Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content

Advertisement

Springer Nature Link
Log in

Application of a semiquantitative and GIS-based statistical model to landslide susceptibility zonation in Kayangan Catchment, Java, Indonesia

  • Original Paper
  • Published:
Natural Hazards Aims and scope Submit manuscript

Abstract

Kayangan Catchment, one of the extremely landslide susceptible areas in Indonesia, is situated on the eastern flank of Menoreh Mountain in Yogyakarta Province on the island of Java. Landslides cause land and infrastructure damages because of their frequency in human settlements. The objectives of this study are twofold: (1) to analyze the spatial distribution of landslides and its correlation using terrain parameters; and (2) to analyze landslide susceptibility using both semiquantitative and statistical methods, i.e., analytical hierarchy process (AHP) and information value (IV) methods. Nine parameter maps were introduced to assess landslide susceptibility. The parameter maps and landslide distribution map were spatially overlaid to calculate the contribution of each parameter to landslide susceptibility. The landslide susceptibility map encompassed four different categories: very high, high, medium, and low susceptibility. The map was validated through a success rate curve by determining the area under the curve using existing landslide events. The success rate curves indicated that the IV was more accurate than the AHP, although both of them had high correlations. Both methods show that the precondition factors represented approximately 80% of the influence on landslide occurrence, with the remaining 20% attributed to the triggering factors, primarily rainfall and seismic factors.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  • Ahmed A, Brahmantyo B, Ugai K (2013) On the Tasikmalaya earthquake induced landslide in Indonesia: field investigation. In: Ugai K et al (eds) Earthquake-induced landslides. Springer, Berlin Heidelberg, pp 253–260

    Chapter  Google Scholar 

  • Aleotti P, Chowdhury P (1999) Landslide hazard assessment: summary review and new perspectives. Bull Eng Geol Environ 58:21–44

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Barredo JI, Benavides A, Hervas J, van Westen CJ (2000) Comparing heuristic landslide hazard assessment techniques using GIS in the Tirajana basin, Gran Canaria Island, Spain. Int J Appl Earth Obs Geoinform 2(1):9–23

    Article  Google Scholar 

  • Brabb EE (1984) Innovative approaches to landslide hazard mapping. In: Landslides-Glissements de Terrain, IV international symposium on landslides, vol 1. Toronto, pp 307–323

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

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Carrara A, Cardinali M, Guzzetti F, Reichenbach P (1995) GIS technology in mapping landslide hazard. In: Carrara A, Guzzetti F (eds) Geographical information systems in assessing natural hazards. Kluwer Academic Publishers, Dordrecht, pp 135–175

    Chapter  Google Scholar 

  • Carson MA, Kirkby MJ (1972) Hillslope form and process. Cambridge University Press, London

    Google Scholar 

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

    Article  Google Scholar 

  • Castellanos Abella EA, Van Westen CJ (2008) Qualitative landslide susceptibility assessment by multicriteria analysis: a case study from San Antonio del Sur, Guantánamo, Cuba. Geomorphology 94(3–4):453–466

    Article  Google Scholar 

  • Chau KT, Sze YL, Fung MK (2004) Landslide hazard analysis for Hong Kong using landslide inventory and GIS. Comput Geosci 30(4):429–443

    Article  Google Scholar 

  • Chung CF, Fabbri A (1998) Three Bayesian prediction models for landslide hazard. In: Bucciantti A (ed) Proceedings of international association for mathematical geology. IAMG’98. Ischia, pp. 204–211

  • Chung CF, Fabbri A (1999) Probabilistic prediction models for landslide hazard mapping. Photogramm Eng Remote Sens 65(12):1389–1399

    Google Scholar 

  • Chung CF, Fabbri A, Van Westen CJ (1995) Multivariate regression analysis for landslide hazard zonation. In: Carrara A, Guzzetti F (eds) Geographical information systems in assessing natural hazards. Kluwer Academic Publishers, Dordrecht, pp 107–133

    Chapter  Google Scholar 

  • Dai FC, Lee CF, Ngai YY (2002) Landslide risk assessment and management: an overview. Eng Geol 64:65–87

    Article  Google Scholar 

  • Das I, Stein A, Kerle N, Dadhwal VK (2012) Landslide susceptibility mapping along road corridors in the Indian Himalayas using Bayesian logistic regression models. Geomorphology 179:116–125

    Article  Google Scholar 

  • Dhakal AS, Amada T, Aniya M (1999) Landslide hazard mapping and the application of GIS in the Kulenkhani watershed, Nepal. Mt Res Dev 19(1):3–16

    Article  Google Scholar 

  • Duque A, Echeverría G, Fernández E, Kerejeta A, Cendrero A, Díaz de Terán JR, Tamés P (1991) A methodological approach for the development of predictive models for hazard assessment. In: Panizza M, Soldati M, Coltellacci MM (eds) Proceedings european experimental course on applied geomorphology, vol 2., Instituto di geologiaUniversitá degli Studi di Modena, Modena, pp 13–25

