Abstract
In Turkey, landslide phenomenon is one of the most important natural hazards. Due to landslide occurrence, several landforms and man-made structures are adversely affected and may cause many injuries and loss of life. In this context, landslide susceptibility assessment is an important task to determine susceptible areas to landslide occurrence. Especially, several dam reservoir areas in Turkey are threatened by landslide phenomena. For this reason, in this study, a dam reservoir area, located in the northern part of Turkey, was selected and investigated in the point of view of landslide susceptibility assessment. A landslide susceptibility assessment for Kurtun Dam reservoir area (Gumushane, North Turkey) was carried out by geographical information system (GIS)-based statistical and deterministic models. For this purpose, logistic regression (LR) and stability index mapping (SINMAP) methodologies were applied. In this context, eight contributing factors such as altitude, lithology, slope gradient, slope aspect, distance to drainage, distance to lineament, stream power index (SPI) and topographical wetness index (TWI) were considered. After assessment of these parameters by LR and SINMAP methods in a GIS environment, two landslide susceptibility maps were obtained. Then, the produced maps were analyzed for validation purpose. For this purpose, area under curvature (AUC) approach was used. At the end of this process, the AUC values of 0.73 and 0.65 were found for LR and SINMAP models, respectively. For the performance of the SINMAP model, statistical results produced by the model were also considered. In this context, landslide density of the stability index (SI) classes were taken into account, and it was determined that 89.5 % of the landslides fall into lower and upper threshold classes which almost correspond to moderate and high susceptibility classes. These two validation values indicate that the accuracy of landslide susceptibility maps is acceptable, and the maps are feasible for further natural hazard management affairs in the area.
Similar content being viewed by others
References
Akgun A (2011) Assessment of possible damaged areas due to landslide-induced waves at a constructed reservoir using empirical approaches: Kurtun (North Turkey) dam reservoir area. Nat Hazards Earth Syst Sci 11:1341–1350
Akgun A (2012) A comparison of landslide susceptibility maps produced by logistic regression, multicriteria decision and likelihood ratio methods: case study at Izmir, Turkey. Landslides 9(1):93–106
Akgun A, Bulut F (2007) GIS-based landslide susceptibility for Arsin-Yomra (Trabzon, North Turkey) region. Environ Geol 51:1377–1387
Akgun A, Turk N (2010) Landslide susceptibility mapping for ayvalik (Western Turkey) and its vicinity by multicriteria decision analysis. Environ Earth Sci 61:595–611
Akgun A, Dag S, Bulut F (2008) Landslide susceptibility mapping for a landslide-prone area (findikli, ne of turkey) by likelihood-frequency ratio and weighted linear combination models. Environ Geol 54:1127–1143
Akgun A, Kıncal C, Pradhan B (2012a) Application of remote sensing data and GIS for landslide risk assessment as an environmental threat to Izmir city (west Turkey). Environ Monit Assess 184(9):5453–5470
Akgun A, Sezer EA, Nefeslioglu HA, Gokceoglu C, Pradhan B (2012b) An easy-to-use MATLAB program (MamLand) for the assessment of landslide susceptibility using a Mamdani fuzzy algorithm. Comput Geosci 38(1):23–34
Althuwaynee OF, Pradhan B, Lee S (2012) Application of an evidential belief function model in landslide susceptibility mapping. Comput Geosci 44:120–135
Althuwaynee OF, Pradhan B, Park HJ, Lee JH (2014) A novel ensemble bivariate statistical evidential belief function with knowledge-based analytical hierarchy process and multivariate statistical logistic regression for landslide susceptibility mapping. Catena 114:21–36
