Baharvand, S., Ahmadian moghadam, R., Dehban, M., 2013.Landslide hazard zoning using analytical hierarchy process. Journal of applied geology, 9, 101-110. (In Persian)
- Feizizadeh, B.,Blaschke,T., 2013. GIS-multicriteria decision analysis for landslide susceptibility mapping: comparing three methods for the Urmia Lake basin Iran. Natural Hazard, 65, 2105–2128.
- Komak Panah, A., Montazerolghaem S., and Chodani, A., 1992. Landslide and a Review on Landslide in Iran. Published by International Institute of Earthquake Engineering and Seismology, Tehran, Iran. (In Persian).
- Sarvati, M.R., Nosrati, K., Hasanvandi, S., Mirbagheri, B., 2014. Prediction of Landslide Hazard in Sikan River Basin Using Logistic Regression Model, 67(1), 17-29 (In Persian).
- Sangchini Karimi, E., Ownegh, M., Sadoddin, A., 2013. Assessment of landslide hazard, risk in Chehel - Chay Watershed, Golestan Province, Iran. Watershed management research, 98, 74-84. (In Persian).
- Haeri, S.M., Samiei, A.H., 1996. New zoning approach of slope areas against the landslide risk with emphasis on zoning of Mazandaran province, Earth Sciences, 6, 2-15. (In Persian).
- Shadfar, P., Yamani, M., Namaki, M., 2005. Landslide hazard zonation using information value models, surface density, and LNRE in the Chalker field. Journal of Water and Watershed, 3, 62-68. (In Persian).
- Feiznia, S., Kalarstaghi, A., Ahmadi, H., Safaei, M., 2002. Investigating the factors affecting the occurrence of landslides and zoning of the land slide risk of Shirin-rood-Dam Tajan watershed. Journal of Natural Resources of Iran, 57 (1), 3-20. (In Persian).
9. Yalcin, A., .2008. GIS-based landslide susceptibility mapping using analytical hierarchy process and bivariate statistics in Ardesen (Turkey): Comparisons of results and confirmations. Catena, 72, 1-12.
Ayalew, L., Yamagishi, H., Marui, H., Kanno, T., .2005. Landslides in Sado Island of Japan: Part II. GIS-based susceptibility mapping with comparisons of results from two methods and verifications. Engineering Geology, 81, 432– 445.
Ghodsipoor, H., 2003. Analytical Hierarchy Process (AHP). Amirkabir Publication. 4, 220p (In Persian).
Komac, M., 2006. A landslide susceptibility model using the analytical hierarchy process method and multivariate statistics in pri-alpine Slovenia. Geomorphology, 74, 17-28.
Mirnazari, J., Khezri, S., Shahabi, H., 2015. Assessment and zoning of landslide hazard sing AHP model and fuzzy logic operation in Posht tang watershed of sar pole zahab (Kermanshah province). Geography and development, 12 (37), 35-70 (In Persian).
Gee, M.D., .1991. Classification of landslide hazard zonation methods and a test of predictive capability, Landslides, Bell (ed.), Balkema, Rotterdam. pp. 947- 952.
Ohlmacher, G.C. Davis, J.C., .2003. Using multiple logistic regression and GIS technology to predict landslide hazard in Northeast Kansas, USA. Engineering Geology, 69, 331-343.
Yamani, M., Shamsipour, A., Goorabi, A., Rahmati, M., 2014. Determining landslide zones in Khoramabad-pole zaal freeway by using hierarchy analysis-fuzzy logic method. Journal of geographical sciences, 14(32), 27-44 (In Persian).
Chau, K.T., Chan, J.E., .2005. Regional bias of landslide data in generating susceptibility maps using logistic regression: Case of Hong Kong Island. Landslides, 2, 280-290.
Lee, S., Abdul Talib, J., .2005. Probabilistic landslide susceptibility and factor effect analysis. Environmental Geology, 47, 982-990.
Dymond, J.R., Ausseeil, A.G., Shepherd, J.D., Buettner, l., .2006. Validation of a Region- Wide Model of Landslide Susceptibility in the Manawatu- Wanganui Region of New Zealand. Geomorphology, 74, 70-79.
Duman, T. Y., Can, T., Gokceoglu, C., Nefeslioglu, H. A., Sonmez, H., .2006. Application of logistic regression for landslide susceptibility zoning of Cekmece Area, Istanbul, Turkey. Environmental Geology, 51, 241-256.
Lee, S., .2007. Application and verification of fuzzy algebraic operators to landslide susceptibility mapping. Environmental Geology, 52, 615-623.
Mohammady, M., Pourghasemi, H.R., Pradhan, B., .2012. Landslide susceptibility mapping at Golestan province, Iran: a comparison between frequency ratio, Dempster–Shafer, and weights-ofevidence models. Journal of Asian Earth Sciences, 61, 221–236.
Ahmadi, H., Mohammad Khan, S., Feiznia, S., Ghoddoosi. J., 2006. Landslide hazard zonation by AHP hierarchical analysis method in Taleghan basin, Natural Resources Journal. 58, 3-14 (In Persian).
Ercanoglu, M., Gokceoglu, C., .2004. Use of fuzzy relations to produce landslide susceptibility map of a landslide prone area (West Black Sea Region, Turkey). Engineering Geology, 75, 229–250.
Abedini, M., Ghasemian, B., Shirzadi, A., 2014. Modelling the Hazard of Landslides by Using Statistical Method of Logistic Regression. Geography and development Iranian journal, 37, 85-120 (In Persian).
Neuhauser, B., Terhorst, B., .2006. Landslide Susceptibility Assessment Using Weights-of- Evidence Applied to a Study Area at the Jurassic Escarpment (SW-Germany). Geomorphology, 1-13.
Mohammadi, M., Moradi, H. R., Feizenya, S., Pourghasemi, H. R., 2009. Prioritizing the factors affecting the landslide and preparing its hazard map using information value models and AHP in a part of the Haraz watershed. Journal of Geosciences, 19 (74), 27- 32 (In Persian).
Mohammadi, M., Moradi, H. R., Feizenya, S., Pourghasemi, H. R., 2009. Comparison of the Efficiency of Certainty Factor, Information Value and AHP Models in Landslide Hazard Zonation (Case study: Part of Haraz Watershed). Journal of Range and Watershed Management, 62(4), 539-551 (In Persian).
Hejazi, S.A., 2015. Landslide hazard mapping in Goijabel of Ahar using GIS. Journal of geography and planning, 18(50), 135-152 (In Persian).
Ayalew, L., Yamagishi, H., .2005. The Application of GIS – based logistic regression for landslide susceptibility mapping in the Kakuda–Yahiko Mountains, central Japan. Geomorphology, 65, 15-31.
Kayastha, P., Dhital, M.R., DeSmedt., .2013. Application of the analytical hierarchy process (AHP) for landslide susceptibility mapping: A case study from the Tinau watershed, west Nepal. Computers & Geosciences 52, 398–408.
Feizizadeh, B., Shadman Roodposhti, M., Blaschke, T., .2014. A GIS-based extended fuzzy multi-criteria evaluation for landslide susceptibility mapping. Computers & Geosciences, 73, 208–221.