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2012 | OriginalPaper | Buchkapitel

2. Landslide Susceptibility Mapping Using a Spatial Multi Criteria Evaluation Model at Haraz Watershed, Iran

verfasst von : H. R. Pourghasemi, Biswajeet Pradhan, Candan Gokceoglu, K. Deylami Moezzi

Erschienen in: Terrigenous Mass Movements

Verlag: Springer Berlin Heidelberg

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Abstract

The purpose of this study is to prepare landslide susceptibility map using a spatial multi criteria evaluation approach (SMCE) in a landslide-prone area (Haraz) in Iran. In the first stage, landslide locations were identified in the study area from interpretation of aerial photographs, and field surveys. In the second stage, twelve data layers were used as landslide conditioning factors for susceptibility mapping. These factors are slope, aspect, altitude, lithology, land use, distance from rivers, distance from roads, distance from faults, topographic wetness index, stream power index, stream transport index, and plan curvature. Next, landslide-susceptible areas were analyzed using the SMCE approach and mapped using landslide conditioning factors. For verification, the results of the analyses was compared with the field-verified landslide locations. Additionally, the receiver operating characteristics (ROC) curves for all landslide susceptibility models were drawn and the area under curve values was calculated. Landslide locations were used to validate results of the landslide susceptibility map generated using the SMCE approach and the verification results showed a 76.84% accuracy. According to the results of the AUC evaluation, the produced map has exhibited good performance.

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Vorheriges Kapitel An Automated Approach for Detection of Shallow Landslides from LiDAR Derived DEM Using Geomorphological Indicators in a Tropical Forest

Nächstes Kapitel Soft Computing Modeling in Landslide Susceptibility Assessment

Akgun A (2011) A comparision of landslide susceptibility maps produced by logistic regression, multi-criteria decision, and likelihood ratio methods: a case study at Izmir, Turkey. Landslides doi:10.1007/s10346-011-0283-7

Akgun A, Bulut F (2007) GIS-based landslide susceptibility for Arsin-Yomra (Trabzon, 381 North Turkey) region. Environ Geol 51:1377–1387CrossRef

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(6):1127–1143CrossRef

Akgun A, Turk N (2010) Landslide susceptibility mapping for Ayvalik (Western Turkey) 379 and its vicinity by multicriteria decision analysis. Env Earth Sci 61(3):595–611CrossRef

Anbalgan R (1992) Land hazard evaluation and zonation mapping in mountainous terrain. Eng Geol 32:269–277CrossRef

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):15–31CrossRef

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 81:432–445CrossRef

Baeza C, Lantada N, Moya J (2010) Validation and evaluation of two multivariate statistical models for predictive shallow landslide susceptibility mapping of the Eastern Pyrenees (Spain). Environ Earth Sci 61:507–523CrossRef

Bai S, Lü G, Wang J, Zhou P, Ding L (2010) GIS-based rare events logistic regression for landslide-susceptibility mapping of Lianyungang, China. Environ Earth Sci 62(1):139–149CrossRef

Brabb EE, Pampeyan EH (1972) Preliminary map of landslide deposits in San Mateo County, California. US Geological Survey Miscellaneous Field Studies, Map MF-360, scale 1:62.500 (reprinted in 1978)

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

Castellanos AEA (2008) Multi-Scale landslide risk assessment in Cuba. PhD thesis, ITC, ITC.Nl

Castellanos E, Van Westen CJ (2007) Generation of a landslide risk index map for Cuba using spatial multi-criteria evaluation. Landslide 4:311–325CrossRef

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

Chauhan S, Sharma M, Arora MK, Gupta NK (2010) Landslide susceptibility zonation through ratings derived from artificial neural network. Int J Appl Earth Observ Geoinf 12:340–350CrossRef

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

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

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

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

Dobrovolny E (1971) Landslide susceptibility in and near anchorage as interpreted from topographic and geologic maps, in the great Alaska earthquake of 1964-Geology volume. Publication 1603. U.S. Geological survey open file report 86-329, National Research Council, Committee on the Alaska Earthquake, National Academy of Sciences, USA, pp 735–745

Duman TY, Can T, Gokceoglu C, Nefeslioglu HA, Sonmez H (2006) Application of logistic regression for landslide susceptibility zoning of Cekmece Area, Istanbul, Turkey. Env Geol 51:241–256CrossRef

