Sains Malaysiana 48(1)(2019): 33–43
http://dx.doi.org/10.17576/jsm-2019-4801-05
Keperluan
Peta Kerentanan Bencana sebagai Input dalam Pengurusan Guna Tanah: Kajian Kes Universiti
Kebangsaan Malaysia
(The
Needs of Disaster Susceptibility Map as an Input in Land Use Management: A Case
Study of Universiti Kebangsaan Malaysia)
NURFASHAREENA MUHAMAD, CHOUN-SIAN LIM, MOHAMMAD IMAM HASAN REZA
&
JOY JACQUELINE PEREIRA*
Pusat
Kajian Bencana Asia Tenggara (SEADPRI-UKM), Institut Alam Sekitar dan
Pembangunan, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor Darul
Ehsan, Malaysia
Diserahkan:
14 Februari 2018/Diterima: 1 September 2018
ABSTRAK
Limpahan pesat aktiviti tepu bina di UKM Bangi
untuk memenuhi kehendak dan juga keperluan warganya menjadikan ia setara fungsi
satu pekan kecil. Di samping pembangunan yang pesat, UKM turut
mengalami insiden kegagalan cerun, tanah runtuh dan banjir kecil di beberapa
kawasan dalam kampus. Kajian ini direka untuk menyepadukan maklumat pelbagai
dimensi untuk menyokong membuat keputusan dalam pengurusan guna tanah untuk
menangani isu bencana di kampus ini. Objektif kajian adalah untuk: mengenal
pasti maklumat pelbagai dimensi yang menyumbang kepada bencana di UKM dan
membangunkan satu peta kerentanan tanah runtuh dan banjir untuk menyokong dalam
membuat keputusan secara termaklum. Melalui pendekatan heuristik, tiga kaedah
utama telah digunakan untuk menghasilkan peta kerentanan tanah runtuh dan
banjir iaitu: analisis kandungan untuk mengenal pasti kriteria yang menyumbang
kepada tanah runtuh dan banjir; elisitasi pakar untuk memberi nilai pemberat
terhadap kriteria; dan analisis tindan-lapis untuk memproses dan menjana peta
tematik. Kriteria yang menyumbang kepada tanah runtuh dan banjir dikategorikan
kepada faktor hujan, topografi, struktur geologi dan ciri-ciri geomorfologi
yang seterusnya diberi nilai pemberat. Peta kerentanan tanah runtuh yang
terhasil menunjukkan kelas kerentanan tinggi merupakan kelas terbesar di UKM dengan
keluasan sebanyak 6.10 km2 bersamaan 51.91% daripada jumlah
keluasan asal kampus. Analisis terhadap lokasi insiden lepas mendapati kesemua
taburan tanah runtuh berlaku pada kelas kerentanan sederhana, tinggi dan sangat
tinggi. Hampir separuh daripada jumlah taburan tanah runtuh berlaku pada kelas kerentanan
tinggi iaitu 57.14% yang merupakan peratusan terbesar. Peta kerentanan banjir
menunjukkan UKM turut terdedah kepada banjir. Majoriti kawasan kampus
didominasi oleh kelas kerentanan sederhana dengan keluasan sebanyak 6.5 km2 kira-kira
hampir 56% daripada keluasan asal. Aset penting universiti dan laluan utama
kampus ini yang bersebelahan dengan saliran sungai terletak di dalam kawasan berkerentanan
tinggi. Situasi ini agak membimbangkan kerana terdapat infrastruktur penting di
sekitar kawasan ini. Input berguna yang diperoleh melalui kajian ini telah menunjukkan
keupayaan peta kerentanan tanah runtuh dan banjir sebagai medium yang
bermaklumat dalam perancangan guna tanah sebelum menjalankan sebarang aktiviti
pembangunan di sesuatu kawasan.
