Skip to main content

Advertisement

Log in

Landslide susceptibility mapping for Ayvalik (Western Turkey) and its vicinity by multicriteria decision analysis

  • Original Article
  • Published:
Environmental Earth Sciences Aims and scope Submit manuscript

Abstract

This paper presents the results of geographical information system (GIS)-based landslide susceptibility mapping in Ayvalık, western Turkey using multi-criteria decision analysis. The methodology followed in the study includes data production, standardization, and analysis stages. A landslide inventory of the study area was compiled from aerial photographs, satellite image interpretations, and detailed field surveys. In total, 45 landslides were recorded and mapped. The areal extent of the landslides is 1.75 km2. The identified landslides are mostly shallow-seated, and generally exhibit progressive character. They are mainly classified as rotational, planar, and toppling failures. In all, 51, 45, and 4% of the landslides mapped are rotational, planar, and toppling types, respectively. Morphological, geological, and land-use data were produced using existing topographical and relevant thematic maps in a GIS framework. The considered landslide-conditioning parameters were slope gradient, slope aspect, lithology, weathering state of the rocks, stream power index, topographical wetness index, distance from drainage, lineament density, and land-cover and vegetation density. These landslide parameters were standardized in a common data scale by fuzzy membership functions. Then, the degree to which each parameter contributed to landslides was determined using the analytical hierarchy process method, and the weight values of these parameters were calculated. The weight values obtained were assigned to the corresponding parameters, and then the weighted parameters were combined to produce a landslide susceptibility map. The results obtained from the susceptibility map were evaluated with the landslide location data to assess the reliability of the map. Based on the findings obtained in this study, it was found that 5.19% of the total area was prone to landsliding due to the existence of highly and completely weathered lithologic units and due to the adverse effects of topography and improper land use.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  • Akgun A (2007) GIS-based erosion and landslide susceptibility assessment of Ayvalık and ıts surrounding areas. Ph.D. thesis. Institute of Applied Sciences, Dokuz Eylul University, İzmir (In Turkish), 400 p

  • Akgun A, Bulut F (2007) GIS-based landslide susceptibility for Arsin-Yomra (Trabzon, North Turkey) region. Env Geol 51:1377–1387

    Article  Google Scholar 

  • 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. Env Geol 54(6):1127–1143

    Article  Google Scholar 

  • Akinci A, Taktak AG, Ergintav S (1994) Attenuation of coda waves in western Anatolia. Phys. Earth Planet Inter 87:155–165

    Article  Google Scholar 

  • Akyol N, Zhu L, Mitchell B, Sozbilir H, Kekovali K (2006) Crustal structure and local seismicity in western Anatolia. Geophys J Int 166(3):1259–1269

    Article  Google Scholar 

  • Akyurek B, Soysal Y (1981) Basic geological properties of the south part of Biga Peninsula (Savaştepe-Kırkağaç-Bergama Ayvalık). MTA J 95-96:1–13 (In Turkish)

    Google Scholar 

  • Altunkaynak Ş, Yilmaz Y (1998) The Mount Kozak magmatic complex, Western Anatolia. J Volcanol Geotherm Res 85:211–231

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Ayalew L, Yamagishi H, Marui H, Kanno T (2005) Landslide in Sado Island of Japan: Part II. GIS-based susceptibility mapping with comparison of results from two methods and verifications. Eng Geol 81:432–445

    Article  Google Scholar 

  • Butler DR, Walsh SJ (1990) Lithologic, structural and topographic influences on snow-avalanche path location, Eastern Glacier National Park, Montana. Ann Assoc Am Geog 80(3):362–378

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Carrara A (1983) A multivariate model for landslide hazard evaluation. Math Geol 15:403–426

    Article  Google Scholar 

  • Carrara A, Cardinalli M, Detti R, Guzetti F, Pasqui V, Reichenbach P (1991) GIS techniques and statistical models in evaluating landslide hazard. Earth Surf Proc Land 16(5):427–445

    Article  Google Scholar 

  • 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

    Google Scholar 

  • Cevik E, Topal T (2003) GIS-based landslide susceptibility mapping for a problematic segment of the natural gas pipeline, Hendek (Turkey). Environ Geol 44:949–962

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Chen X (2002) Using remote sensing and GIS to analyse land cover change and its impacts on regional sustainable development. Int J Remote Sens 23:107–124

    Article  Google Scholar 

  • Chen H, Lee CF (2003) A dynamic model for rainfall-induced landslides on natural slopes. Geomorphology 51:269–288