Anderson MG, Lloyd DM (1991) Using a combined slope hydrology-stability model to develop cut slope design charts. Proc Inst Civ Eng 91:705–718
ASTM D2216: test methods for laboratory determination of water (moisture) content of soil and rock mass
Atkinson PM, Massari R (1998) Generalized linear modelling of susceptibility to landsliding in the central Appennines, Italy. Comput Geosci 24(4):373–385
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
Bai SB, Wang J, Lu GN, Zhou PG, Hou SS, Xu SN (2010) GIS-based logistic regression for landslide susceptibility mapping of the Zhongxian segment in the three Gorges area, China. Geomorphology 23–31
Baum, RL, Savage, WZ, Godt, JW (2002) TRIGRS-A fortran program for transient rainfall infiltration and grid-based regional slope-stability analysis: U.S. geological survey open-file report 02–0424, 61 p, http://pubs.usgs.gov/of/2002/ofr-02-424/
Bernknopf RL, Cambell RH, Brookshire DS, Shapiro CD (1988) A probabilistic approach to landslide hazard mapping in Cincinnati, Ohio, with applications for economic evaluation. Bull Int Assoc Eng Geol 25:39–56
Beven KJ, Kirkby MJ (1979) A physically based, variable contributing area model of basin hydrology. Hydrol Sci Bull 24:43–69
Butler DR, Walsh SJ (1990) Lithologic, structural and topographic influences on snow-avalanche path location, Eastern Glacier National Park, Montana. Ann Assoc Am Geogr 80(3):362–378
Can T, Nefeslioglu HA, Gokceoglu C, Sonmez H, Duman TY (2005) Susceptibility assessment of shallow earthflows triggered by heavy rainfall at three subcatchments by logistic regression analyses. Geomorphology 72:250–271
Capparelli G, Versace P (2011) FLaIR and SUSHI: two mathematical models for early warning systems for rainfall induced landslides. Landslides 8:67–79
Carrara A (1983) Multivariate models for landslide hazard evaluation. Math Geol 15(3):403–426
Carrara A, Cardinali M, Guzzetti F (1992) Uncertainty in assessing landslide hazard and risk. ITC J 2:172–183
Carrara A, Cardinali M, Guzetti F, Reichenbach P (1995) GIS-based techniques for mapping landslide hazard. http://deis158.deis.unibo.it
Castellanos Abella EA, Van Westen CJ (2007) Qualitative landslide susceptibility assessment by multicriteria analysis: a case study from San Antonio del Sur, Guantanamo, Cuba. Geomorphology 94(3–4):453–466
Ceryan S, Zorlu K, Gokceoglu C, Temel A (2008) The use of cation packing index for characterizing the weathering degree of granitic rocks. Eng Geol 98:60–74
Chacon J, Irigaray C, Fernandez T, El Hamdouni R (2006) Engineering geology maps: landslides and geographical information systems. Bull Eng Geol Environ 65:341–411
Clark WAV, Hosking PL (1986) Statistical methods for geographers. Wiley, New York
Clerici A, Perego S, Tellini C, Vescovi P (2002) A procedure for landslide susceptibility zonation by the conditional analysis method. Geomorphology 48:349–364
Clerici A, Perego S, Tellini C, Vescovi P (2006) A GIS-based automated procedure for landslide susceptibility mapping by the conditional analysis method: the Baganza valley case study (Italian Northern Apennines). Environ Geol 50:941–961
Conforti M, Pascale S, Robustelli G, Sdao F (2014) Evaluation of prediction capability of the artificial neural networks for mapping landslide susceptibility in the Turbolo River catchment (northern Calabria, Italy). Catena 113:236–250
Conoscenti C, Di Maggio C, Rotigliano E (2008) Soil erosion susceptibility assessment and validation using a geostatistical multivariate approach: a test in Southern Sicily. Nat Hazards 46(3):287–305
Conrad O (2002) Digitales Gelande-modell (DiGeM) terrain analysis software. http://www.geogr.unigoettingen.de/pg/saga/digem. Accessed 18.04.06
