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Generating Landslide Susceptibility Maps Using Mathematical Models and UAV data: The Case of Çankırı Region in Türkiye

Year 2022, Volume: 8 Issue: 1, 1 - 10, 30.06.2022
https://doi.org/10.33904/ejfe.1066040

Abstract

Landslides are natural disasters that affect not only residential areas but alos forest ecosystems. In order to determine the areas with high landslide risk and take necessary measures in risky areas, landslides susceptible should analyzed and susceptible map (LSM) should be developed in advance. In this study, a LSM was produced for two study areas with different sizes including Çankırı province and in the Ilısılık Village of Çankırı in Türkiye. Analytical Hierarchy Process (AHP) and Logistic Regression Modeling (LRM) methods were used to generate LSM based on the main factors including elevation, slope, lithology, distance to faults - streams and roads. For Çankırı province, 30 m resolution Digital Elevation Model (DEM) was used to produce the map while one-meter resolution Digital Terrain Model (DTM), generated by using Unmanned Aerial Vehicle (UAV), was used for Ilısılık Village. As a result of the study, AHP model success was calculated as 73.9% and 91.7% for Çankırı and Ilısılık, respectively, considering the previous landslides occurred in the region. On the other hand, LRM model success was 75.2% and 93.1%, respectively. It was also indicated that DTM data is advantageous to DEM data by offering a more precise and detailed usage opportunity. The sensitivity is revealed more clearly and effectively in precision planning studies such as risk mapping of natural disasters that requires special measurement in small areas.

Thanks

This study, carried out in the Department of Forest Engineering, Graduate School of Natural and Applied Sciences at Çankırı Karatekin University, is derived from Master’s Thesis

