Skip to main content

Probabilistic landslide hazards and risk mapping on Penang Island, Malaysia

Abstract

This paper deals with landslide hazards and risk analysis of Penang Island, Malaysia using Geographic Information System (GIS) and remote sensing data. Landslide locations in the study area were identified from interpretations of aerial photographs and field surveys. Topographical/geological data and satellite images were collected and processed using GIS and image processing tools. There are ten landslide inducing parameters which are considered for landslide hazard analysis. These parameters are topographic slope, aspect, curvature and distance from drainage, all derived from the topographic database; geology and distance from lineament, derived from the geologic database; landuse from Landsat satellite images; soil from the soil database; precipitation amount, derived from the rainfall database; and the vegetation index value from SPOT satellite images. Landslide susceptibility was analyzed using landslide-occurrence factors employing the probability-frequency ratio model. The results of the analysis were verified using the landslide location data and compared with the probabilistic model. The accuracy observed was 80.03%. The qualitative landslide hazard analysis was carried out using the frequency ratio model through the map overlay analysis in GIS environment. The accuracy of hazard map was 86.41%. Further, risk analysis was done by studying the landslide hazard map and damageable objects at risk. This information could be used to estimate the risk to population, property and existing infrastructure like transportation network.

This is a preview of subscription content, access via your institution.

References

  • Atkinson P M and Massari R 1998 Generalized linear modeling of susceptibility to landsliding in the central Apennines, Italy; Computer & Geosciences 24 373–385.

    Article  Google Scholar 

  • Baeza C and Corominas J 2001 Assessment of shallow landslide susceptibility by means of multivariate statistical techniques; Earth Surface Processes and Landforms 26 1251–1263.

    Article  Google Scholar 

  • Carro M, Amicis M, Luzi L and Marzorati S 2003 The application of predictive modeling techniques to landslides induced by earthquakes, the case study of the 26 September 1997 Umbria-Marche earthquake (Italy); Engineering Geology 69 139–159.

    Article  Google Scholar 

  • Christian J T, Ladd C C and Baecher G B 1992 Reliability and probability in stability; In: Stability and Performance of Slope and Embankments-II; Geotechnical Special Publication No. 3; Proc. ASCE Specialty Conference, Berkeley 1071–1111.

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

    Article  Google Scholar 

  • Dai F C, Lee C F, Li J and Xu Z W 2001 Assessment of landslide susceptibility on the natural terrain of Lantau Island, Hong Kong; Environmental Geology 40 381–391.

    Article  Google Scholar 

  • Dai F C and Lee C F 2002 Landslide characteristics and slope instability modeling using GIS; Lantau Island, Hong Kong; Geomorphology 42 213–228.

    Article  Google Scholar 

  • Donati L and Turrini M C 2002 An objective method to rank the importance of the factors predisposing to landslides with the GIS methodology, application to an area of the Apennines (Valnerina; Perugia, Italy); Engineering Geology 63 277–289.

    Article  Google Scholar 

  • Einstein H H 1988 Landslide risk assessment procedure; Proceedings of the Fifth International Symposium on Landslides 1075–1090.

  • Ercanoglu M and Gokceoglu C 2002 Assessment of landslide susceptibility for a landslide-prone area (north of Yenice, NW Turkey) by fuzzy approach; Environmental Geology 41 720–730.

    Article  Google Scholar 

  • Fell R 1994 Landsldie risk assessment and acceptable risk; Canadian Geotechnical Journal 31 261–272.

    Google Scholar 

  • Gokceoglu C, Sonmez H and Ercanoglu M 2000 Discontinuity controlled probabilistic slope failure risk maps of the Altindag (settlement) region in Turkey; Engineering Geology 55 277–296.

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Jibson W R, Edwin L H and John A M 2000 A method for producing digital probabilistic seismic landslide hazard maps; Engineering Geology 58 271–289.

    Article  Google Scholar 

  • Lee S and Min K 2001 Statistical analysis of landslide susceptibility at Yongin, Korea; Environmental Geology 40 1095–1113.

    Article  Google Scholar 

  • Lee S, Chwae U and Min K 2002a Landslide susceptibility mapping by correlation between topography and geological structure: the Janghung area, Korea; Geomorphology 46 49–162.

    Google Scholar 

  • Lee S, Choi J and Min K 2002b Landslide susceptibility analysis and verification using the Bayesian probability model; Environmental Geology 43 120–131.