Kata kunci: GIS; guna tanah; peta kerentanan
bencana; UKM
ABSTRACT
The rapid overflow of built-up activities in UKM to meet the needs of the campus
deems it a small town. In conjunction with this rapid development, UKM has experienced slope failures,
landslides and small inundation in several areas within the campus. This study
is designed to integrate multi-dimensional information to support
decision-making in land use management to address disaster issues in this
campus. The objectives were to: identify the various dimensions of information
that contributed to disasters in UKM; and develop a landslide and
flood susceptibility map to support informed decision-making. The study
employed a heuristic approach and three main methods including: content
analysis to identify criteria that contribute to landslides and floods; expert
elicitation to provide weightage; and overlay analysis to produce
thematic maps. Criteria that contribute to landslides and floods are
categorized into precipitation, topography, geological structure and
geomorphological characteristics that are weighted according to expert
input. Landslide
susceptibility map shows high susceptibility class is the largest at 6.10 km2 equivalent to 51.91% of the total
area of campus. Analysis of past incidences found that all landslides occurred
in medium, high and very high susceptibility classes. About half of the total
landslides amounting to 57.14% are located in high susceptibility classes and
this represents the largest percentage. Flood susceptibility map indicates that UKM is also exposed to flooding. The
moderate susceptibility class dominates the campus at 6.5 km2, which is about 56% of the total
area. The university’s asset and the main route of this campus, which is
adjacent to a river is located within the high susceptibility area. The
situation is quite alarming as important infrastructure is located within this
area. The findings reflect the capability of landslide and flood susceptibility
maps as an informative medium in land use planning before executing any
development activities in a particular area.
Keywords: Disaster
susceptibility map; GIS; land use; UKM
RUJUKAN
Abd. Manap, M., Mohammad Firuz, R., Wan Nor Azmin, S. &
Noraini, S. 2010. Application of remote sensing in the identification of the
geological terrain features in Cameron Highlands, Malaysia. Sains Malaysiana 39(1): 1-11.
Abd. Nasir, M., Abdul, B. & Harahap, I.S.H. 2012. Study
of regional monsoonal effects on landslide hazard zonation in Cameron
Highlands, Malaysia. Arabian Journal of Geosciences 5(5): 1069-1084.
Ahmed, B. 2015. Landslides susceptibility mapping using
multi-criteria evaluation techniques in Chittagong Metropolitan Area
Bangladesh. Landslide 12(6): 1077-1095.
Ainon Nisa, O., Wan Mohd Naim, W.M. & Noraini, S. 2012.
GIS based multi-criteria decision making for landslide hazard zonation. Procedia
- Social and Behavioral Sciences 35: 595-602.
Anbalagan, R. 1992. Land hazard evaluation and zonation
mapping in mountainous terrain. Engineering Geology 32: 269-277.
Arnous, O. 2011. Integrated remote sensing and GIS
techniques for landslide hazard zonation: A case study Wadi Watier Area, South
Sinai, Egypt. Journal of Coastal Conservation 15: 477-497.
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. Engineering
Geology 81: 432-445.
Ayyub, B.M. 2001. A practical guide on conducting
expert-opinion elicitation of probabilities and consequences for corps
facilities. Institute of Water Resources Report 01-R-01.
Basharat, M., Shah, H.R. & Hameed, N. 2016. Landslide
susceptibility mapping using GIS and weighted overlay method: a case study from
NW Himalayas, Pakistan. Arabian Journal of Geoscience 9: 292.
Bujang, B.K.H., Faisal Ali, David, H.B., Singh, H. &
Husaini Omar. 2008. Landslide in Malaysia: Occurrences, Assessment, Analyses
and Remediation. Serdang: Universiti Putra Malaysia.
Bhatt, P.B., Awasthi, K.D., Heyojoo, B.P., Silwal, T. &
Kafle, G. 2013. Using geographic information system and analyical hierarchy
process in landslide hazard zonation. Applied Ecology and Environmental
Sciences 1(2): 14-22.
Campbell, J. & Shin, M. 2015. Essentials of
Geographic Information Systems, v. 1.0. US: Flat World Education Inc.
Castellanos Abella, E.A. & van Westen, C.J. 2007.
Generation of a landslide risk index map for Cuba using spatial multi-criteria
evaluation. Landslides 4: 311-325.
Chi, M.T.H., Glaser, R. & Farr, M.J. 1988. The Nature
of Expertise. New Jersey: Erlbaum.
Dai, F.C., Lee, C.F. & Ngai, Y.Y. 2002. Landslide risk
assessment and management: An overview. Engineering Geology 64: 65-87.
Ehsan, S. & Marx, W. 2011. Impact of river valley shape
on flow characteristics, Pakistan. Journal of Engineering and Applied
Sciences 8: 9-20.