References

  • Aksüt, Abedini, M., Ghasemyan, B., Mogaddam, M.R. 2017. Landslide susceptibility mapping in Bijar city, Kurdistan Province, Iran: a comparative study by logistic regression and AHP models. Environmental Earth Sciences, 76(8): 308.
  • AFAD, 2015. Bütünleşik Tehlike Haritalarının Hazırlanması Heyelan-Kaya Düşmesi Temel Kılavuzu. Afet ve Acil Durum Yönetimi Başkanlığı, 151 s., Ankara. (In Turkish)
  • Akgun, A., Turk, N. 2010. Landslide susceptibility mapping for Ayvalik (Western Turkey) and its vicinity by multicriteria decision analysis. Environmental Earth Sciences, 61(3): 595–611.
  • 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(1-2): 15-31.
  • Brabb, E.E. 1991. The world landslide problem. Episodes, 14(1): 52-61.
  • Bugday, E., Akay, A. E. 2019. Evaluation of forest road network planning in landslide sensitive areas by GIS-based multi-criteria decision making approaches in Ihsangazi watershed, Northern Turkey. Šumarski list, 143(7-8): 325-336.
  • Çan, T., Duman, T.Y., Olgun, Ş., Çörekçioğlu, Ş., Karakaya-Gülmez, F., Elmacı, H., Hamzaçebi, S., Emre, Ö. 2013. Turkey Landslide Database. TMMOB Geographic Information Systems Congress, Proceedings Book, 1-6, Ankara.
  • Cruden, D.M. 1991. A simple definition of a landslide. Bulletin of the International Association of Engineering Geology-Bulletin de l'Association Internationale de Géologie de l'Ingénieur, 43(1): 27-29.
  • 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(2): 241-256.
  • Duman, T.Y., Çan, T., Emre, Ö. 2011. 1/1.500.000 ölçekli Türkiye Heyelan Envanteri Haritası. Maden Tetkik ve Arama Genel Müdürlüğü, Özel Yayınlar Serisi-27, Ankara, Türkiye. ISBN: 978-605-4075-84-3 (In Turkish)
  • Eker, A.M., Dikmen, M., Cambazoglu, S., Duzgun, S.H., Akgun, H. 2012. Application of Artificial Neural Network and Logistic Regression Methods to Landslide Susceptibility Mapping and Comparison of the Results for the Ulus District, Bartın. Journal of the Faculty of Engineering and Architecture of Gazi University, 27(1):163-173.
  • Emre, Ö., Duman, T.Y., Özalp, S., Elmacı, H., Olgun, Ş., Şaroğlu, F. 2013. Açıklamalı Türkiye Diri Fay Haritası. Ölçek 1:1.250.000, Maden Tetkik ve Arama Genel Müdürlüğü, Özel Yayın Serisi-30, Ankara-Türkiye. ISBN: 978-605-5310-56-1 (In Turkish)
  • Ergünay, O. 2007. Turkey's Disaster Profile. TMMOB Disaster Symposium proceedings book, 1-14, Ankara.
  • ESRI, 2018. How Cut Fill works. http://desktop.arcgis.com/en/arcmap/10.3/tools/spatial-analyst-toolbox/how-cut-fill-works.htm. (Accessed: 19.08.2021)
  • Gorsevski, P., Gessler, P.E., Foltz, R.B., Elliot, W.J. 2006. Spatial prediction of landslide hazard using logistic regression and ROC analysis. Transactions in GIS, 10(3): 395-415. Görüm, T., Gönençgil, B. 2006. Coğrafi bilgi sistemi ve istatistiksel yöntemler kullanılarak heyelan duyarlılık analizi: Melen boğazı ve yakın çevresi. Yüksek Lisans Tezi. İstanbul Üniversitesi, 150 sayfa, İstanbul. (In Turkish)
  • Hong, H., Pradhan, B., Xu, C., Tien Bui, D. 2015. Spatial prediction of landslide hazard at the Yihuang area (China) using two-class kernel logistic regression, alternating decision tree and support vector machines. Catena, 133: 266–281.
  • Hungr, O., Leroueil, S., ve Picarelli, L. 2014. The Varnes classification of landslide types, an update. Landslides, 11(2): 167-194.
  • Jaafari, A., Najafi, A., Rezaeian, J., Sattarian, A., Ghajar, I. 2015. Planning road networks in landslide-prone areas: A case study from the northern forests of Iran. Land Use Policy, 47: 198–208.
  • Jacobs, L., Dewitte, O., Poesen, J., Sekajugo, J., Nobile, A., Rossi, M., Thiery, W., Kervyn, M. 2018. Field-based landslide susceptibility assessment in a data-scarce environment: The populated areas of the Rwenzori Mountains. Natural Hazards and Earth System Sciences, 18(1): 105–124.
  • Lee, S., Pradhan, B. 2007. Landslide hazard mapping at Selangor, Malaysia using frequency ratio and logistic regression models. Landslides, 4(1): 33-41.
  • Lee, S., Sambath, T. 2006. Landslide susceptibility mapping in the Damrei Romel area, Cambodia using frequency ratio and logistic regression models. Environmental Geology, 50(6): 847-855.
  • Myronidis, D., Papageorgiou, C., Theophanous, S. 2016. Landslide susceptibility mapping based on landslide history and analytic hierarchy process (AHP). Natural Hazards, 81(1): 245-263.
  • Nefeslioğlu, H.A., San, T., Gokceoglu, C., Duman, T.Y. 2012. An assessment on the use of Terra ASTER L3A data in landslide susceptibility mapping. Int. J. Appl. Earth Obs. Geoinf. 14 (1): 40–60.
  • Niethammer, U., Rothmund, S., Schwaderer, U., Zeman, J., Joswig, M. 2011. Open source image-processing tools for low-cost UAV-based landslide investigations. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 38(1): C22.
  • Park, S., Choi, C., Kim, B., Kim, J. 2013. Landslide susceptibility mapping using frequency ratio, analytic hierarchy process, logistic regression, and artificial neural network methods at the Inje area, Korea. Environmental earth sciences, 68(5): 1443-1464.
  • Pourghasemi, H.R., Pradhan, B., Gokceoglu, C. 2012. Application of fuzzy logic and analytical hierarchy process (AHP) to landslide susceptibility mapping at Haraz watershed, Iran. Natural hazards, 63(2): 965-996.
  • Saha, A.K., Arora, M.K., Gupta, R.P., Virdi, M.L., Csaplovics, E. 2005. GIS-based route planning in landslide-prone areas. International Journal of Geographical Information Science, 19(10): 1149–1175.
  • Varnes, D.J. 1978. Slope movement types and processes. Special report, 176: 11-33.
  • WHO. 2021. Landslides. https://www.who.int/health-topics/landslides#tab=tab_1. (Accessed: 03.02.2022)
  • Yalçın, A. 2007. The Use of Analytical Hierarchy Process and GIS in Production of Landslide Susceptibility Maps. J. Fac.Eng.Arch. Selcuk Univ, 22 (3): 1-14.
  • Yalçın, 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): 1–12.
  • Yalçın, A., Reis, S., Aydinoglu, A. C., ve Yomralioglu, T. 2011. A GIS-based comparative study of frequency ratio, analytical hierarchy process, bivariate statistics and logistics regression methods for landslide susceptibility mapping in Trabzon, NE Turkey. Catena, 85(3): 274–287.
Year 2022, Volume: 8 Issue: 1, 1 - 10, 30.06.2022
https://doi.org/10.33904/ejfe.1066040