    Article  Google Scholar 

  • Lee S, Ryu J H, Min K and Won J S 2003a Landslide Susceptibility Analysis using GIS and artificial neural network; Earth Surface Processes and Landforms 27 1361–1376.

    Article  Google Scholar 

  • Lee S, Ryu J H, Lee M J and Won J S 2003b Landslide susceptibility analysis using artificial neural network at Boun, Korea; Environmental Geology 44 820–833.

    Article  Google Scholar 

  • Lee S and Choi U 2003c Development of GIS-based geological hazard information system and its application for landslide analysis in Korea; Geoscience Journal 7 243–252.

    Article  Google Scholar 

  • Lee S, Ryu J H, Won J S and Park H J 2004a Determination and application of the weights for landslide susceptibility mapping using an artificial neural network; Engineering Geology 71 289–302.

    Article  Google Scholar 

  • Lee S, Choi J and Min K 2004b Probabilistic landslide hazard mapping using GIS and remote sensing data at Boun, Korea; International Journal of Remote Sensing 25 2037–2052.

    Article  Google Scholar 

  • Luzi L, Pergalani F and Terlien M T J 2000 Slope vulnerability to earthquakes at sub-regional scale, using probabilistic techniques and geographic information systems; Engineering Geology 58 313–336.

    Article  Google Scholar 

  • Ohlmacher G C and Davis J C 2003 Using multiple logistic regression and GIS technology to predict landslide hazard in northeast Kansa, USA; Engineering Geology 69 331–343.

    Article  Google Scholar 

  • Parise M and Jibson W R 2000 A seismic landslide susceptibility rating of geologic units based on analysis of characteristics of landslides triggered by the 17 January, 1994 Northridge, California earthquake; Engineering Geology 58 251–270.

    Article  Google Scholar 

  • Pistocchi A, Luzi L and Napolitano P 2000 The use of predictive modeling techniques for optimal exploitation of spatial databases: a case study in landslide hazard mapping with expert system-like methods; Environmental Geology 41 765–775.

    Article  Google Scholar 

  • Rautelal P and Lakhera R C 2000 Landslide risk analysis between Giri and Tons Rivers in Himachal Himalaya (India): International Journal of Applied Earth Observation and Geoinformation 2 153–160.

    Article  Google Scholar 

  • Rece A and Capolongo D 2002 Probabilistic modeling of uncertainties in earthquake-induced landslide hazard assessment; Computers & Geosciences 28 735–749.

    Article  Google Scholar 

  • Romeo R 2000 Seismically induced landslide displacements: a predictive model; Engineering Geology 58 337–351.

    Article  Google Scholar 

  • Rowbotham D and Dudycha D N 1998 GIS modeling of slope stability in Phewa Tal watershed, Nepal; Geomorphology 26 151–170.

    Article  Google Scholar 

  • Shou K J and Wang C F 2003 Analysis of the Chiufengershan landslide triggered by the 1999 Chi-Chi earthquake in Taiwan; Engineering Geology 68 237–250.

    Article  Google Scholar 

  • Temesgen B, Mohammed M U and Korme T 2001 Natural hazard assessment using GIS and remote sensing methods, with particular reference to the landslides in the Wondogenet area, Ethiopia; Physics and Chemistry of the Earth, Part C: Solar, Terrestrial and Planetary Science 26 665–675.

    Article  Google Scholar 

  • Varne D J 1984 Landslide hazard zonation: A review of principles and practice; Natural Hazards 3 63.

    Google Scholar 

  • Whitman R V 1984 Evaluating calculated risk in geotechnical engineering; ASCE Journal of Geotechnical Engineering 110 145–188.

    Google Scholar 

  • Zhou C H, Lee C F, Li J and Xu Z W 2002 On the spatial relationship between landslides and causative factors on Lantau Island, Hong Kong; Geomorphology 43 197–207.

    Article  Google Scholar 

  • Zhou G, Esaki T, Mitani Y, Xie M and Mori J 2003 Spatial probabilistic modeling of slope failure using an integrated GIS Monte Carlo simulation approach; Engineering Geology 68 373–386.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Lee, S., Pradhan, B. Probabilistic landslide hazards and risk mapping on Penang Island, Malaysia. J Earth Syst Sci 115, 661–672 (2006). https://doi.org/10.1007/s12040-006-0004-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12040-006-0004-0

Keywords

  • Landslide
  • frequency ratio
  • landslide hazard
  • risk analysis
  • geographic information system
  • remote sensing