Dagdelenler G, Nefeslioglu HA, Gokceoglu C (2015) Modification of seed cell sampling strategy for landslide susceptibility mapping: an application from the eastern part of the Gallipoli Peninsula (Canakkale, Turkey). Bull Eng Geol Environ. doi:10.1007/s10064-015-0759-0
Dai FC, Lee CF (2002) Landslide characteristics and slope instability modelling using GIS, Lantau Island, Hong Kong. Geomorphology 42:213–228
Demir G, Aytekin M, Akgun A, İkizler SB, Tatar O (2013) A comparison of landslide susceptibility mapping of the eastern part of the north Anatolian fault zone (Turkey) by likelihood-frequency ratio and analytic hierarchy process methods. Nat Hazards 65:1481–1506
Dietrich, WE, Montgomery DR (1998) SHALSTAB: a digital terrain model for mapping shallow landslide potential. Technical Report. Corvallis, OR: National Council of the Paper Industry for Air and Stream Improvement, 26 p
Duman TY, Can T, Emre O, Kecer M, Dogan A, Ates S, Durmaz S (2005) Landslide inventory of Northwestern Anatolia. Eng Geol 77:99–114
Egan JP (1975) Signal detection theory and ROC analysis, Series in Cognition and Perception. Academic Press, New York
Ercanoglu M, Gokceoglu C (2002) Assessment of landslide susceptibility for a landslide-prone area (north of Yenice, NW Turkey) by fuzzy approach. Environ Geol 41:720–730
Ermini L, Filippo C, Casagli N (2005) Artificial neural networks applied to landslide susceptibility assessment. Geomorphology 66:327–343
Ewen JP (2000) SHETRAN: distributed river basin flow and transport modeling system. J Hydrol Eng 5:250–258
General Directorate of Mineral Research and Exploration (MTA) (2005). Geological map of Turkey,1,25.000-scaled Gumushane Sheet
Gokceoglu C, Sonmez H, Nefeslioglu HA, Duman TY, Can T (2005) The 17 March 2005 Kuzulu landslide (Sivas, Turkey) and landslide-susceptibility map of its near vicinity. Eng Geol 81:65–83
Gorsevski PV, Gessler PE, Foltz RB, Elliot WJ (2006) Spatial prediction of landslide hazard using logistic regression and ROC analysis. Trans GIS 10(3):395–415
Gorum T, Gonencgil B, Gokceoglu C, Nefeslioglu HA (2008) Implementation of reconstructed geomorphologic units in landslide susceptibility mapping: the Melen Gorge (NW Turkey). Nat Hazards 46:323–351
Guven IH (1993) 1: 250.000 scaled geological and metallogenical map of the Eastern Black Sea Region, MTA Report (in Turkish, unpublished)
Guzetti F, Carrarra A, Cardinali M, Reichenbach P (1999) Landslide hazard evaluation: a review of current techniques and their application in a multiscale study, Central Italy. Geomorphology 31:181–216
Hammond C, Hall D E, Miller S, Swetik P (1992) Level I stability analysis (LISA) documentation for version 2.0: U.S. Department of Agriculture, Forest Service, Intermountain Research Station; General Technical Report INT-285, Ogden, UT, 190 p
Haneberg WC (2004) A rational probabilistic method for spatially distributed landslide hazard assessment. Environ Eng Geosci 10:27–43
Hosmer DW, Lomeshow S (2000) Applied logistic regression, 2nd edn. Wiley, New York
Ildir B (1995) Türkiyede heyelanlarin dagilimi ve afetler yasası ile ilgili uygulamalar. In: Onalp A (ed) Proceedings of the 2nd National Landslide Symposium, Turkey, Sakarya University, pp 1–9
Kıncal C, Akgun A, Koca MY (2009) Landslide susceptibility assessment in the Izmir (West Anatolia, Turkey) city center and its near vicinity by the logistic regression method. Environ Earth Sci 59:745–756
Lee S (2005) Application of logistic regression model and its validation for landslide susceptibility mapping using GIS and remote sensing data. Int J Remote Sens 26:1477–1491
Lee S, Min K (2001) Statistical analysis of landslide susceptibility at Yongin, Korea. Environ Geol 40:1095–1113
Lee S, Ryu JH, Lee MJ, Won JS (2006) The application of artificial neural networks to landslide susceptibility mapping at Janghung, Korea. Math Geol 38(2):199–219
