Sains Malaysiana 46(9)(2017): 15311540
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
Diserahkan: 9
Disember 2016/Diterima: 2 Mei 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
RUJUKAN
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.
Zezere,
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.
*Pengarang
untuk surat-menyurat;
email: norbsn@ukm.edu.my