Ercanoglu M, Gokceoglu C (2004) Use of fuzzy relations to produce landslide susceptibility map of a landslide prone area (West Black Sea Region, Turkey). Eng Geol 75:229–250CrossRef

Ercanoglu M, Gokceoglu C (2002) Assessment of landslide susceptibility for a landslide-prone area (north of Yenice, NW Turkey) by fuzzy approach. Environ Geol 41:720–730CrossRef

Ermini L, Catani F, Casagli N (2005) Artificial neural networks applied to landslide susceptibility assessment. Geomorphology 66:327–343CrossRef

Fernández CI, Castillo TF, Hamdouni RE, Montero JC (1999) Verification of landslide susceptibility mapping: a case study. Earth Surf Proc Land 24(6):537–544CrossRef

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 81:65–83CrossRef

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 44:147–161CrossRef

Gritzner ML, Marcus WA, Aspinall R, Custer SG (2001) Assessing landslide potential using GIS, soil wetness modeling and topographic attributes, Payette River, Idaho. Geomorphology 37:149–165CrossRef

Guzzetti F, Carrarra A, Cardinali M, Reichenbach P (1999) Landslide hazard evaluation: are view of current techniques and their application in a multi-scale study, Central Italy. Geomorphology 31:181–216CrossRef

Hanley JA, McNeil BJ (1983) A method of comparing the areas under receiver operating characteristic curves derived from the same cases. Radiology 148:839–843

Hengl T, Gruber S, Shrestha DP (2003) Digital terrain analysis in ILWIS. International Institute for Geo-Information Science and Earth Oservation Enschede, The Netherlands, p 62

Herwijnen MV (1999) Spatial Decision Support for Environmental Management. Vrije Universiteit, Amsterdam 274

ITC (2001) ILWIS 3.0 academic-user’s guide. ITC, Enschede, p 520

Jakob M (2000) The impacts of logging on landslide activity at Clayoquot Sound, British Columbia. Catena 38:279–300CrossRef

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

Kanungo DP, Arora MK, Sarkar S, Gupta RP (2006) A comparative study of conventional, ANN black box, fuzzy and combined neural and fuzzy weighting procedures for landslide susceptibility zonation in Darjeeling Himalayas. Eng Geol 85(3–4):347–366CrossRef

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 26:1477–1491CrossRef

Lee S, Choi J, Min K (2004a) Probabilistic landslide hazard mapping using GIS and remote sensing data at Boun, Korea. Int J Remote Sens 25:2037–2052CrossRef

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

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

Lee S, Pradhan B (2006) Probabilistic landslide risk mapping at Penang Island. Malays J Earth Syst Sci 115(6):1–12

Lee S, Ryu JH, Won JS, Park H (2004b) Determination and application of the weights for landslide susceptibility mapping using an artificial neural network. Eng Geol 71:289–302CrossRef

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):199–219CrossRef

Luzi L, Pergalani F (1999) Slope instability in static and dynamic conditions for urban planning: the ‘‘Oltre Po Pavese’’ case history (Region Lombardia-Italy). Nat Hazards 20:57–82CrossRef

Maharaj RJ (1993) Landslide processes and landslide susceptibility analysis from an upland watershed: a case study from St. Andrew, Jamaica, West Indies. Eng Geol 34: 53–79CrossRef

Malczewski J (1999) GIS and multi criteria decision analysis. Wiley, New York. ISBN: 978-0-471-32944-2, P 408

Mejia-Navarro M, Garcia LA (1996) Natural hazard and risk assessment using decision support systems, application: Glenwood Springs, Colorado. Environ Eng Geosci 2(3):299–324

Mejia-Navarro M, Wohl EE (1994) Geological hazard and risk evaluation using GIS: methodology and model applied to Medellin, Colombia. Bull Assoc Eng Geol 31:459–481

Melchiorre C, Matteucci M, Remondo J (2006) Artificial neural networks and robustness analysis in landslide susceptibility zonation, IEEE. 2006 International Joint Conference on Neural Networks Sheraton Vancouver Wall Centre Hotel, Vancouver, 16–21 July, pp 4375–4381