Menard S (1995) Applied logistic regression analysis. Sage university paper series on quantitative applications in social sciences, vol. 106. Thousand Oaks, California
Montgomery DR, Dietrich WE (1994) A physically based model for the topographic control on shallow landsliding. Water Resour Res 30(4):1153–1171
Moore ID, Grayson RB, Ladson AR (1991) Digital terrain modeling: a review of hydrological, geomorphological and biological applications. Hydrol Process 13(4):305–320
Moore ID, Lewis A, Gallant JC (1993) Terrain attributes: estimation methods and scale effects. In: Jakeman AJ, Beek MJ, McAleer MJ (eds) Modelling change in environmental systems. Wiley, London
Nefeslioglu AH, Duman TY, Durmaz S (2008a) Landslide susceptibility mapping for a part of tectonic Kelkit Valley (Eastern Black Sea region of Turkey). Geomorphology 94(3):401–418
Nefeslioglu HA, Gokceoglu C, Sonmez H (2008b) An assessment on the use of logistic regression and artificial neural networks with different sampling strategies for the preparation of landslide susceptibility maps. Eng Geol 97(3–4):171–191
Nefeslioglu HA, Sezer E, Gokceoglu C, Bozkir AS, Duman TY (2010) Assessment of landslide susceptibility by decision trees in the metropolitan area of Istanbul, Turkey. Math Probl Eng 1–15
Nefeslioglu HA, Gokceoglu C, Sonmez H, Gorum T (2011) Mediumscale hazard mapping for shallow landslide initiation: the Buyukkoy catchment area (Cayeli, Rize, Turkey). Landslides 8(4):459–483
Nefeslioglu AH, Sezer EA, Gokceoglu C, Ayas Z (2013) A modified analytical hierarchy process (M-AHP) approach for decision support systems in natural hazard assessments. Comput Geosci 59:1–8
O’Callaghan JF, Mark DM (1984) The extraction of drainage networks from digital elevation data. Comput Vision Graph Image Process 28(3):323–344
O’Loughlin EM (1986) Prediction of surface saturation zones in natural catchments by topographic analysis. Water Resour Res 30(4):1153–1171
Ohlmacher CG, Davis CJ (2003) Using multiple regression and GIS technology to predict landslide hazard in northeast Kansas, USA. Eng Geol 69:331–343
Osna T, Sezer EA, Akgun A (2014) Geofis: an integrated tool for the assessment of landslide susceptibility. Comput Geosci 66:20–30
Pack RT, Tarboton DG, Goodwin CN (1998) Terrain stability mapping with SINMAP, technical description and users guide for version 1.00. Report number 4114–0, Terratech Consulting Ltd., Salmon Arm
Paulin LG, Bursik M (2009) Logisnet: a tool for multimethod, multiple soil layers slope stability analysis. Comput Geosci 35(5):1007–1016
Pourghasemi HR, Pradhan B, Gokceoglu C (2012) Application of fuzzy logic and analytical hierarchy process (AHP) to landslide susceptibility mapping at Haraz watershed, Iran. Nat Hazards 63:965–996
Pradhan B, Youssef AM (2009) Manifestation of remote sensing data and GIS on landslide hazard analysis using spatial-based statistical models. Arab J Geosci 3(3):319–326
Pradhan B, Sezer EA, Gokceoglu C, Buchroithner MF (2010) Landslide susceptibility mapping by neuro-fuzzy approach in a landslide prone area (Cameron Highland, Malaysia). IEEE Trans Geosci Remote Sens 48(12):4164–4177
Roodposhti MS, Rahimi S, Beglou MJ (2013) PROMETHEE II and fuzzy AHP: an enhanced GIS-based landslide susceptibility mapping. Nat Hazards 73(1):77–95
Safaei M, Omar H, Huat BK, Yousuf ZBM, Ghiasi V (2011) Deterministic rainfall induced landslide approaches, advantage and limitation. Electron J Geotech Eng 16:1619–1650
Schuster RL, Fleming RW (1986) Economic losses and fatalities due to landslides. Bull Assoc Eng Geol 23:11–28
Sezer EA, Pradhan B, Gokceoglu C (2011) Manifestation of an adaptive neuro-fuzzy model on landslide susceptibility mapping: Klang valley, Malaysia. Expert Syst Appl 38(7):8208–8219
Shaw SC, Johnson DH (1995) Slope morphology model derived from digital elevation data. Northwest Arc/Info Users Conference, Coeur d’Alene
