BASIC DETAILS Paper reference number : MWF PN 121 Title of the paper Name of the Presenter Author affiliation Mailing address Email address : Extraction of Topographic and Morphometric features for landslide zonation A case study for Ooty Mettupalayam highway : Mr. S. Vasantha Kumar : GIS Engineer : Centre for Disaster Mitigation and Management (CDMM), VIT University, Vellore 632 014 : vasanth_research@yahoo.co.in Telephone number : 94440 50435 0416-2243092 Author s photograph : Brief bio data : Mr.S.Vasantha Kumar received Masters Degree in Geoinformatics from Institute of Remote Sensing, Anna University (2005).He handled classes & labs for M.Tech Remote Sensing at PSNA Engineering College, Dindigul, Tamilnadu. He guided 3 PG projects. His articles on Soil contamination & Accident analysis was published in THE HINDU & Dinamalar. He had published 10 papers out of which 9 in National Conferences & 1 in International Conference.
EXTRACTION OF TOPOGRAPHIC AND MORPHOMETRIC FEATURES FOR LANDSLIDE ZONATION A CASE STUDY FOR OOTY METTUPALAYAM HIGHWAY S.Vasantha Kumar 1 N.Raja 2 G. Prasad Babu 3 1,2 GIS Engineer, Centre for Disaster Mitigation and Management, VIT University, Vellore, Tamilnadu, India 3 Geological Specialist, Centre for Disaster Mitigation and Management, VIT University, Vellore, Tamilnadu, India Abstract In hilly regions, landslides constitute one of the major hazards that cause losses to lives and property. Landslide analysis is a complex analysis, involving multiple of factors and it needs to be studied systematically in order to locate the areas prone for landslides. The topographic & morphometric features play an important role in deciding the areas prone to landslide. In this paper an attempt has been made to derive the topographic features such as slope, aspect, various convexities and curvatures and morphometric features such as peak, ridge, pass, plane, channel and pit for Mettupalayam- Udhagamandalam ghat section of length 54 Kilometers. The 1: 50000 scale Survey of India toposheets were used to derive contours of 20m intervals. The digitized vector contour was then converted to Digital Elevation Model (DEM) using the topographic functions of ENVI 4.3. The pixel size of output DEM was set no smaller than the contour interval in an attempt to reduce interpolation artifacts. The DEM was then used to derive topographic features such as slope, aspect, and various convexities and curvatures. All of the parameters are calculated by fitting a quadratic surface to the digital elevation data for the entered kernel size and taking the appropriate derivatives. The profile convexity measures the rate of change of the slope along the profile. The plan convexity measures the rate of change of the aspect along the plan. The longitudinal curvature and crosssectional curvature are also measures of the surface curvature orthogonally in the down slope and across slope directions. Also the minimum and maximum overall surface curvatures are calculated. Finally an output image that classifies each pixel into one of the following terrain types or morphometric features: peak, ridge, pass, plane, channel, or pit was generated. The slope and curvature of the surface determines the morphometric feature. For example, a sloping surface that is concave in the cross-sectional direction is a channel. A sloping surface that is convex in the cross-sectional direction is a ridge. Peaks have a
convex cross-section and convex longitudinal curvature while pits have concave curvatures. These derived products if viewed in 3D surface view will be useful in enhancing the preparation of hazard zonation maps and would pave way for effective decision making for various development and regulatory activities in the mountainous regions. 