    Article  Google Scholar 

  • Chigira M, Yokoyama O (2005) Weathering profile of non-welded ignimbrite and the water infiltration behavior within it in relation to the generation of shallow landslides. Eng Geol 78:187–207

    Article  Google Scholar 

  • Clerici A, Perego S, Tellini C, Vescovi P (2002) A procedure for landslide susceptibility zonation by the conditional analysis method. Geomorphology 48:349–364

    Article  Google Scholar 

  • Congalton RG, Mead RA (1983) A quantitative method to test for consistency and correctness in photointerpretation. Photogramm Eng Remote Sens 49:69–74

    Google Scholar 

  • Conrad O (2002) Digitales Gelände-modell (DiGeM) terrain analysis software. http://www.geogr.uni-goettingen.de/pg/saga/digem/. 18 April 2006

  • CORINE (1995) Land cover technical guide. European Commission, Luxemburg, pp 21–53

    Google Scholar 

  • Dai FC, Lee CF (2001) Terrain-based mapping of landslide susceptibility using a geographical information systems: a case study. Can Geotech J 38:911–923

    Article  Google Scholar 

  • Dai FC, Lee CF (2002) Landslide characteristics and slope instability modelling using GIS, Lantau Island, Hong Kong. Geomorphology 42:213–228

    Article  Google Scholar 

  • Dai FC, Lee CF, Xu ZW (2001) Assessment of landslide susceptibility on the natural terrain of Lantau Island, Hong Kong. Environ Geol 40(3):381–391

    Article  Google Scholar 

  • De Fries RS, Chan JC-W (2000) Multiple criteria for evaluating machine learning algorithms for land cover classification from satellite data. Remote Sens Environ 74:503–515

    Article  Google Scholar 

  • Donati L, Turrini MC (2002) An objective method to rank the importance of the parameters predisposing to landslides with the GIS methodology: application to an area of the Appennines (Valnerina; Perugia, Italy). Eng Geol 63:277–289

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Eastman JR (1993) Decision theory and GIS. Proceedings, Africa GIS 93, UNITAR, Geneva

  • Eastman JR (2004) IDRISI Kilimanjaro: guide to GIS and ımage processing. Clark Labs, Clark University, Worcester, p 328

    Google Scholar 

  • Ercan T, Satır M, Turkecan A, Akyurek B, Cevikbas A, Gunay E, Ates M, Can B (1986) Ayvalık çevresinin jeolojisi ve volkanik kayaların petrolojisi. Jeoloji Mühendisliği Dergisi 27:11–19

    Google Scholar 

  • 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

    Article  Google Scholar 

  • Ermini L, Filippo C, Casagli N (2005) Artificial neural networks applied to landslide susceptibility assessment. Geomorphology 66:327–343

    Article  Google Scholar 

  • ESRI (2002) Getting to start ArcGIS. ESRI Books, USA

    Google Scholar 

  • Gemitzi A, Petalas C, Tsihrintzis VA, Pisinaras V (2006) Assessment of groundwater vulnerability to pollution: a combination of GIS, fuzzy logic and decision making techniques. Environ Geol 49(5):653–673

    Article  Google Scholar 

  • Gokceoglu C, Aksoy H (1996) Landslide susceptibility mapping of the slopes in the residual soils of the Mengen region (Turkey) by deterministic stability analyses and image processing techniques. Eng Geol 44:147–161

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Gupta RP (2003) Remote sensing geology, 2nd edn. Springer, Berlin, p 655

    Google Scholar 

  • Guzetti F, Carrarra A, Cardinal 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

    Article  Google Scholar 

  • Hall FG, Towhshend JR, Engman ET (1995) Status of remote sensing algorithms for estimation of land surface state parameters. Remote Sens Environ 51:138–156

    Article  Google Scholar 

  • Haralick RM, Sternberg SR, Zhuang X (1987) Image analysis using mathematical morphology. IEEE Trans Pattern Anal Mach Intell 9(4):532–550

    Article  Google Scholar 

  • Huang X, Jensen R (1997) A machine-learning approach to automated knowledge-base building for remote sensing image analysis with GIS data. Photogramm Eng Remote Sens 63:1185–1194

    Google Scholar 

  • Hung LQ, Batelaan O, De Smedt F (2005) Lineament extraction and analysis, comparison of Landsat ETM and ASTER imagery. Case study: Suoimuoi tropical karst catchment, Vietnam. In: Ehlers M, Michel U (eds) Remote sensing for environmental monitoring. GIS applications, and geology V. Proceedings of the SPIE, vol 5983, pp 182–193

