Landslide Susceptibility Mapping of Samsun (Turkey) Province Using Frequency Ratio and AHP Methods
Year 2021,
Volume: 3 Issue: 1, 24 - 30, 28.05.2021
Aslan Cihat Başara
,
Mehmet Emin Tabar
,
Yasemin Şişman
Abstract
Landslide susceptibility mapping is of critical importance to identify landslide-prone areas to reduce future landslides, casualties, and infrastructural damages. In this study, the Landslide Susceptibility Map of Samsun (Turkey) was produced. The Slope, elevation, land use, soil, proximity to stream networks and lakes, proximity to fault lines were selected as parameters. All parameters were divided as the sub classes according to their properties. The Frequency Ratio method was applied to determine the relationship between the parameters and the landslide events. Paired comparison matrices were created to determine the weights of the parameters using the Analytical Hierarchy method. The weighted overlay operation was applied to the classified and weighted map data using ArcGIS program. As a result, the Landslide Susceptibility Map was produced as divided to 5 classes.
References
- AFAD (2020). T.C. Afet ve Acil Durum Yönetimi Başkanlığı, Samsun Bölge Müdürlüğü.
- AFAD (2014). Açıklamalı Afet Yönetimi Terimleri Sözlüğü. TC Başbakanlık Afet ve Acil Durum Yönetimi Başkanlığı Deprem Dairesi Başkanlığı, Ankara.
- Aleotti P & Chowdhury R (1999). Landslide hazard assessment: summary review and new perspectives. Bulletin of Engineering Geology and the Environment, 58(1), 21-44.
- Baeza C & Corominas J (2001). Assessment of shallow landslide susceptibility by means of multivariate statistical techniques. Earth Surface Processes and Landforms. The Journal of the British Geomorphological Research Group, 26:12, 1251-1263.
- Basara A C, Tabar M E & Sisman Y (2020). GIS-Based Landslide Susceptibility Mapping Using Frequency Ratio and AHP Methods. Intercontinental Geoinformation Days (IGD), 223-226, Mersin, Turkey.
- Elevli S, Sisman Y & Uzgoren N (2012). Statistical Evaluation of Landslides in Samsun Region, Turkey.
- Gökçeoğlu C & Ercanoğlu M (2001). ncertainties on the parameters emloyed in preparation of landslide susceptibility maps. Bulletin for Earth Sciences, 22(23), 189-206.
- Guzzetti F, Ardizzone F, Cardinali M, Rossi M & Valigi D (2009). Landslide volumes and landslide mobilization rates in Umbria, central Italy. Earth and Planetary Science Letters, 279(3-4), 222-229.
- Guzzetti F, Carrara A, Cardinali M & Reichenbach, P. (1999). Landslide hazard evaluation: a review of current techniques and their application in a multi-scale study, Central Italy. Geomorphology, 31(1-4), 181-216.
- Ildır B (1995). Distribution of Landslides in Turkey and Practices Regarding Disasters Law. National Landslide Symposium Proceedings Book, Sakarya, 1-9.
- Karsli F, Atasoy, M, Yalcin, A, Reis S, Demir O & Gokceoglu, C. (2009). Effects of land-use changes on landslides in a landslide-prone area (Ardesen, Rize, NE Turkey). Environmental monitoring and assessment, 156(1), 241-255.
- Kavas E (2009). Analitik hiyerarşik süreç yöntemiyle İzmir ilinde heyelan duyarlılığının coğrafi bilgi sistemleri tabanlı incelenmesi. TMMOB Coğrafi Bilgi Sistemleri Kongresi, İzmir.
- Kavzoglu T, Şahi E K & Çölkesen İ (2012). Assessment of Landslide Susceptibility Using Regression Trees: The Case of Trabzon Province. Harita Dergisi, 147(3), 21-33.