1. INTRODUCTION Landslides occur as a consequence of a number of triggering factors. In order to assess landslide susceptibility it is necessary to identify and analyze the factors leading to landslide. In any landslide susceptibility model, the various factors along with their weightages are lithology (0.3), slope (0.25), landcover type (0.25), curvature (0.1), distance to structural elements (0.05) and aspect (0.05). Of the above factors the slope, aspect and curvature were given a total of 40% weightage [1] which clearly implies its importance in identifying landslide prone areas. A cost effective method of extracting these topographic parameters is the use of existing Toposheets. The contour also makes its possible to identify morphometric features such as peak, plane and passes etc. The use of these topographic & morphometric features has its real world application in studying landslide prone areas via generating various maps within GIS. The Nilgiris in Western Ghats has taken as the study area as it entered an anxious era of landslides since the calamitous landslides of 1978. The frequency of landslides has increased in recent years with major slides occurring in 1993, 1995, 2002 and recent landslides of November 2006 [2].The objective of the study is to establish a relationship between various triggering factors and landslide occurrence and to generate maps of landslide prone areas which would help effective decision making for various development and regulatory activities in the mountainous regions. 2. STUDY AREA The Mettupalayam Udhagamandalam ghat section of length 54 kilometers has taken as the study area to identify the landslide prone areas. The highway is an extension of NH-67 connecting the states Tamil Nadu and Karnataka. The highway passes through important towns like Coonoor, Gudalur and Bandipur in Karnataka. Heavy landslides in this area have often resulted in diversion of the vehicular traffic to utilise the alternate Mettupalayam-Kothagiri road instead of the Mettupalayam-Ooty road, which consumes more time of travel between the two points. The study area is limited to 500m on either side of the Ooty Mettupalayam highway as the worst ever landslide is only 150m width (an average 1,000 metres in length and displacing three million tonnes of earth and rock debris) occurred in 1993.The area encompasses a total of 39.149 square kilometer and bounded between 76 42 and 76 56 E longitudes and 11 18 and 11 25 N latitudes. The elevation ranges between 300m and 2500m above MSL.
3. PREPARATION OF BASE MAP The Survey of India (SOI) Topo sheets were used in the preparation of base map at a scale of 1: 50000. The topo sheets numbered 58 A/15 and 58 A/11 was used to derive the features of ghat road of length 54 kilometers and contours of 20m interval. A total of 32 control points was used to georeference the base map. The road was buffered to 500m on either side and contours were digitized within that buffer using ArcGIS 9.2. The elevation values were added as attribute to each contour. The elevation varies between 300m at Mettupalayam and 2480m at Udhagamandalam. The base map is shown in Fig.1. Fig.1. Base map showing road & contour 4. STUDY OF TOPOGRAPHIC FEATURES The contour to DEM option of ENVI 4.3 is used to derive the Digital Elevation Model (DEM). The pixel size of output DEM was set to 30m, no smaller than the contour interval of 20m in an attempt to reduce interpolation artifacts. The Digital Elevation Model of 30m pixel size is shown in Fig.2.
Fig.2. Digital Elevation Model The DEM was then used to derive topographic features such as slope, aspect, and various convexities and curvatures. All of the parameters are calculated by fitting a quadratic surface to the digital elevation data for the kernel size of 3 3 as large kernel sizes may run slower and taking the appropriate derivatives. 4.1. INFLUENCE OF SLOPE & ASPECT ON LANDSLIDES In the case of the relationship between landslide occurrence and slope, landslide probability increases according to slope angle. As the slope angle increases, then the shear stress in the soil or other unconsolidated material generally increases. Gentle slopes are expected to have a low frequency of landslides because of the generally lower shear stresses associated with low gradients. The slope was classified into four categories based on its slope angle as gentle slope, moderate slope, steep slope and very steep slope and is shown in Fig.3.