  • Ildır B (1995) Turkiyede heyelanlarin dagilimi ve afetler yasası ile ilgili uygulamalar. In: Onalp A (ed) Proceedings of the 2nd national landslide symposium. Sakarya University, Turkey, pp 1–9

    Google Scholar 

  • ISRM (1981) In: Brown ET (ed) Rock characterization, testing and monitoring—ISRM suggested methods. Pergamon Press, Oxford

    Google Scholar 

  • Jensen JR (2000) Indroductory digital image processing: a remote sensing perspective. Prentice Hall, Upper Saddle River, p 319

    Google Scholar 

  • Jollifee IT, Stephenson DB (2003) Forecast verification. A practitioner’s guide in atmospheric science. Wiley, New York, p 240

    Google Scholar 

  • Kam TS (1995) Integrating GIS & RS techniques for urban land cover and land use analysis. Photogramm Eng Remote Sens 57:655–668

    Google Scholar 

  • Kavzoglu T, Mather PM (2003) The use of back-propagating artificial neural networks in land cover classification. Int J Remote Sens 24:4907–4938

    Article  Google Scholar 

  • 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. doi:10.1007/s12665-009-0070-0

  • Komac M (2006) A landslide susceptibility model using analytical hierarchy process method and multivariate statistics in perialpine Slovenia. Geomorphology 74:17–28

    Article  Google Scholar 

  • Kramer SL (1996) Geotechnical earthquake engineering. Prentice-Hall, Upper Saddle river, p 663

    Google Scholar 

  • Lee S (2004) Soil erosion assessment and its verification using the universal soil loss equation and geographic ınformation system: a case study at Boun, Korea. Env Geol 45(4):457–465

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Lee S, Min K (2001) Statistical analysis of landslide susceptibility at Yongin, Korea. Environ Geol 40:1095–1113

    Article  Google Scholar 

  • Lee S, Pradhan B (2007) Landslide hazard mapping at Selangor, Malaysia using frequency ratio and logistic regression models. Landslides 4:33–41

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Liu JG, Mason P, Hilton F, Lee H (2004) Detection of rapid erosion in SE Spain: a GIS approach based on ERS SAR coherence imagery. Photogramm Eng Remote Sens 70(10):1197–1185

    Google Scholar 

  • Lunetta RS, Elvidge CD (1998) Remote sensing change detection: environmental monitoring methods and applications. Ann Arbor Press, Chelsea, p 318

    Google Scholar 

  • Malczewski J (1999) GIS and multicriteria decision analysis. Wiley, New York, p 392

    Google Scholar 

  • Mason PJ, Rosenbaum MS (2002) Geohazard mapping for predicting landslides: an example from the Langhe Hills in Piemonte, NW Italy. Q J Eng Geol Hydrogeol 35:317–326

    Article  Google Scholar 

  • Moore ID, Grayson RB, Ladson AR (1991) Digital terrain modeling: a review of hydrological, geomorphological and biological applications. Hydrol Process 13(4):305–320

    Google Scholar 

  • 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 HA, Duman TY, Durmaz S (2008) Landslide susceptibility mapping for a part of tectonic Kelkit Valley (Eastern Black Sea region of Turkey). Geomorphology 94(3–4):401–418

    Article  Google Scholar 

  • Ohlmacher CG, Davis CJ (2003) Using multiple regression and GIS technology to predict landslide hazard in northeast Kansas, USA. Eng Geol 69:331–343

    Article  Google Scholar 

  • Pandey A, Dabral PP, Chowdary VM, Yadav NK (2007) Landslide hazard zonation using remote sensing and GIS: a case study of Dikrong river basin, Arunachal Pradesh, India. Env Geol 54(7):1517–1529

    Article  Google Scholar 

  • Pereıra JMC, Duckstein L (1993) A multiple criteria decision-making approach to GIS-based land suitability evaluation. Int J Geograph Inform Syst 75:407–424

    Article  Google Scholar 

  • Popescu ME (1996) From landslide causes to landslide remediation. In: Senneset K (ed) Landslides. Proceedings of the 7th ınternational symposium of landslides. Trondheim, Balkema, Rotterdam, pp 75–96

    Google Scholar 

  • Rashed T, Weeks J (2003) Assessing vulnerability to earthquake hazards through spatial multicriteria analysis of urban areas. Int J Geograph Inform Sci 17(6):547–576

    Article  Google Scholar 

  • Remondo J, Gonzalez A, Diaz De Teran JR, Cendrero A, Fabbri A, Cheng CF (2003) Validation of landslide susceptibility maps: examples and applications from a case study in Northern Spain. Nat Hazards 30(3):437–449