- Lee S & Talib J A (2005). Probabilistic landslide susceptibility and factor effect analysis. Environmental Geology, 47:7, 982-990
- Luzi L & Pergalani F (1999). Slope Instability in Static and Dynamic Conditions for Urban Planning: The “Oltre Po Pavese” Case History (Region Lombardia-Italy). National Hazard, 20, 57-82.
- Malczewski J (1999). GIS and multicriteria decision analysis: John Wiley & Sons.
- Ozturk D & Batuk F (2010). Analytic Hierarcy Process for Spatial Decision Making. SIGMA Journal of Engineering and Natural Science, 28, 124-137.
- Reduction D R (2009). UNISDR terminology on disaster risk reduction: Bangkok.
- Sisman Y & Kirici U (2019). Landslide Monitoring with Fuzzy Logic, A Case Study. ICOCEM, Trabzon, Turkey.
- Tabar M E & Sisman Y (2020). Creating a Land Valuation Model by Fuzzy Logic. Turkey Land Management Journal, 2(1), 18-24.
- Tetik Biçer Ç (2017). A semi-quantitative evaluation of landslide risk mapping. Doctoral Thesis. Hacettepe University, Institute of Science, Geological Engineering, Ankara, 353 p (in Turkish).
- Tombus F E & Ozulu M (2005). A New Approach In Determining of Erosion Risk with Use of Remote Sensing and Geographic Information Systems: Case Of Çorum Province. TMMOB Chamber of Survey Engineers National Geographic Information Systems 30 October –02 November 2007, KTÜ, Trabzon.
- Varnes D J (1984), Landslide hazard zonation: a review of principles and practice. Commission of Landslides of the IAEG, UNESCO, Natural Hazards No. 3, 61 pp.
- Wachal, D. J. and Hudak, P. F., (2000). Mapping landslide susceptibility in Travis County, Texas, USA, GeoJournal, 51 (3), 245-253.)
- Wind Y & Saaty T L (1980). Marketing applications of the analytic hierarchy process. Management science, 26(7), 641-658.
Landslide Susceptibility Mapping of Samsun (Turkey) Province Using Frequency Ratio and AHP Methods
Year 2021,
Volume: 3 Issue: 1, 24 - 30, 28.05.2021
Aslan Cihat Başara
,
Mehmet Emin Tabar
,
Yasemin Şişman
Abstract
Landslide susceptibility mapping is of critical importance to identify landslide-prone areas to reduce future landslides, casualties, and infrastructural damages. In this study, the Landslide Susceptibility Map of Samsun (Turkey) was produced. The Slope, elevation, land use, soil, proximity to stream networks and lakes, proximity to fault lines were selected as parameters. All parameters were divided as the sub classes according to their properties. The Frequency Ratio method was applied to determine the relationship between the parameters and the landslide events. Paired comparison matrices were created to determine the weights of the parameters using the Analytical Hierarchy method. The weighted overlay operation was applied to the classified and weighted map data using ArcGIS program. As a result, the Landslide Susceptibility Map was produced as divided to 5 classes.
References
- AFAD (2020). T.C. Afet ve Acil Durum Yönetimi Başkanlığı, Samsun Bölge Müdürlüğü.
- AFAD (2014). Açıklamalı Afet Yönetimi Terimleri Sözlüğü. TC Başbakanlık Afet ve Acil Durum Yönetimi Başkanlığı Deprem Dairesi Başkanlığı, Ankara.
- Aleotti P & Chowdhury R (1999). Landslide hazard assessment: summary review and new perspectives. Bulletin of Engineering Geology and the Environment, 58(1), 21-44.
- Baeza C & Corominas J (2001). Assessment of shallow landslide susceptibility by means of multivariate statistical techniques. Earth Surface Processes and Landforms. The Journal of the British Geomorphological Research Group, 26:12, 1251-1263.
- Basara A C, Tabar M E & Sisman Y (2020). GIS-Based Landslide Susceptibility Mapping Using Frequency Ratio and AHP Methods. Intercontinental Geoinformation Days (IGD), 223-226, Mersin, Turkey.