Simoni S, Zanotti F, Bertoldi G, Rigon R (2007) Modelling the probability of occurrence of shallow landslides and channelized debris flows using GEOtop-FS. Hyrdrological Process 22:532–545
Soeters R, Van Westen, CJ (1996) Slope instability recognition analysis and zonation. In: Turner KT, Schuster RL (Eds) Landslides: Investigation and Mitigation. Transportation Research Board National Research Council, Washington, DC, pp. 129–177, Special Report No. 247
Suzen ML, Doyuran V (2004) Data driven bivariate landslide susceptibility assessment using geographical information systems: a method and application to Asarsuyu Catchment, Turkey. Eng Geol 71:303–321
Swets JA (1988) Measuring the accuracy of diagnostic systems. Science 240:1285–93
Tarboton DG (1997) A new method for the determination of flow directions and contributing areas in grid digital elevation models. Water Resour Res 33(2):309–319
Terlien MT, Van Westen CJ, Van Asch TW (1995) Deterministic modelling in GIS-based landslide hazard assessment. In: Carrara A, Guzetti F (eds) Geographical information systems in assessing in natural hazards. Kluwer, The Netherlands, pp 57–77
Thiebes B (2011): Landslide analysis and early warning—local and regional case study in the Swabian Alb. PhD thesis, University of Vienna
USGS (1993) USCS data user guide 5 for DEM’s, ftp://www.mapping.usgs.gov/pub/ti/DEM/demguide. Accessed 02.06.2006
Van Beek LP (2002) Assessment of the influence of change. PhD thesis, Utrecht University
Van Westen CJ, Rengers N, Terlien MTJ, Soeters R (1997) Prediction of the occurrence of slope instability phenomena through GIS based hazard zonation. Geol Rundsch 86(2):404–414
Van Westen CJ, Van Asch TWJ, Soeters R (2006) Landslide hazard and risk zonation: why is it still so difficult? Bull Eng Geol Environ 65(2):167–184
Varnes DJ (1978) Slope movement types and processes. In: Schuster RL, Krizek RJ (eds) Landslides analysis and control. Special Report, vol 176. Transportation Research Board, National Academy of Sciences, New York, pp 12–33
Williams CJ, Lee SS, Fisher RA, Dickerman LH (1999) A comparison of statistical methods for prenatal screening for Down syndrome. Applied Stochastic Models and Data Analysis 15:89–101
Wu W, Sidle R (1995) A distributed slope stability model for steep forested basins. Water Resour Res 2097–2110
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
Yesilnacar EK, Topal T (2005) Landslide susceptibility mapping: comparison between logistic regression and neural networks in a medium scale study, Hendek region Turkey). Eng Geol 79:251–266
Yilmaz I (2010a) Comparison of landslide susceptibility mapping methodologies for Koyulhisar, Turkey: conditional probability, logistic regression, artificial neural networks, and support vector machine. Environ Earth Sci 61(4):821–836
Yilmaz I (2010b) The effect of the sampling strategies on the landslide susceptibility mapping by conditional probability (CP) and artificial neural networks (ANN). Environ Earth Sci 60(3):505–519
Yılmaz I, Keskin I (2009) GIS based statistical and physical approaches to landslide susceptibility mapping (Sebinkarahisar, Turkey). Bull Eng Geol Environ 68:459–471
Acknowledgments
This study was financially supported by Karadeniz Technical University, Scientific Research Projects division (project number 2008.112.005.9). The authors thank the State Hydraulics Works 22nd District Management for providing data.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Akgun, A., Erkan, O. Landslide susceptibility mapping by geographical information system-based multivariate statistical and deterministic models: in an artificial reservoir area at Northern Turkey. Arab J Geosci 9, 165 (2016). https://doi.org/10.1007/s12517-015-2142-7
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s12517-015-2142-7