ESRI. 2013. Understanding GIS. http://www.esri.com/what-is-gis.
Diakses pada 5 November 2013.
ESRI. 2015. Data Classification Methods. http://pro.arcgis.
com/en/pro app/help/mapping/symbols-and-styles/data-classification-methods.htm.
Farhan, A. & Akhyar, H. 2017. Analysis of tsunami
disaster map by GIS: Aceh Singkil-Indonesia. IOP Conference Series: Earth
and Environmental Science 56: 012002.
Feizizadeh, B., Roodposhti, M.S., Jankowski, P. &
Blaschke, T. 2014. A GIS-based extended fuzzy multi-criteria evaluation for
landslide susceptibility mapping. Computers & Geosciences 73:
208-221.
Goldsworthy, M. & Jackson, J. 2000. Active normal fault
evolution in Greece revealed by geomorphology and drainage patterns. Journal
of the Goelogical Soeciety 157(5): 967-981.
Gorsevski, P.V., Jankowski, P. & Gessler, P.E. 2006. An
heuristic approach for mapping landslide hazard by integrating fuzzy logic with
analytic hierarchy process. Control and Cybernetics 35(1): 121-146.
Hervas, J. & Bobrowsky, P. 2009. Chapter 19 - Mapping:
Inventories, susceptibility, hazard and risk. Dlm. Landslides- Disaster Risk
Reduction, disunting oleh Sassa, K. & Canuti, P. Berlin:
Springer-Verlag Berlin Heidelberg.
Ibrahim, K. 1987. Survey of slope failures in Selangor. Sains
Malaysiana 16(1): 1-14.
Ibrahim, K. 1984. Geological aspect engineering of the earth
in Bangi, Selangor. Ilmu Alam 12&13: 41-54.
Ilanloo, M. 2011. A comparative study of Fuzzy Logic
approach for landslide susceptibility mapping using GIS: An experience of Karaj
Dam Basin in Iran. Procedia - Social and Behavioral Sciences 19:
668-676.
Isa, I., Muibi, K.H., Alaga, A.T., Babatimehin, O.,
Ige-Olumide, O., Mustapha, O.O. & Hafeez, S.A. 2015. Suitability analysis
of resettlement sites for flood disaster victims in Lokoja and Evirons. World
Environment 5(3): 101-111.
Ituen, U.J., Johnson, I. & Nyah, N. 2014. Flood hazard
assessment and decisions support using Geographic Information System: A case
study of Uyo Capital City, Akwa Ibom State, Nigeria. International Journal
of Geography and Geology 3(4): 56-67.
Jabatan Mineral dan Geosains Malaysia (JMG). 2006. Data
of Geological Terrain Map. Putrajaya: Jabatan Mineral dan Geosains
Malaysia.
Jansen, J.D. 2006. Flood magnitude-frequency and lithologic
control on bedrock river incision in post-orogenic terrain. Geomorphology 82 (1-2): 39-57.
Lee, S. & Pradhan, B. 2007. Landslide hazard mapping at
Selangor, Malaysia using frequency ratio and logistic regression models. Landslides 4: 33-41.
Lee, S. & Jasmi, A.T. 2005. Probabilistic landslide
susceptibility and factor effect analysis. Environmental Geology 47(7):
982-990.
Lim, C.S. 2004. Pemetaan geobencana menggunakan Sistem
Maklumat Geografi: Kajian kes di Wilayah Lembah Klang. Tesis Sarjana,
Universiti Kebangsaan Malaysia (tidak diterbitkan).
Magliulo,
P., Di Lisio, A. & Russo, F. 2009. Comparison of GIS-based methodologies
for the landslide susceptibility assessment. Geoinformatica 13(3):
253-265.
McDonald, A.J.W., O’Connor, E.A. & David, G.
2004. Rapid landslide susceptibility mapping. Conference on GIS and Remote
Sensing Application. hlm. 1-11.
Meneround, J.P. & Calvino, A. 1976. ZERMOS
Map, area exposed to risk linked to movement of soil and subsoil at 1: 25000.
Dlm. Landslide Hazard Assessment: Summary Review and New Perspectives, disunting
oleh Aleotti, P. & Chowdhury. Bulletin of Engineering Geology and the
Environment 58: 21-44.
