Skip to main content

Advertisement

Log in

Susceptibility Assessment of Shallow Landslides in Hulu Kelang Area, Kuala Lumpur, Malaysia Using Analytical Hierarchy Process and Frequency Ratio

  • Original paper
  • Published:
Geotechnical and Geological Engineering Aims and scope Submit manuscript

Abstract

Hulu Kelang is known as one of the most landslide susceptible areas in Malaysia. From 1990 to 2011, a total of 28 landslide events had been reported in this area. This paper compares two models as Analytical Hierarchy Process (AHP) and probability–frequency ratio (FR) methods for recognizing landslide susceptibility regions in the Hulu Kelang area. Eleven landslide influencing factors were considered to form the probability–FR and AHP matrix, i.e. lithology-weathering, land cover, curvature, slope inclination, slope aspect, drainage density, elevation, distance to lake and stream, distance to road and trenches, the Stream Power Index and the Topographic Wetness Index. The accuracy of the maps produced from the two models were verified using a receiver operating characteristics. The verification results indicated that the probability–FR model based on probabilistic analysis of spatial distribution of historical landslide events was capable of producing a more reliable landslide susceptibility map in this study area compared to AHP model. About 89 % of the landslide locations have been predicted accurately by using the FR map.

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.

Institutional subscriptions

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

Similar content being viewed by others

References

  • Akgün A, Bulut F (2007) GIS-based landslide susceptibility for Arsin-Yomra (Trabzon, North Turkey) region. Environ Geol 51:1348–1377

    Article  Google Scholar 

  • Akgün A, Dag S, Bulut F (2008) Landslide susceptibility mapping for landslide-prone area (Findikli, NE Turkey) by likelihood frequency ratio and weighted linear combination models. Environ Geol 54:1127–1143

    Article  Google Scholar 

  • Ali F (2000) Unsaturated tropical residual soils and rainfall induced slopes in malaysia. Asian Conference on Unsaturated Soils Singapore 41(52):18–19

    Google Scholar 

  • Ayalew L, Yamagishi H (2005) The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko mountains. Cent Jpn Geomorphol 65:15–31

    Article  Google Scholar 

  • Ayalew L, Yamagishi H, Ugawa N (2004) Landslide susceptibility mapping using GIS-based weighted linear combination, the case in Tsugawa area of Agano River, Niigata prefecture. Jpn Landslides 1:73–81

    Article  Google Scholar 

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

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Cervi F, Berti M, Borgatti L, Ronchetti F, Manenti F, Corsini A (2010) Comparing predictive capability of statistical and deterministic methods for landslide susceptibility mapping: a case study in the northern Apennines (Reggio Emilia Province, Italy). Landslides 7:433–444

  • 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 

  • Chigira M, Nakamoto M, Nakata E (2002) Weathering mechanisms and their effects on the landsliding of ignimbrite subject to vapor-phase crystallization in the Shirakawa pyroclastic flow, northern Japan. Eng Geol 66(1–2):111–125

    Article  Google Scholar 

  • Chung CJF, Fabbri AG (2003) Validation of spatial prediction models for landslide hazard mapping. Nat Hazards 30:451–472

  • Dai FC, Lee CF, Li J, Xu ZW (2001) Assessment of landslide susceptibility on the natural terrain of Lantau Island. Hong Kong. Environ Geol 43(3):381–391

    Google Scholar 

  • Dai FC, Lee CF, Ngai YY (2002) Landslide risk assessment and management: an overview. Eng Geol 64(1):65–87

    Article  Google Scholar 

  • D’Amato Avanzi G, Giannecchini R, Puccinelli A (2004) The influence of the geological and geomorphological settings on shallow landslides. An example in a temperate climate environment: the June 19, 1996 event in northwestern Tuscany (Italy). Eng Geol 73:215–228

    Article  Google Scholar 

  • Derbyshire E, Wang J, Meng X (2000) A treacherous terrain: background to natural hazards in northern China with special reference to the history of landslide in Gansu Province, in Landslides in the Thick Loess Terrain of North-West China. Wiley, Chichester, UK, pp 1–19

  • Ercanoglu M (2005) Landslide susceptibility assessment of SE Bartin (West Black Sea region, Turkey) by artificial neural networks. Nat Hazards Earth Syst Sci 5:979–992

    Article  Google Scholar 

  • Ercanoglu M, Gokceoglu C, Van Asch THWJ (2004) Landslide susceptibility zoning north of Yenice (NW Turkey) by multivariate statistical techniques. Nat Hazards 32:1–23

    Article  Google Scholar 

  • Ercanoglu M, Kasmer O, Temiz N (2008) Adaptation and comparison of expert opinion to analytical hierarchy process for landslide susceptibility mapping. Bull. Eng Geol Environ 67:565–578

    Article  Google Scholar 

  • Farisham AS (2007) Landslides in the hillside development in the Hulu Klang, Klang Valley. Post-Graduate Seminar, UTM, Skudai, Malaysia