    Google Scholar 

  • Faris F, Fawu W (2014) Investigation of the initiation mechanism of an earthquake- induced landslide during rainfall: a case study of the Tandikat landslide, West Sumatra, Indonesia. Geoenviron Disasters 1:4

    Article  Google Scholar 

  • ftp://ftp.itc.nl/pub/ilwis/ilwis30/pdf/chap10.pdf, consulted on 1 July 2013

  • García-Rodríguez MJ, Malpica JA, Benitoc B, Díaz M (2008) Susceptibility assessment of earthquake-triggered landslides in El Salvador using logistic regression. Geomorphology 95:172–191

    Article  Google Scholar 

  • Glade T, Crozier MJ (2005) A review of scale dependency in landslide hazard and risk analysis. In: Glade T, Anderson M, Crozier MJ (eds) landslide hazard and risk. Wiley, Chichester, pp 75–138

    Chapter  Google Scholar 

  • Hadmoko DS (2009) Les mouvements de terrain dans les Monts Menoreh: variabilité spatio-temporelle, impacts, déclenchement, et analyse de la susceptibilité. Ph.D. thesis. Université Paris 1 Panthéon Sorbonne

  • Hadmoko DS, Lavigne F, Sartohadi J, Samodra G, Christanto N (2009) GIS application for comprehensive spatial landslides analysis in Kayangan Catchment, Menoreh Mountains, Java, Indonesia. In: Malet JP, Remaître A, Bogaard T (eds) Landslides processes: from geomorphic mapping to dynamic modeling. Europeen Center of Geomorphological Hazards, Strasbourg, pp 297–302

    Google Scholar 

  • Hadmoko DS, Lavigne F, Sartohadi J, Hadi MP (2010) Landslide hazard and risk assessment and their application in risk management and landuse planning in eastern flank of Menoreh Mountains, Yogyakarta Province, Indonesia. Nat Hazards 54(3):623–642. doi:10.1007/s11069-009-9490-0

    Article  Google Scholar 

  • He Y, Beighley RE (2008) GIS-based regional landslide susceptibility mapping: a case study in southern California. Earth Surf Process Landf 33:380–393

    Article  Google Scholar 

  • Irigaray C, Fernández T, Chacón J (1996) Comparative analysis of methods for landslide susceptibility mapping. In: Chacón J, Irigaray C, Fernández T (eds) Landslides. Balkema, Rotterdam, pp 373–384

    Google Scholar 

  • Irigaray CF, Del Castillo TF, El Hamdouni R, Montero JC (1999) Verification of landslide susceptibility mapping: a case study. Earth Surf Process Landf 24:537–544

    Article  Google Scholar 

  • Jade S, Sarkar S (1993) Statistical model for slope instability classifications. Eng Geol 36:71–98

    Article  Google Scholar 

  • Kayastha P, Dhital MR, De Smedt F (2013) Application of the analytical hierarchy process (AHP) for landslide susceptibility mapping: a case study from the Tinau watershed, west Nepal. Comput Geosci 52:398–408

    Article  Google Scholar 

  • Kendall M, Stuart A (1979) The advanced theory of statistics: inference and relationship. Griffin, London, p 748

    Google Scholar 

  • Khan YA, Lateh H (2011) Failure mechanism of a shallow landslide at Tun-Sardon road cut section of Penang Island, Malaysia. Geotech Geol Eng 29:1063–1072

    Article  Google Scholar 

  • Lee S, Talib JA (2005) Probabilistic landslide susceptibility and factor effect analysis. Environ Geol 47(7):982–990

    Article  Google Scholar 

  • Marfai MA, King L, Singh LP, Mardiatno D, Sartohadi J, Hadmoko DS (2008) Natural hazard in central Java. Environ Geol 56:335–351

    Article  Google Scholar 

  • Mulder HF (1991) In: Mulder HF (ed) Assessment of landslide hazard, Faculty of Geographical Science. University of Utrecht, The Netherlands

  • Oh HJ, Lee S, Soedradjat GM (2010) Quantitative landslide susceptibility mapping at Pemalang area, Indonesia. Environ Earth Sci 1(6):1317–1328

    Article  Google Scholar 

  • Ohlmacher GC (2007) Plan curvature and landslide probability in regions dominated by earth flows and earth slides. Eng Geol 91:117–134

    Article  Google Scholar 

  • Paudel PP, Omura H, Kubota T, Inoue T (2007) Spatio-temporal patterns of historical shallow landslides in a volcanic area Mt. Aso, Japan. Geomorphology 88:21–33

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Rahardjo W, Rumidi S, Rosidi HMD (1995) Peta Geologi Lembar Yogyakarta, Jawa. Pusat Penelitian dan Pengembangan Geologi, Bandung. (Geological map of Yogyakarta, Java)

