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GIS Based Determination of Landslide Location by Sheryl Lin Kuok Tyng

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GIS Based Determination of Landslide Location by Sheryl Lin Kuok Tyng GIS Based Determination of Landslide Location by Sheryl Lin Kuok Tyng Dissertation submitted in partial fulfillment of the requirements for the Bachelor of Engineering (Hons) (Civil Engineering) SEPTEMBER 2014 Universiti Teknologi PETRONAS Bandar Seri Iskandar 31750 Tronoh Perak Darul Ridzuan I FINAL YEAR PROJECT DISSERTATION GIS Based Determination of Landslide Location Sheryl Lin Kuok Tyng 14438 Civil Engineering Supervisor: Associate Professor Dr. Indra Sati Hamonangan Harahap II CERTIFICATION APPROVAL GIS Based Determination of Landslide Location by Sheryl Lin Kuok Tyng A project dissertation submitted to the Civil Engineering Programme Universiti Teknologi PETRONAS in partial fulfillment of the requirement for the BACHELOR OF ENGINEERING (HONS) (CIVIL ENGINEERING) Approved by, __________________________________ (Associate Professor Dr. Indra Sati Hamonangan Harahap) UNIVERSITI TEKNOLOGI PETRONAS TRONOH, PERAK September 2014 III CERTIFICATION OF ORIGINALITY This is to certify that I am responsible for the work submitted in this project, that the original work is my own except as specified in the references and acknowledgements, and that the original work contained herein have not been undertaken or done by unspecified sources or persons. ___________________________ SHERYL LIN KUOK TYNG IV ABSTRACT This paper discusses about the Landslide Hazard Assessment (LHA) conducted on Cameron Highlands for October 2013. This site is identified as one of the very susceptible to landslides. In tropical countries such as Malaysia, rainfall is considered as the triggering factor of a landslide. Therefore, the information was obtained from rainfall station gauges to be used in Geographical Information System (GIS) by Kriging interpolation method. The variables including slope, slope aspect, curvature, land use land cover (LULC), elevation, distance from road, distance from river/lake and distance from lineament were used in the GIS system. The system managed to identify few areas that are highly susceptible to landslide using rainfall data on 23rd October 2013. However, it did not manage to identify the area that had mudflow reported on that day with the Landslide Hazard Zonation (LHZ) map produced. This paper provides recommendations to be done in future work in order to obtain more accurate results. Keywords: Landslide Hazard Assessment; GIS; rainfall interpolation; Cameron Highlands; weighted overlay V TABLE OF CONTENTS List of Figures VII List of Tables VII List of Abbreviations VII Chapter 1: Introduction 1.1 Background 1 1.2 Problem Statement 2 1.3 Objective of Study 2 1.4 Scope of Study 3 1.5 Relevancy and Feasibility of the Project 4 Chapter 2: Literature Review 2.1 Introduction 5 2.2 GIS Application in Landslide Prediction 5 2.3 Triggering and Causative Factors 7 2.4 Spatial Interpolation Methods 11 2.5 Summary 13 Chapter 3: Methodology 3.1 Introduction 15 3.2 Research Methodology 16 3.3 Project Activities 17 3.4 Key Milestone 18 3.5 Gantt Chart 20 3.6 Tools required 21 3.7 Landslide Hazard Assessment 21 3.8 Summary 23 VI Chapter 4: Results and Discussion 4.1 Introduction 24 4.2 Results and Discussions 24 4.3 Final Output 34 4.4 Recommendations 35 4.4 Summary 36 Chapter 5: Conclusion and Recommendations 5.1 Introduction 37 5.2 Conclusion 37 5.3 Summary 38 References 39 Appendix 41 VII LIST OF FIGURES Figure 1 shows study area Figure 2 shows flowchart of landslide hazard prediction Figure 3 shows GIS Layers Figure 4 shows rain gauge stations available in Cameron Highlands, Pahang Figure 5 shows rain gauge (Tipping Bucket) Figure 6 shows research methodology Figure 7 shows research activities Figure 8 shows ArcToolbox with Kriging options Figure 9 shows station location with JUPEM data Figure 10 shows after kriging of rainfall station Figure 11 shows color code and values Figure 12 shows contour lines Figure 13 shows curvature layer Figure 14 shows slope aspect layer Figure 15 shows slope layer Figure 16 shows elevation layer Figure 17 shows Land Use Land Cover (LULC) layer Figure 18 shows roads after buffer Figure 19 shows river/lakes after buffer Figure 20 shows lineament after buffer Figure 21 shows weighted overlay toolbox Figure 22 shows final output VIII LIST OF TABLES Table 1 shows the weighting system for each layer used Table 2 shows the types of data and sources Table 3 shows station location and coordinates with rainfall data LIST OF ABBREVIATIONS LHA Landslide Hazard Assessment GIS Geographical Information System DID Department of Irrigation and Drainage MMD Malaysia Meteorological Department JUPEM Jabatan Ukur dan Pemetaan Malaysia CRS Coordinate Reference System LHZ Landslide Hazard Zonation IX CHAPTER 1 INTRODUCTION 1.1 BACKGROUND Landslides are known as one of the natural disasters that destroy properties and claim lives. Landslide is described as a “movement of rock, debris, or earth down a slope” which may happen in five distinct mechanisms which are falling, toppling, spreading, flowing