- Elevli S, Sisman Y & Uzgoren N (2012). Statistical Evaluation of Landslides in Samsun Region, Turkey.
- Gökçeoğlu C & Ercanoğlu M (2001). ncertainties on the parameters emloyed in preparation of landslide susceptibility maps. Bulletin for Earth Sciences, 22(23), 189-206.
- Guzzetti F, Ardizzone F, Cardinali M, Rossi M & Valigi D (2009). Landslide volumes and landslide mobilization rates in Umbria, central Italy. Earth and Planetary Science Letters, 279(3-4), 222-229.
- Guzzetti F, Carrara A, Cardinali M & Reichenbach, P. (1999). Landslide hazard evaluation: a review of current techniques and their application in a multi-scale study, Central Italy. Geomorphology, 31(1-4), 181-216.
- Ildır B (1995). Distribution of Landslides in Turkey and Practices Regarding Disasters Law. National Landslide Symposium Proceedings Book, Sakarya, 1-9.
- Karsli F, Atasoy, M, Yalcin, A, Reis S, Demir O & Gokceoglu, C. (2009). Effects of land-use changes on landslides in a landslide-prone area (Ardesen, Rize, NE Turkey). Environmental monitoring and assessment, 156(1), 241-255.
- Kavas E (2009). Analitik hiyerarşik süreç yöntemiyle İzmir ilinde heyelan duyarlılığının coğrafi bilgi sistemleri tabanlı incelenmesi. TMMOB Coğrafi Bilgi Sistemleri Kongresi, İzmir.
- Kavzoglu T, Şahi E K & Çölkesen İ (2012). Assessment of Landslide Susceptibility Using Regression Trees: The Case of Trabzon Province. Harita Dergisi, 147(3), 21-33.
- Lee S & Talib J A (2005). Probabilistic landslide susceptibility and factor effect analysis. Environmental Geology, 47:7, 982-990
- Luzi L & Pergalani F (1999). Slope Instability in Static and Dynamic Conditions for Urban Planning: The “Oltre Po Pavese” Case History (Region Lombardia-Italy). National Hazard, 20, 57-82.
- Malczewski J (1999). GIS and multicriteria decision analysis: John Wiley & Sons.
- Ozturk D & Batuk F (2010). Analytic Hierarcy Process for Spatial Decision Making. SIGMA Journal of Engineering and Natural Science, 28, 124-137.
- Reduction D R (2009). UNISDR terminology on disaster risk reduction: Bangkok.
- Sisman Y & Kirici U (2019). Landslide Monitoring with Fuzzy Logic, A Case Study. ICOCEM, Trabzon, Turkey.
- Tabar M E & Sisman Y (2020). Creating a Land Valuation Model by Fuzzy Logic. Turkey Land Management Journal, 2(1), 18-24.
- Tetik Biçer Ç (2017). A semi-quantitative evaluation of landslide risk mapping. Doctoral Thesis. Hacettepe University, Institute of Science, Geological Engineering, Ankara, 353 p (in Turkish).
- Tombus F E & Ozulu M (2005). A New Approach In Determining of Erosion Risk with Use of Remote Sensing and Geographic Information Systems: Case Of Çorum Province. TMMOB Chamber of Survey Engineers National Geographic Information Systems 30 October –02 November 2007, KTÜ, Trabzon.
- Varnes D J (1984), Landslide hazard zonation: a review of principles and practice. Commission of Landslides of the IAEG, UNESCO, Natural Hazards No. 3, 61 pp.
- Wachal, D. J. and Hudak, P. F., (2000). Mapping landslide susceptibility in Travis County, Texas, USA, GeoJournal, 51 (3), 245-253.)
- Wind Y & Saaty T L (1980). Marketing applications of the analytic hierarchy process. Management science, 26(7), 641-658.