Mezughi, T.H., Juhari, M.A., Abdul Ghani Rafek
& Ibrahim, A. 2012. Analytical hierarchy process method for mapping landslide
susceptibility to an area along the E-W highway (Gerik-Jeli), Malaysia. Asian
Journal of Earth Sciences 5(1): 13-24.
Mokhtar, J. & Mohd Afif, S. 2013. Potensi
tanah runtuh bagi cerun-cerun berhampiran kolej kediaman pelajar di Universiti
Kebangsaan Malaysia (UKM). Geografia Malaysian Journal of Society and Space 9(3):
107-115.
Mokhtar, J., Abdul Halim, Y. & Asiah, Y.
2011. Analisis tahap kebolehruntuhan tanah dengan menggunakan skala ROM: Kajian
di Kampus Universiti Kebangsaan Malaysia, Bangi. Geografia Malaysian Journal
of Society and Space 7(3): 45-55.
Nelson, A. & Dubem, K. 2015. Channel
response to an extreme flood and sediment pulse in a mixed bedrock and
gravel-bed river. Earth Surface Processes and Landforms 41(2): 178-195.
Nithya, S.E. & Prasanna, P.R. 2010. An
integrated approach with GIS and remote sensing technique for landslide hazard
zonation. International Journal of Geomatics and Geosciences 1(1):
66-75.
Norbazlan, M.Y. & Pradhan, B. 2014.
Landslide susceptibility mapping along PLUS expressways in Malaysia using
probabilistic based model in GIS. IOP Conference Series: Earth and
Environmental Science 20(1): 1-22.
Norbert, S., Juhari, M.A., Azlikamil, N. &
Tan, H.K. 2009. Pemetaan potensi bencana tanah runtuh menggunakan faktor
penilaian bencana tanah runtuh dengan pendekatan GIS. Bulletin of the
Geological Society of Malaysia 55: 47-53.
Nurfashareena, M. 2016. Bencana semulajadi di
kawasan tepu bina: Kajian kes sub-lembangan Langat, Malaysia. Tesis Doktor
Falsafah, Universiti Kebangsaan Malaysia (tidak diterbitkan).
Nurfashareena, M., Lim, C.S., Reza, M.I.H. &
Pereira, J.J. 2013. Input geologi untuk sistem sokongan membuat keputusan dalam
pengurusan risiko bencana: Kajian kes Universiti Kebangsaan Malaysia. Bulletin
of the Geological Society of Malaysia 59: 73-84.
Nuriah, A.M. & Wan Mohd Muhiyuddin. 2013.
Pemetaan zon kebolehrentanan kegagalan cerun di Pulau Pinang menggunakan
Rangkaian Saraf Buatan (ANN). Geografia Malaysian Journal of Society and
Space 9(1): 34-47.
Nuriah, A.M., Ruslan, R. & Wan Mohd
Muhiyuddin. 2017. Pemodelan ruangan pelbagai jenis kegagalan cerun di Pulau
Pinang menggunakan kaedah nisbah kekerapan. Geografi 5(2): 13-26.
Pradhan, B. 2010. Remote sensing and GIS-based
landslide hazard analysis and cross-validation using multivariate logistic
regression model on three test areas in Malaysia. Advances in Space Research 45(10): 1244-1256.
Pradhan, B.S. & Lee, S. 2010. Landslide
susceptibility assessment and factor effect analysis: Backpropagation
artificial neural networks and their comparison with frequency ratio and
bivariate logistic regression modelling. Environmental Modelling &
Software 25: 747-759.
Ramlal, B. & Baban, S.M.J. 2008. Developing
a GIS based integrated approach to flood management in Trinidad, West Indies. Journal
of Environmental Management 88: 1131- 1140.
Resources Inventory Committee. 1996. Guidelines
and Standards for Terrain Mapping in British Columbia. Government of
British Columbia. Victoria, B.C.
Saadatkhah, N., Azman, K. & Lee, M.L. 2014.
Qualitative and quantitative landslide susceptibility assessments in Hulu
Kelang area, Malaysia. Electronic Journal of Geotechnical Engineering 19:
545-563.
Saha, A.K., Gupta, R.P. & Arora, M.K. 2002.