  • Remondo J, Gonzàlez-Diez A, Dìaz de Teràn JR, Cendrero A (2003) Landslides susceptibility models utilising spatial data analysis techniques. A case study from the lower Deba Valley, Guipùzcoa (Spain). Nat Hazards 30:267–279

    Article  Google Scholar 

  • Saaty TL (1980) The analytic hierarchy process: planning, priority setting, resource allocation. McGraw-Hill Book Co, New York, p 287

    Google Scholar 

  • Saaty TL, Vargas LG (2001) Models, methods, concepts and applications of the analytic hierarchy process. Kluwer, Dordrecht, p 333

    Book  Google Scholar 

  • Saha AK, Gupta RP, Arora MK (2002) GIS-based landslide hazard zonation in the Bhagirathi (Ganga) Valley, Himalayas. Int J Remote Sens 23(2):357–369

    Article  Google Scholar 

  • 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 2:61–69

    Article  Google Scholar 

  • Schicker R, Moon V (2012) Comparison of bivariate and multivariate statistical approaches in landslide susceptibility mapping at a regional scale. Geomorphology 161–162:40–57

    Article  Google Scholar 

  • Sidle RC, Ochiai H (2006) Landslides: processes, prediction and landuse. Water Resources Monograph 18, American Geophysical Union, Washington, DC

  • Terlien MTJ (1996) Modelling spatial and temporal variations in rainfall-triggered landslides. Ph.D. Thesis. ITC Enschede, the Netherlands

  • Thiery Y, Malet JP, Sterlacchini S, Puissant A, Maquaire O (2007) Landslide susceptibility assessment by bivariate methods at large scales: application to a complex mountainous environment. Geomorphology 92:38–59

    Article  Google Scholar 

  • Van Den Eeckhout 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 76:392–410

    Article  Google Scholar 

  • Van Westen CJ (1993) Application of geographic information systems to landslide hazard zonation. Ph.D. Thesis, Technical University Delft. ITC-Publication Number 15, ITC, Enschede, The Netherlands

  • Van Westen CJ, Rengers N, Soeters R (2003) Use of Geomorphological Information in Indirect Landslide Susceptibility Assessment. Natural Hazards 30:399–419

    Article  Google Scholar 

  • Van Westen CJ, Van Ach TWJ, Soeters R (2005) Landslide hazard and risk zonation: Why is still so difficult ? Bull Eng Geol Environ 65:167–184

    Article  Google Scholar 

  • Van Westen CJ, Castellanos E, Kuriakose SL (2008) Spatial data for landslide susceptibility, hazard, and vulnerability assessment: an overview. Eng Geol 102(3–4):112–131

    Article  Google Scholar 

  • Varnes DJ (1984) Landslide hazard zonation: a review of principles and practice. Commission on landslides of the IAEG, UNESCO, Natural Hazards No. 3

  • Yalcin A (2007) GIS-based landslide susceptibility mapping using analytical hierarchy process and bivariate statistics in Ardesen (Turkey). Catena 72(1):1–12

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Yalcin A, Bulut F (2007) Landslide susceptibility mapping using GIS and digital photogrammetric techniques: a case study from Ardesen (NE-Turkey). Nat Hazards 41:201–226

    Article  Google Scholar 

  • Yin KJ, Yan TZ (1988) Statistical prediction model for slope instability of metamorphosed rocks. In: Proceedings 5th international symposium on landslides, vol 2. Lausanne, pp 1269–1272

  • 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 68:373–386

    Article  Google Scholar 

Download references

Acknowledgements

Author acknowledges Beasiswa Unggulan, Indonesian Ministry of Education and Culture through P2D program, for financial support, Research Centre for Disasters, and Faculty of Geography Universitas Gadjah Mada, Indonesia, for the facilities during data processing and providing financial support through Small Research Grant Project and UMR 8591 CNRS Laboratoire de Géographie Physique, 1 place A. Briand, 92195 Meudon Cedex, France, for data processing. The author is also grateful to the anonymous reviewers for their valuable comments on the manuscript.

Author information

Authors and Affiliations

  1. Department of Geography and Environmental Science, Faculty of Geography, Universitas Gadjah Mada, Sekip-Bulaksumur, Yogyakarta, 55281, Indonesia

    Danang Sri Hadmoko & Guruh Samodra

  2. UMR 8591 CNRS Laboratoire de Géographie Physique, University Paris 1 Panthéon Sorbonne, 1 Place A. Briand, 92195, Meudon Cedex, France

    Franck Lavigne

Authors
  1. Danang Sri Hadmoko
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Franck Lavigne
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Guruh Samodra
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Danang Sri Hadmoko.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hadmoko, D.S., Lavigne, F. & Samodra, G. Application of a semiquantitative and GIS-based statistical model to landslide susceptibility zonation in Kayangan Catchment, Java, Indonesia. Nat Hazards 87, 437–468 (2017). https://doi.org/10.1007/s11069-017-2772-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11069-017-2772-z

Keywords

Search

Navigation