Sains Malaysiana 46(9)(2017): 1531–1540

http://dx.doi.org/10.17576/jsm-2017-4609-23

 

Landslide Factors and Susceptibility Mapping on Natural and Artificial Slopes in Kundasang, Sabah

(Faktor Tanah Runtuh dan Pemetaan Kerentanan ke atas Cerun Semula Jadi dan Buatan di Kundasang, Sabah)

 

KAMILIA SHARIR1, RODEANO ROSLEE2, LEE KHAI ERN3 & NORBERT SIMON1*

 

1School of Environmental and Natural Resource Sciences, Faculty of Science & Technology

Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor Darul Ehsan, Malaysia

 

2School of Science & Technology, Universiti Malaysia Sabah, UMS Road, 88400 Kota Kinabalu, Sabah Negeri di Bawah Bayu, Malaysia

 

3Institute for Environment and Development (LESTARI), Universiti Kebangsaan Malaysia

43600 UKM Bangi, Selangor Darul Ehsan, Malaysia

 

Received: 9 December 2016/Accepted: 2 May 2017

 

ABSTRACT

This study was carried out on the hilly topographic area in Kundasang, Sabah. This area is known to be extremely prone to landslides that occurred either naturally or by human interference to natural slopes. Aerial photographs interpretations was conducted in order to identify landslide distributions across three assessment years (2012, 2009 and 1984). These datasets were classified into two landslides groups based on their occurrences; natural and artificial. A total of 362 naturally occurring landslides were identified and another 133 are artificial slope landslides. Physical parameters which include lithology, slope angle, slope aspect and soil series were analyzed with each landslide group to examine the different influence of these parameters on each of the group. From the analysis, the landslide density for the natural landslide group shows that more than 35° slope angle and slope aspect facing east and southwest are prone to landslides. In terms of geological materials, high landslide density is recorded in the phyllite, shale, siltstone and sandstone lithologies group and the Pinosuk, Kepayan and Trusmadi soil series. In contrast, for the artificial slope landslide, high landslide density is observed in the 25°-35° slope angle and similar density in every slope aspect classes. The geological materials however have similar landslide density across their factors' classes. The landslide density technique was also used to generate the landslide susceptibility maps for both landslide conditions. Validation of the maps shows acceptable accuracy of 71% and 74%, respectively, for both natural and artificial slope landslide susceptibility maps and this shows that these maps can be used for future land use planning.

 

Keywords: Artificial slope landslide; landslide; landslide density; landslide susceptibility; natural landslide

 

ABSTRAK

Kajian ini dijalankan di kawasan bertopografi tinggi yang terletak di Kundasang, Sabah. Kawasan ini terkenal dengan kejadian tanah runtuh tinggi yang berlaku secara semula jadi ataupun secara gangguan oleh manusia pada cerun semula jadi. Penafsiran fotograf udara telah dilakukan untuk mengenal pasti taburan tanah runtuh sepanjang tiga tahun penilaian (2012, 2009 dan 1984). Set data ini telah dikelaskan kepada dua kumpulan tanah runtuh berdasarkan kepada punca berlakunya tanah runtuh, sama ada secara semula jadi atau pada cerun buatan. Sejumlah 362 tanah runtuh semula jadi telah dikenal pasti manakala 133 tanah runtuh lagi berlaku di cerun buatan. Parameter fizikal; litologi, sudut kecuraman cerun, aspek cerun dan siri tanah dianalisis bersama dengan setiap kumpulan tanah runtuh untuk melihat perkaitannya pada setiap kumpulan tersebut. Daripada analisis yang dibuat, ketumpatan tanah runtuh dalam kumpulan tanah runtuh semula jadi menunjukkan bahawa, sudut kecuraman cerun melebihi 35° dan aspek cerun yang menghadap arah timur dan barat daya mempunyai tahap kerentanan tanah runtuh yang tinggi. Daripada segi bahan geologi pula, ketumpatan tanah runtuh yang tinggi direkodkan dalam batuan jenis filit, syal, batu lodak dan batu pasir serta jenis tanah daripada siri Pinosuk, Kepayan dan Trusmadi. Bagi ketumpatan tanah runtuh yang berlaku di cerun buatan manusia pula, ketumpatan tinggi direkodkan pada sudut kecuraman cerun 25°-35° dan hampir sama dalam setiap kelas aspek cerun. Daripada segi bahan-bahan geologi pula, ketumpatan tanah runtuh adalah hampir sama dalam semua kelas jenis batuan dan siri tanah. Teknik ketumpatan tanah runtuh ini juga digunakan untuk menghasilkan peta kerentanan tanah runtuh untuk kedua-dua set data ini. Pengesahan peta ini menunjukkan nilai ketepatan yang boleh diterima iaitu 71% dan 74% masing-masing untuk peta kerentanan tanah runtuh semula jadi dan cerun buatan manusia dan ini menunjukkan peta-peta ini boleh digunakan dalam perancangan guna tanah pada masa hadapan.