GIS-based landslide hazard zonation in the Bhagirathi (Ganga) Valley, Himalaya. International Journal of Remote Sensing 23(2): 357-369.
Samy Ismail, E. & Mohamed, M.M. 2013.
Natural hazards susceptibility mapping in Kuala Lumpur, Malaysia: An assessment
using remote sensing and geographic information system (GIS). Geomatics,
Natural Hazards and Risk 4(1): 71-91.
Santangelo, N., Santo, A., Di Crescenzo, G.,
Foscari, G., Liuzza, V., Sciarrotta, S. & Scorpio, V. 2011. Flood
susceptibility assessment in a highly urbanized alluvial fan: The case study of
Sala Consilina (Southern Italy). Natural Hazards and Earth System Science 11(10):
2765-2780.
Sarkar, S., Kanungo, D.P., Patra, A.K. &
Kumar, P. 2006. GIS based landslide susceptibility mapping: A case study in
Indian Himalaya. Dlm. Disaster Mitigation of Debris Flows, Slope Failures
and Landslides. Tokyo: Universal Academy Press Inc. hlm. 617-624.
Shahabi, H. & Mazlan, H. 2015. Landslide susceptibility
mapping using GIS-based statistical models and remote sensing data
in tropical environment. Scientific Reports 5: Article number
9899.
Shahabi, H., Ahmad, B.B. & Khezri, S. 2013.
Evaluation and comparison of bivariate and multivariate statistical methods for
landslide susceptibility mapping (Case Study: Zab Basin). Arab Journal of
Geoscience 6: 3885-3907.
Shit, P.K., Bhunia, G.S. & Maiti, R. 2016.
Potential landslide susceptibility mapping using weighted overlay model (wom). Modeling
Earth Systems and Environment 2: 21.
Sina Alaghman, R.A., Ismail, A. & Vosoogh,
B. 2010. GIS-based river flood hazard mapping in urban area: A case study in
Kayu Ara River Basin, Malaysia. International Journal of Engineering and
Technology 2(6): 488-500.
Sinha, N., Priyanka, N. & Joshi, P.K. 2016.
Using spatial multi-criteria analysis and rangking tool (SMART) in earthquake
risk assessment: A case study of Delhi region, India. Geomatics, Natural
Hazards and Risk 7(2): 680-701.
Soeters, R. & Van Westen, C.J. 1996. Slope
instability recognition, analysis, and zonation. Dlm. Landslides,
Investigation and Mitigation, disunting oleh Turner, A.K. & Schuster,
L.R. Washington: National Academy Press. hlm. 129-177.
Tan, C.T. & Pereira, J.J. 2013. Management
of climate change and disaster risk. The Malaysia perspective. Dlm. Climate
Change and Disaster Risk Management, disunting oleh Filho, W.L. Berlin:
Springer-Verlag Berlin Heidelberg. hlm. 193-204.
Tehrany, M.S., Pradhan, B. & Jebur, M.N. 2015. Flood
susceptibility analysis and its verification using a novel ensemble support
vector mechine and frequency ratio method. Stochastic Environmental Research
and Risk Assessment 29(4): 1149-1165.
Temesgen,
B., Mohammed, M.U. & Korme, T. 2001. Natural hazard assessment using GIS
and remote sensing methods, with particular reference to the landslides in the
Wondegenet Area, Ethiopia. Physic and Chemistry of the Earth, Part C: Solar,
Terrestrial & Plenary Science 26(9): 665-675.
Van
Westen, C.J. 1994. GIS in landslide hazard zonation: A review, with examples
from the Andes of Colombia. Dlm Mountain Environments and Geographic
Information System, disunting oleh Price, M. & Heywood, I. London:
Taylor & Francis.
Wan
Mohd Muhiyuddin, W.I. & Ruslan, R. 2004. Modelling landslide using GIS and
RS: A case study of upper stream of Langat River Basin, Malaysia. Malaysian
Journal of Environmental Management 5: 113-122.
Zulfahmi,
A.R., Sahibin, A.R., Jasni, Y. & Wan Muhd Razi, I. 2007. Tinjauan awal
potensi ketidakstabilan cerun dan cirian fiziko-kimia tanah di Cameron
Highlands, Pahang. Sains Malaysiana 36(2): 105-116.
*Pengarang
untuk surat-menyurat; email: joy@ukm.edu.my
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