Abstract

References

  • Aksüt, Abedini, M., Ghasemyan, B., Mogaddam, M.R. 2017. Landslide susceptibility mapping in Bijar city, Kurdistan Province, Iran: a comparative study by logistic regression and AHP models. Environmental Earth Sciences, 76(8): 308.
  • AFAD, 2015. Bütünleşik Tehlike Haritalarının Hazırlanması Heyelan-Kaya Düşmesi Temel Kılavuzu. Afet ve Acil Durum Yönetimi Başkanlığı, 151 s., Ankara. (In Turkish)
  • Akgun, A., Turk, N. 2010. Landslide susceptibility mapping for Ayvalik (Western Turkey) and its vicinity by multicriteria decision analysis. Environmental Earth Sciences, 61(3): 595–611.
  • 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(1-2): 15-31.
  • Brabb, E.E. 1991. The world landslide problem. Episodes, 14(1): 52-61.
  • Bugday, E., Akay, A. E. 2019. Evaluation of forest road network planning in landslide sensitive areas by GIS-based multi-criteria decision making approaches in Ihsangazi watershed, Northern Turkey. Šumarski list, 143(7-8): 325-336.
  • Çan, T., Duman, T.Y., Olgun, Ş., Çörekçioğlu, Ş., Karakaya-Gülmez, F., Elmacı, H., Hamzaçebi, S., Emre, Ö. 2013. Turkey Landslide Database. TMMOB Geographic Information Systems Congress, Proceedings Book, 1-6, Ankara.
  • Cruden, D.M. 1991. A simple definition of a landslide. Bulletin of the International Association of Engineering Geology-Bulletin de l'Association Internationale de Géologie de l'Ingénieur, 43(1): 27-29.
  • 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(2): 241-256.
  • Duman, T.Y., Çan, T., Emre, Ö. 2011. 1/1.500.000 ölçekli Türkiye Heyelan Envanteri Haritası. Maden Tetkik ve Arama Genel Müdürlüğü, Özel Yayınlar Serisi-27, Ankara, Türkiye. ISBN: 978-605-4075-84-3 (In Turkish)
  • Eker, A.M., Dikmen, M., Cambazoglu, S., Duzgun, S.H., Akgun, H. 2012. Application of Artificial Neural Network and Logistic Regression Methods to Landslide Susceptibility Mapping and Comparison of the Results for the Ulus District, Bartın. Journal of the Faculty of Engineering and Architecture of Gazi University, 27(1):163-173.
  • Emre, Ö., Duman, T.Y., Özalp, S., Elmacı, H., Olgun, Ş., Şaroğlu, F. 2013. Açıklamalı Türkiye Diri Fay Haritası. Ölçek 1:1.250.000, Maden Tetkik ve Arama Genel Müdürlüğü, Özel Yayın Serisi-30, Ankara-Türkiye. ISBN: 978-605-5310-56-1 (In Turkish)
  • Ergünay, O. 2007. Turkey's Disaster Profile. TMMOB Disaster Symposium proceedings book, 1-14, Ankara.
  • ESRI, 2018. How Cut Fill works. http://desktop.arcgis.com/en/arcmap/10.3/tools/spatial-analyst-toolbox/how-cut-fill-works.htm. (Accessed: 19.08.2021)
  • Gorsevski, P., Gessler, P.E., Foltz, R.B., Elliot, W.J. 2006. Spatial prediction of landslide hazard using logistic regression and ROC analysis. Transactions in GIS, 10(3): 395-415. Görüm, T., Gönençgil, B. 2006. Coğrafi bilgi sistemi ve istatistiksel yöntemler kullanılarak heyelan duyarlılık analizi: Melen boğazı ve yakın çevresi. Yüksek Lisans Tezi. İstanbul Üniversitesi, 150 sayfa, İstanbul. (In Turkish)
  • Hong, H., Pradhan, B., Xu, C., Tien Bui, D. 2015. Spatial prediction of landslide hazard at the Yihuang area (China) using two-class kernel logistic regression, alternating decision tree and support vector machines. Catena, 133: 266–281.
  • Hungr, O., Leroueil, S., ve Picarelli, L. 2014. The Varnes classification of landslide types, an update. Landslides, 11(2): 167-194.
  • Jaafari, A., Najafi, A., Rezaeian, J., Sattarian, A., Ghajar, I. 2015. Planning road networks in landslide-prone areas: A case study from the northern forests of Iran. Land Use Policy, 47: 198–208.