 

Kata kunci: Kerentanan tanah runtuh; ketumpatan tanah runtuh; tanah runtuh; tanah runtuh cerun buatan; tanah runtuh semula jadi

REFERENCES

Australian Geomechanics Society. 2007. Guideline for landslide susceptibility, hazard and risk zoning for land use planning. Australian Geomechanics 42(1): 13-36.

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.

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.

Chalkias, C., Ferentinou, M. & Polykretis, C. 2014. GIS-based landslide susceptibility mapping on the Peloponnese Peninsula, Greece. Geosciences 4: 176-190.

Dai, F.C. & Lee, C.F. 2002. Landslide characteristics and slope instability modelling using GIS, Lantau Island, Hong Kong. Geomorphology 42: 213-228.

Dai, F.C., Lee, C.F., Li, J. & Xu, Z.W. 2001. Assessment of landslide susceptibility on the natural terrain of Lantau Island, Hong Kong. Environ. Geol. 40: 381-391.

Gomez, H. & Kavzoglu, T. 2005. Assessment of shallow landslide susceptibility using artificial neural networks in Jabonosa River Basin, Venezuela. Engineering Geology 78: 11-27.

Guzzetti, F., Reichenbach, P., Ardizzone, F., Cardinali, M. & Galli, M. 2006. Estimating the quality of landslide susceptibility models. Geomorphology 81(1-2): 166-184.

Guzzetti, F., Reichenbach, P., Cardinali, M., Galli, M. & Ardizzone, F. 2005. Landslide hazard assessment in the Staffora basin, northern Italian Apennines. Geomorphology 72: 272-299.

Guzzetti, F., Carrara, A., Cardinali, M. & 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.

Hufschmidt, G. & Crozier, M.J. 2008. Evolution of natural risk: Analysing changing landslide hazard in Wellington, Aotearoa/New Zealand. Natural Hazards 45: 255-276.

Jabcoson, G. 1970. Gunung Kinabalu area, Sabah, Malaysia. Geol. Surv. Malaysia. Report 8: 111.

Jadda, M., Shafri, H.Z.M., Mansor, S.B., Sharifika, M., & Pirasteh, S. 2009. Landslide susceptibility evaluation and factor effect analysis using probabilistic-frequency ratio model. European Journal of Scientific Research 33(4): 654-668.

Fell, R., Corominas, J., Bonnard, C., Cascini, L., Leroi, E., Savage, W.Z. on behalf of the JTC-1 Joint Technical Committee on Landslides and Engineered Slopes 2008. Guidelines for landslide susceptibility, hazard and risk zoning for land use planning. Engineering Geology 102: 85-98.

Kolat, C., Doyuran, V., Ayday, C. & Süzen, M.L. 2006. Preparation of a geotechnical microzonation model using geographical information systems based on multicriteria decision analysis. Eng. Geol. 87: 241-255.

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

Magliulo, P., Antonio, D.L., Filippo, R. & Antonio, Z. 2008. Geomorphology and landslide susceptibility assessment using GIS and bivariate statistics: A case study in southern Italy. Natural Hazards 47(3): 411-435.

Nagarajan, R., Roy, A., Vinod, K.R., Mukherjee, A. & Khire, M.V. 2000. Landslide hazard susceptibility mapping based on terrain and climatic factors for tropical monsoon regions. Bull. Eng. Geol. Env. 58: 275-287.