    Article  Google Scholar 

  • Ridd KM, Liu J (1998) A comparison of four algorithms for change detection in an urban environment. Remote Sens Environ 63:95–100

    Article  Google Scholar 

  • Rogan J, Chen DM (2004) Remote sensing technology for mapping and monitoring land-cover and lan-use change. Progress Plann 61(4):301–325

    Article  Google Scholar 

  • Saaty TL (1980) The analytical hierarchy process. McGraw Hill, New York

    Google Scholar 

  • Sakellariou MG, Ferentinou MD (2001) GIS-based estimation of slope stability. Nat Hazards Rev 2(1):12–21

    Article  Google Scholar 

  • Schuster RL, Fleming RW (1986) Economic losses and fatalities due to landslides. Bull Assoc Eng Geol 23:11–28

    Google Scholar 

  • Selby MJ (1980) A rock mass strength classification for geomorphic purposes: with tests from Antarctica and New Zealand. Zeitschrift für Geomorphologie 24:31–51

    Google Scholar 

  • 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, Special report no 247, Washington, DC, pp 129–177

  • Sunar F, Kaya S (1997) An assessment of geometric accuracy of remotely sensed images. Int J Remote Sens 18:3069–3074

    Article  Google Scholar 

  • Suzen ML, Doyuran V (2004a) Data driven bivariate landslide susceptibility assessment using geographical information systems: a method and application to Asarsuyu Catchment, Turkey. Eng Geol 71:303–321

    Article  Google Scholar 

  • Suzen ML, Doyuran V (2004b) A comparison of the GIS based landslide susceptibility assessment methods: multivariate versus bivariate. Environ Geol 45:665–679

    Article  Google Scholar 

  • Terlien MT, Van Westen CJ, Van Asch ThW (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

    Google Scholar 

  • USGS (1993) USCS data user guide 5 for DEM’s. ftp://mapping.usgs.gov/pub/ti/DEM/demguide. Accessed 12 April 2006

  • Vaiopoulos D, Nikolakopoulos K, Skianis G, Korompilis G, Antonakakis A (2002) Erosion risk and desertification risk at Pyrgos, Greece. In: Brebbia CA (ed) Management information systems 2002: GIS and remote sensing, vol 26, 448 pp

  • Van Westen CJ, Bonilla JBA (1990) Mountain hazard analysis using PC-based GIS. 6th IAEG Congress, vol 1. Balkema, Rotterdam, pp 265–271

    Google Scholar 

  • Van Westen CJ, Rengers N, Soeters R (2003) Use of geomorphological information in indirect landslide susceptibility assessment. Nat Hazards 30(3):399–419

    Article  Google Scholar 

  • Van Westen CJ, Van Asch TWJ, Soeters R (2006) Landslide hazard and risk zonation-why is it still so difficult? Bull Eng Geol Environ 65:167–184

    Article  Google Scholar 

  • 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

    Google Scholar 

  • Voogd H (1983) Multicriteria evaluation for urban and regional planning. Pion Ltd, London

    Google Scholar 

  • Weier J, Herring D (2005) Measuring vegetation (NDVI and EVI), Earth Observatory Library of NASA

  • Wood EF, Sıvapalan M, Beven KJ (1990) Similarity and scale catchment storm response. Rev Geophys 28:1–18

    Article  Google Scholar 

  • Yalcın A (2008) GIS-based landslide susceptibility mapping using analytical hierarchy process and bivariate statistics in Ardesen (Turkey): comparisons of results and confirmations. Catena 1:1–12

    Google Scholar 

  • Yesilnacar E, Topal T (2005) Landslide susceptibility mapping: a comparison of logistic regression and neural networks methods in a moderate scale study, Hendek region (Turkey). Eng Geol 79:251–266

    Article  Google Scholar 

  • Zadeh LA (1965) Fuzzy sets. Inf Control 12(2):94–102

    Article  Google Scholar 

Download references

Acknowledgments

This research was supported by the Dokuz Eylul University Scientific Research Fund, project number 02.KB.FEN.052. The authors thank Ayvalık Municipality and Mr. Vecdi Ziyansız for their support during the field investigations. The author also would like to thank the one anonymous reviewer for the constructive comments which significantly improved the quality of this paper.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Aykut Akgun.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Akgun, A., Türk, N. Landslide susceptibility mapping for Ayvalik (Western Turkey) and its vicinity by multicriteria decision analysis. Environ Earth Sci 61, 595–611 (2010). https://doi.org/10.1007/s12665-009-0373-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12665-009-0373-1

Keywords

Navigation