  • Guzzetti F, Carrara A, Cardinalli M, Reichenbach P (2006) Landslide hazard evaluation: a review of current techniques and their application in a multi-scale study. Cent Italy. Geomorphology 31:181–216

    Article  Google Scholar 

  • Komac M (2006) A landslide susceptibility model using the analytical hierarchy process method and multivariate statistics in perialpine Slovenia. Geomorphology 74(1–4):17–28

    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, 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, Choi J, Min K (2004a) Probabilistic landslide hazard mapping using GIS and remote sensing data at Boun. Korea. Int J Remote Sens 25(11):2037–2052

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Low TH, Ali F (2012) Slope hazard assessment in urbanized area. Electron J Geotech Eng 17(C):341–352

  • Moore ID, O'Loughlin EM, Burch GJ (1988) A contour based topographic model and its hydrologic and ecological applications, Earth Surf. Process. Landforms 13: 305–320

  • Nagarajan R, Roy A, Vinod Kumar R, Mukherjee A, Khire MV (2000) Landslide hazard susceptibility mapping based on terrain and climatic factors for tropical monsoon regions. Eng Geol Environ 58:275–287

    Article  Google Scholar 

  • Nandi A, Shakoor A (2009) A GIS-based landslide susceptibility evaluation using bivariate and multivariate statistical analyses. Eng Geol 110:11–20

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

  • Phua MH, Minowa M (2005) Evaluation of environmental functions of tropical forest in Kinabalu Park, Sabah, Malaysia using GIS and remote sensing techniques: implications to forest conservation planning. J For Res 5:123–131

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Saaty TL (1977) A scaling method for priorities in hierarchical structures. J Math Psychol 15(3):234–281

  • Saaty TL (1980) The analytic hierarchy process. Mcgraw-Hill International, New York

  • Saaty TL, Vargas GL (2001) Models, methods, concepts, and applications of the analytic hierarchy process. Kluwer Academic Publisher, Boston

    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 

  • Sidle RC, Chigira M (2004) Landslides and debris flows strike Kyushu, Japan. Trans Am Geophys Union 85(15):145–151

    Article  Google Scholar 

  • Sidle RC, Ochiai H (2006) Landslides: processes, prediction and land use. Water Resour Monogr 18:312

    Google Scholar 

  • Sidle RC, Tsuboyama Y, Noguchi S, Hosoda I, Fujieda M, Shimizu T (2000a) Stream flow generation in steep headwaters: a linked hydrogeomorphic paradigm. Hydrol Process 14:369–385

    Article  Google Scholar 

  • Sidle RC, Kamil I, Sharma A, Yamashita S (2000b) Stream response to subsidence from underground coal mining in central Utah. Environ Geol 39(3–4):279–291

    Article  Google Scholar 

  • Swets JA (1988) Measuring the accuracy of diagnostic systems. Science 240:1285–1293

  • Vargas LG (1990) An overview of the analytic hierarchy process and its applications. Eur J Oper Res 1(48):2–8

    Article  Google Scholar 

  • Wakatsuki T, Tanaka Y, Matsukura Y (2005) Soil slips on weathering-limited slopes underlain by coarse-grained granite or fine-grained gneiss near Seoul, Republic of Korea. Catena 60(2):181–203

    Article  Google Scholar 

  • Wilson JP, Gallant JC (2000) Terrain analysis: principles and applications. Wiley, New York, pp 303

  • Yalcin A (2005) An investigation on Ardesen (Rize) region on the basis of landslide susceptibility. Ph.D. dissertation Karadeniz Technical University, Trabzon, Turkey (in Turkish)

  • Yalcin A (2008) GIS based landslide susceptibility mapping using analytical hierarchy process and bivariat statistics in Ardesen (Turkey): comparison of results and confirmations. Catena 72:1–12

    Article  Google Scholar 

  • Yoshimatsu H, Abe S (2006) A review of landslide hazards in Japan and assessment of their susceptibility using analytical hierarchy process (AHP) method. Landslides 3:149–158

    Article  Google Scholar 

Download references

Acknowledgments

The authors acknowledge and appreciate the provisions of rainfall and landslide data by the Ampang Jaya Municipal Council (MPAJ), the Slope Engineering Branch of Public Works Department Malaysia (PWD), and the Department of Irrigation and Drainage Malaysia (DID), without which this study would not have been possible.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Nader Saadatkhah.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Saadatkhah, N., Kassim, A. & Lee, L.M. Susceptibility Assessment of Shallow Landslides in Hulu Kelang Area, Kuala Lumpur, Malaysia Using Analytical Hierarchy Process and Frequency Ratio. Geotech Geol Eng 33, 43–57 (2015). https://doi.org/10.1007/s10706-014-9818-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10706-014-9818-8

Keywords

Navigation