Ohlmacher, G.C. & Davis, J.C. 2003. Using multiple logistic regression and GIS technology to predict landslide hazard in northeast Kansas, USA. Eng. Geol. 69: 331-343.

Ohlmacher, G.C. 2000. The relationship between geology and landslide hazards of Atchison, Kansas and Vicnity. Current Research in Earth Sciences: Kansas Geological Survey Bulletin 244: 1-6.

Oyagi, N. 1984. Landslides in weathered rocks and residuals soils in Japan a surrounding areas: State-of-the-art report. Proceedings of the 4th International Symposium on Landslides, Toronto. pp. 1-31.

Rib, H.T. & Ta, L. 1978. Recognition and identification. In Landslides Analysis and Control, Special Report, edited by Schuster, R.A. Washington: National Academy of Science. 176: 34-80.

Roslee, R., Jamaluddin, T.A. & Talip, M.A. 2012. Landslide susceptibility mapping (LSM) at Kota Kinabalu, Sabah, Malaysia using factor analysis model (FAM). Journal of Advanced Science and Engineering Research 2: 80-103.

Roslee, R., Tahir, S., Zawawi, N.S.A., Mansor, H.E. & Omang, S.A.K.S. 2008. Engineering geological assessment on slope design in the mountainous area of Sabah Western, Malaysia: A case study from the Ranau - Tambunan, Penampang - Tambunan and Kimanis - Keningau Road. An International Conference on Recent Advances in Engineering Geology. Kuala Lumpur, Malaysia.

Süzen, M.L. & Doyuran, V. 2004. Data driven bivariate landslide susceptibility assessment using geographical information systems: A method and application to Asarsuyu catchment, Turkey. Eng. Geol. 71: 303-321.

Simon, N., De Roiste, M., Crozier, M. & Rafek, A.G. 2017. Representing landslides as polygon (areal) or points? How different data types influence the accuracy of landslide susceptibility maps. Sains Malaysiana 46(1): 27-34.

Simon, N. 2012. Developing a systematic approach to susceptibility mapping for landslides in natural and artificial slopes in an area undergoing land use change, Kota Kinabalu, Sabah, Malaysia. Ph.D Thesis. Victoria University of Wellington (Unpublished).

Tating, F. 2006. Geological factors contributing to the landslide hazard area at the Tamparuli - Ranau Highway, Sabah,

Malaysia. Proc. of International Symposium on Geotechnical Hazards: Prevention, Mitigation and Engineering Response. Yogyakarta, Indonesia. p. 10.

Thanapackiam, P., Khairulmaini, O.S. & Fauza, A.G. 2012. Space-time behavior of Klang Valley region slope failures. Sains Malaysiana 41(12): 1613-1620.

Tongkul, F. 2007. Geological inputs in road design and construction in mountainous areas of West Sabah, Malaysia. Second Malaysia-Japan Symposium on Geohazards and Geoenvironmental Engineering Recent Advances. Langkawi, Malaysia.

van Westen, C.J., Rengers, N. & Soeters, R. 2003. Use of geomorphological information in indirect landslide susceptibility assessment. Nat. Hazards 30: 399-413.

Wieczorek, G.F., Mandrone, G. & De Colla, L. 1997. The influence of hill slope shapes on debris-flow initiation. In Debris Flow Hazard Mitigation: Mechanics, Prediction, and Assessment, edited by Chen, C.L. New York: American Society of Civil Engineers. pp. 21-31.

Yalcin, A. 2008. GIS-based landslide susceptibility mapping using analytical hierarchy process and bivariate statistics in Ardesen (Turkey): Comparisons of results and confirmations, Turkey. Catena 72: 1-12.

Yang, S. & Yeh, Y. 2015. Geologic hazard risk assessment of slopeland villages in Southern Taiwan using remote sensing techniques. Sains Malaysiana 44(12): 1677-1683.

Zˆezere, J.L., de Brum, F.A. & Rodrigues, M.L. 1999. The role of conditioning and triggering factors in the occurrence of landslides: A case study in the area north of Lisbon (Portugal). Geomorphology 30: 133-146.

 

 

*Corresponding author; email: norbsn@ukm.edu.my

 

 

 

 

previous