and sliding [1]. In Malaysia, Cameron Highlands is one of the areas that are known to be prone to landslides. Thus, it is important to identify the potential landslide sites to minimize the damages caused by landslides. Landslide hazard assessment serves as an early warning system by developing a landslide susceptibility map that could help planners or authorized personnel to plan out suitable mitigation methods in areas that are prone to landslides. In the hazard assessment, there are various parameters that could be the triggering factor to a landslide depending on the study area such as slope aspect, soil stratigraphy, types of soil, distance to road and etc. In this study, the triggering factor that will be studied is the rainfall data. Statistics have shown that rainfall has a direct relationship with landslide. This study will encompass the data from rainfall gauges to correlate the relationship between the amount of rain and its effect on landslide. There are various ways of conducting landslide hazard assessment but little work or studies are done by applying GIS. GIS can be applied in this hazard analysis to create a dynamic database to control and manage the hazards should there be any changes to the geological or topography data to assess the landslide hazard. It is an easier method to model changes and reduces repetitive manual work. 1 1.2 PROBLEM STATEMENT The main triggering factor of a landslide is usually rainfall. In Malaysia, the average precipitation in depth (mm per year) was 2875 mm measured in 2009 and landslide is ranked second after floods as the most frequent natural disaster. There is minimal work done on the early warning system to predict the landslide before it actually happens. It could warn the community about the hazard. In order to learn more about landslide in Cameron Highlands, which is one of the identified areas in Malaysia [2]that is prone to landslides due to its location at the main range known as Banjaran Titiwangsa, this qualitative research aims to study the correlation between landslide and rainfall characteristics using GIS. This study aims to improve the understanding of correlation between rainfall and landslides particularly in Cameron Highlands. The impacts of landslides can be seen through past incidents which will be further elaborated in literature review. 1.3 OBJECTIVES OF STUDY The objectives of this study are (i) To develop a qualitative landslide hazard map based on GIS and rainfall characteristics (ii) To evaluate the accuracy of the developed landslide hazard map 2 1.4 SCOPE OF STUDY The scope of study in this research focuses on developing a qualitative landslide hazard map in Cameron Highlands. Rainfall gauge station data that is provided by DID will be processed to interpolate the amount of rainfall on the covered area which will be further elaborated on the methodology. The rain data will be weighted accordingly which will be used to overlay with other spatial data such as slope, slope aspect and curvature. With the weighting system, GIS will be able to map out the areas that are prone to landslides, which is the hazard zonation map. As the figure below depicts the whole Peninsular Malaysia, this is the study area concentrated in the state of Pahang, particularly in Cameron Highlands, where the border is highlighted in pink. Kelantan Perak Pahang Figure 1: Study Area 3 1.5 RELEVANCY AND FEASIBILITY OF THE PROJECT Rainfall is an important triggering factor to landslide, especially for tropical countries such as Malaysia where rainfall happens all year round. Moreover, this study covers the area of Cameron Highlands, where this area is prone to landslides due to its geographical location at the main range. It is thus, essential to study rainfall as an early warning system that could help to minimize damages and avoid loss of lives. Geotechnical engineers could use this qualitative method to consult and advise town planners to avoid extreme urbanization at areas that are prone to landslides. This could also help government bodies to suggest suitable mitigations and to allow more funds into preventing than curing the effects of a landslide. The project is feasible within the scope, time frame and budget given. The scope and main objectives had been clearly defined and narrowed, so that the author managed to complete the study within the time frame. A hazard zonation map could be produced within the time frame with the defined boundaries and scope. 4 CHAPTER 2 LITERATURE REVIEW 2.1 INTRODUCTION This chapter presents the literature review on GIS and its application in landslide prediction. Besides that, this chapter also presents the literature review on the factors affecting a landslide susceptibility with regards to Cameron Highlands. The last part explains the types of spatial interpolation available in ArcGIS and the method the author has chosen to use. 2.2 GIS APPLICATION IN LANDSLIDE PREDICTION Environmental System Research Institute (ESRI) defined “GIS integrates hardware, software, and data for capturing, managing, analyzing, and displaying all forms of geographically referenced information”.
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