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

 

Received: 14 February 2018/Accepted: 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

REFERENCES

 

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.

 

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

 

 

 

 

previous