Fig.3. Slope map The area covered by each categories of slope along with its influence on landslide susceptibility is given in Table 1. Slope type Criteria used Area covered in Sq.km Landslide susceptibility Gentle slope 0-18 degree 16.037 Low Medium slope 18-36 degree 10.089 Medium Steep slope 36-54 degree 9.081 High Very steep slope > 54 degree 3.940 Very high Table 1. Area covered by each slope categories As expected the landslide prone areas of Burliar & Marapalam falls under steep slope category which clearly shows that a heavy rainfall is sufficient to make the rocks and boulders come hurtling down in these steep terrains, that s what happened in the recent landslide occurred in November 2006, a few months before. The aspect map was prepared from the slope map and is shown in Fig. 4. The direction of slope was divided into eight divisions as seen from the legend. Fig 4. Aspect map Most of the places are sloping towards south & south west and Burliar the place where frequent landslides are occurring is bounded between south east & south west
facing slopes. Therefore, a road tunnel is a safe proposition between Burliar and Coonoor to avoid landslips from both the sides. The relationship between aspect & landslides can be well defined if one overlaid the past landslides information especially the details about the direction along which the mass movement happened. 4.2. INFLUENCE OF CURVATURE ON LANDSLIDES To establish the relationship between landslide occurrence and curvature, the profile convexity and plan convexity measures were used. The profile convexity measures the rate of change of the slope along the profile. The plan convexity measures the rate of change of the aspect along the plan. In a convexity map a positive curvature indicates that the surface was convex at that grid/cell. A negative curvature indicates that the surface was concave at that grid. A value of zero indicates that the surface was flat. During a heavy rainfall, a concave slope contains more water and retains this water for a longer period, the more negative a value is, the higher is the probability of a landslide occurrence. The map of profile convexity is shown in Fig.5 The curvature values ranges between -2.474 to +2.323 and divided into three categories as Negative curvature, Flat and Positive curvature. The flat areas are the one having zero curvature and it is seen from the figure that most of the places are having negative curvature which may increase the landslide susceptibility as it approaches the extreme value of -2.474. Fig 5. Map of Profile Convexity 5. STUDY OF MORPHOMETRIC FEATURES
The slope and curvature determines the morphometric feature. The Topographic modeling function of ENVI was used to derive an output image that classifies each pixel into one of the following terrain types or morphometric features: peak, ridge, pass, plane, channel, or pit as shown in the Fig.6. Fig 6. Map showing morphometric features For example, a sloping surface that is concave in the cross-sectional direction is a channel. A sloping surface that is convex in the cross-sectional direction is a ridge. Peaks have a convex cross-section and convex longitudinal curvature while pits have concave curvatures. The morphometric parameter which is of prime importance in landslide is channel. As seen from the figure, in most places the channel/ drainage line flows across the road, which implies that the provision of proper drainage is a must to avoid landslips especially during heavy rainfalls. The recent landslips which occurred few months before is mainly due to heavy rainfall followed by massive landslips. 6. CONCLUSION The following conclusions were derived from the study. 1. Landslide prone areas of Burliar & Marapalam falls under steep slope category which clearly shows that a heavy rainfall is sufficient to make the rocks and boulders come hurtling down in these steep terrains. 2. Most of the places are sloping towards south & south west and Burliar the place where frequent landslides are occurring is bounded between south east & south west facing slopes. Therefore, a road tunnel is a safe proposition between Burliar and Coonoor to avoid landslips from both the sides. The relationship between aspect & landslides can be
well defined if one overlaid the past landslides information especially the details about direction along which the mass movement happened. 3. Most of the places are having negative curvature which may increase the landslide susceptibility as it approaches the extreme value of -2.474. 4. In most places the channel/ drainage line flows across the road, which implies that the provision of proper drainage is a must to avoid landslips on roads especially during heavy rainfalls. REFERENCES 1. M. Komac, M. Ribicic, Landslide susceptibility map of Slovenia at scale 1 :250.000, Geophysical Research Abstracts, Vol. 8, 03990, 2006. 2. Article titled Re-crowning the Queen of Hills in THE HINDU dated April 27, 2003. 3. S. Lee a, Digna G. Evangelistab, Landslide Susceptibility Mapping using Probability and Statistics Models in Baguio City, Philippines, Department of Environment and Natural Resources, North Avenue, Diliman, Quezon City, Philippines. 4. S.S. Ramakrishnan et al, Landslide Disaster Management and Planning- A GIS based Approach, Indian Cartographer, 2002, pp 192-195.