Mohammadi M (2008) Mass movement hazard analysis and presentation of suitable regional model using GIS (Case Study: A part of Haraz Watershed), M.Sc. Thesis, Tarbiat Modarres University International Campus, Iran, P 80

Moore ID, Burch GJ (1986) Sediment transport capacity of sheet and rill flow: application of unit stream power theory. Water Res Res 22:1350–1360CrossRef

Moore ID, Gessler PE, Nielsen GA, Peterson GA (1993) Soil attribute prediction using terrain analysis. Soil Sci Soc Am J 57:443–452CrossRef

Moore ID, Grayson RB, Ladson AR (1991) Digital terrain modeling: a review of hydrological, geomorphological, and biological applications. Hydrol Process 5:3–30CrossRef

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, Mathematical Problems in Engineering, Article ID 901095, p 15, doi:10.1155/2010/901095

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

Ocakoglu F, Gokceoglu C, Ercanoglu M (2002) Dynamics of a complex mass movement triggered by heavy rainfall: a case study from NW Turkey. Geomorphology 42(3):329–341CrossRef

Oh HJ, Lee S, Chotikasathien W, Kim CH, Kwon JH (2009) Predictive landslide susceptibility mapping using spatial information in the Pechabun area of Thailand. Environ Geol 57:641–651CrossRef

Pachauri AK, Pant M (1992) Landslide hazard mapping based on geological attributes. Eng Geol 32:81–100CrossRef

Pachauri AK, Gupta PV, Chander R (1998) Landslide zoning in a part of the Garhwal Himalayas. Environ Geol 36(3–4):325–334CrossRef

Pourghasemi HR (2008) Landslide hazard assessment using fuzzy logic (Case Study: A part of Haraz Watershed), M.Sc. Thesis, Tarbiat Modarres University International Campus, Iran, pp 92

Pradhan B (2010a) Remote sensing and GIS-based landslide hazard analysis and cross-validation using multivariate logistic regression model on three test areas in Malaysia. Adv Space Res 45(10):1244–1256CrossRef

Pradhan B (2010b) Manifestation of an advanced fuzzy logic model coupled with Geoinformation techniques for landslide susceptibility analysis. Environ Ecol Stat 18(3):471–493CrossRef

Pradhan B (2010c) Application of an advanced fuzzy logic model for landslide susceptibility analysis. Int J Comput Intell Sys 3(3):370–381CrossRef

Pradhan B (2011) Use of GIS-based fuzzy logic relations and its cross application to produce landslide susceptibility maps in three test areas in Malaysia. Environ Earth Sci 63:329–349CrossRef

Pradhan B, Buchroithner MF (2010) Comparison and validation of landslide susceptibility maps using an artificial neural network model for three test areas in Malaysia. Environ Eng Geosci 16(2):107–126CrossRef

Pradhan B, Lee S (2009) Landslide risk analysis using artificial neural network model focusing on different training sites. Int J Phys Sci 3(11):1–15

Pradhan B, Lee S (2010a) Regional landslide susceptibility analysis using back-propagation neural network model at Cameron Highland, Malaysia. Landslides 7(1):13–30CrossRef

Pradhan B, Lee S (2010b) Landslide susceptibility assessment and factor effect analysis: backpropagation artificial neural networks and their comparison with frequency ratio and bivariate logistic regression modeling. Environ Modell Softw 25:747–759CrossRef

Pradhan B, Lee S (2010c) Delineation of landslide hazard areas using frequency ratio, logistic regression and artificial neural network model at Penang Island, Malaysia. Environ Earth Sci 60:1037–1054CrossRef

Pradhan B, Sezer E, Gokceoglu C, Buchroithner MF (2010) Landslide susceptibility mapping by neuro-fuzzy approach in a landslide prone area (Cameron Highland, Malaysia). IEEE T Geosci Remote 48(12):4164–4177CrossRef

Radbruch DH (1970) Map of relative amounts of landslides in California. US Geological Survey Open-File Report 70-1485, pp 36, map scale 1:500.000. US Geological Survey Open-File Report, pp 85–585

Saaty T (1980) The analytical hierarchy Process. McGraw-Hill, New York

Saaty TL (1997) A scaling method for priorities in hierarchical structures. J Math Psychol 15:234–281CrossRef