  • Jacobs, L., Dewitte, O., Poesen, J., Sekajugo, J., Nobile, A., Rossi, M., Thiery, W., Kervyn, M. 2018. Field-based landslide susceptibility assessment in a data-scarce environment: The populated areas of the Rwenzori Mountains. Natural Hazards and Earth System Sciences, 18(1): 105–124.
  • Lee, S., Pradhan, B. 2007. Landslide hazard mapping at Selangor, Malaysia using frequency ratio and logistic regression models. Landslides, 4(1): 33-41.
  • Lee, S., Sambath, T. 2006. Landslide susceptibility mapping in the Damrei Romel area, Cambodia using frequency ratio and logistic regression models. Environmental Geology, 50(6): 847-855.
  • Myronidis, D., Papageorgiou, C., Theophanous, S. 2016. Landslide susceptibility mapping based on landslide history and analytic hierarchy process (AHP). Natural Hazards, 81(1): 245-263.
  • Nefeslioğlu, H.A., San, T., Gokceoglu, C., Duman, T.Y. 2012. An assessment on the use of Terra ASTER L3A data in landslide susceptibility mapping. Int. J. Appl. Earth Obs. Geoinf. 14 (1): 40–60.
  • Niethammer, U., Rothmund, S., Schwaderer, U., Zeman, J., Joswig, M. 2011. Open source image-processing tools for low-cost UAV-based landslide investigations. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 38(1): C22.
  • Park, S., Choi, C., Kim, B., Kim, J. 2013. Landslide susceptibility mapping using frequency ratio, analytic hierarchy process, logistic regression, and artificial neural network methods at the Inje area, Korea. Environmental earth sciences, 68(5): 1443-1464.
  • Pourghasemi, H.R., Pradhan, B., Gokceoglu, C. 2012. Application of fuzzy logic and analytical hierarchy process (AHP) to landslide susceptibility mapping at Haraz watershed, Iran. Natural hazards, 63(2): 965-996.
  • Saha, A.K., Arora, M.K., Gupta, R.P., Virdi, M.L., Csaplovics, E. 2005. GIS-based route planning in landslide-prone areas. International Journal of Geographical Information Science, 19(10): 1149–1175.
  • Varnes, D.J. 1978. Slope movement types and processes. Special report, 176: 11-33.
  • WHO. 2021. Landslides. https://www.who.int/health-topics/landslides#tab=tab_1. (Accessed: 03.02.2022)
  • Yalçın, A. 2007. The Use of Analytical Hierarchy Process and GIS in Production of Landslide Susceptibility Maps. J. Fac.Eng.Arch. Selcuk Univ, 22 (3): 1-14.
  • Yalçın, 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): 1–12.
  • Yalçın, A., Reis, S., Aydinoglu, A. C., ve Yomralioglu, T. 2011. A GIS-based comparative study of frequency ratio, analytical hierarchy process, bivariate statistics and logistics regression methods for landslide susceptibility mapping in Trabzon, NE Turkey. Catena, 85(3): 274–287.
There are 32 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Research Articles
Authors

Abdullah Özçelik 0000-0002-8625-5447

Ender Buğday 0000-0002-3054-1516

Early Pub Date June 27, 2022
Publication Date June 30, 2022
Published in Issue Year 2022 Volume: 8 Issue: 1

Cite

APA Özçelik, A., & Buğday, E. (2022). Generating Landslide Susceptibility Maps Using Mathematical Models and UAV data: The Case of Çankırı Region in Türkiye. European Journal of Forest Engineering, 8(1), 1-10. https://doi.org/10.33904/ejfe.1066040

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The works published in European Journal of Forest Engineering (EJFE) are licensed under a  Creative Commons Attribution-NonCommercial 4.0 International License.