Saha AK, Gupta RP, Sarkar I, Arora MK, Csaplovics E (2005) An approach for GIS-based statistical landslide susceptibility zonation with a case study in the Himalayas. Landslides 2:61–69CrossRef

Saito H, Nakayama D, Matsuyama H (2009) Comparison of landslide susceptibility based on a decision-tree model and actual landslide occurrence: the Akaishi mountains, Japan. Geomorphology 109:108–121CrossRef

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 App 38(7):8208–8219CrossRef

Sharifi MA, Herwijnen MV (2003) Spatial decision support systems. International Instiute for Geo-Information Science and Earth Observation (ITC). p 201

Sharifi MA, Retsios V (2004) Site selection for waste disposal through spatial multiple criteria decision analysis. J Telecommun Inf Technol 3:1–11

Shou KJ, Wang CF (2003) Analysis of the Chiufengershan landslide triggered by the 1999 Chi–Chi earthquake in Taiwan. Eng Geol 68:237–250CrossRef

Tangestani MH (2009) A comparative study of dempster–shafer and fuzzy models for landslide susceptibility mapping using a GIS: an experience from zagros Mountains, SW Iran. J Asian Earth Sci 35:66–73CrossRef

Van Den Eeckhaut M, Vanwalleghem T, Poesen J, Govers G, Verstraeten G, Vandekerckhove L (2006) Prediction of landslide susceptibility using rare events logistic regression: a case-study in the Flemish Ardennes (Belgium). Geomorphology 76:392–410CrossRef

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

Varnes DJ (1978) Slope movement types and processes. In: Schuster RL, Krizek RJ (eds) Landslides analysis and control. Special Report, Transportation Research Board. vol 176 National Academy of Sciences, New York, pp 12–33

Wan S (2009) A spatial decision support system for extracting the core factors and thresholds for landslide susceptibility map. Eng Geol 108:237–251CrossRef

Wang R (2008) An expert knowledge-based approach to landslide susceptibility mapping using GIS and fuzzy logic, A dissertation submitted in partial fulfillment of the requirement for the degree of Docto of Philosophy, University of Wisconsin-Madison, p 175

Wilson JP, Gallant JC (2000) Terrain analysis principles and applications. Wiley, New York

Wood EF, Sivapalan M, Beven KJ (1990) Similarity and scale catchment storm response. Rev Geophisics 28:1–18CrossRef

Yalcin A (2005) An investigation on Ardesen (Rize) region on the basis of landslide susceptibility, KTU, PhD Thesis (in Turkish)

Yalcin A (2008) GIS-based landslide susceptibility mapping using analytical hierarchy process and bivariate statistics in Anderson (Turkey): comparision of results and confirmations. Catena 1:1–12CrossRef

Yeon YK, Han JG, Ryu KH (2010) Landslide susceptibility mapping in Injae, Korea, using a decision tree. Eng Geol 116:274–283CrossRef

Yesilnacar E, Topal T (2005) Landslide susceptibility mapping: a comparison of logistic regression and neural networks methods in a medium scale study, Hendek region (Turkey). Eng Geol 79(3–4):251–266CrossRef

Yilmaz I (2009) Landslide susceptibility mapping using frequency ratio, logistic regression, artificial neural networks and their comparison: a case study from kat landslides (Tokat-Turkey). Comp Geosci 35(6):1125–1138CrossRef

Zhou G, Esaki T, Mitani Y, Xie M, Mori J (2003) Spatial probabilistic modeling of slope failure using an integrated GIS Monte Carlo simulation approach. Eng Geol 68:373–386CrossRef

Zweig MH, Campbell G (1993) Receiver-operating characteristics (ROC) plots. Clin Chem 39:561–577

Titel: Landslide Susceptibility Mapping Using a Spatial Multi Criteria Evaluation Model at Haraz Watershed, Iran
verfasst von: H. R. Pourghasemi
Biswajeet Pradhan
Candan Gokceoglu
K. Deylami Moezzi
Verlag: Springer Berlin Heidelberg
Buch: Terrigenous Mass Movements
Print ISBN: 978-3-642-25494-9

Electronic ISBN: 978-3-642-25495-6

Copyright-Jahr: 2012
DOI: https://doi.org/10.1007/978-3-642-25495-6_2

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