Mapping Landslide Prone Areas in Ooty Region, South India Using Remote Sensing, Geographic Information System and Geotechnical Data

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1 Mapping Landslide Prone Areas in Ooty Region, South India Using Remote Sensing, Geographic Information System and Geotechnical Data P. Rajakumar 1* and S. Sanjeevi 2 1 Assistant Divisional Engineer, Information Technology Cell, Highways Department, Chennai , India 2 Professor, Department of Geology, Anna University, Chennai , India Abstract Landslide is one of the natural hazards which occur mostly in the hilly areas including Ooty town in south India. Deforestation, changing landuse practices, formation of new roads, slope cuttings are continuous processes in and around Ooty, leading to landslide. This study is an attempt to identify landslide prone areas along roads a part of Ooty region. Landuse and lineament maps are prepared from Indian Remote Sensing satellite (IRS 1D LISS III) imagery. Digital Elevation Model (DEM) was derived from 20 m contours and slope, aspect, road and drainage maps were prepared from the 1:50,000 scale Survey of India topographic map. Engineering properties and depth of soils available at various locations were estimated and engineering soil classification and soil depth thematic maps were prepared. Proper rank and weightage for factors influencing landslides were assigned for each thematic map. Overlay analysis using GIS software resulting a map showing the severity of landslide likely to occur in various areas. Limited field check carried out confirms the results of this study. Thus, it is seen that Remote Sensing and Geographic Information System (GIS) coupled with geotechnical studies are well suited for identifying landslide prone areas. Key words: Landslide; GIS; Remote Sensing; geotechnical survey; Indian Remote Sensing Satellite, DEM; Ooty 1. Introduction Landslide may be defined as the movement of a mass of rock, debris or earth down a slope under the influence of gravity, when the shear stress exceeds the shear strength of the soil. Landslides can be soil-slides or rock-slides or a combination of both. The main causes of landslide are blocking of natural outlets, more infiltration than drainage, natural or artificial rise of water table, capillary water and seepage from artificial flow, toe removal of slope, indiscriminate canal, road, railway cutting, terracing for agriculture or constructional work, increase of head load on slope top, inadvertent location of plantations, factories and settlement, frequent changes in land use practices (Seshagiri et al. 1982). Steep terrain and high intensity of rainfall make landslide occurrence frequent in hilly terrains (Dai and Lee 2002). The other causes include cohesion, angle of internal friction, slope and relative height, direction of slope (aspect), proximity to drainage, vegetation and distance from major faults (Gokceoglu and Aksoy 1996). Natural or artificial influence includes undermining of the foot of slope by stream erosion or by excavation. Intense rainfall in association with the increase in human activities has also contributed to increase instability of slopes (Bhasin et al. 2001). In the Indian sub-continent, three major regions are more prone to landslides. They are the Himalayas in the north, Western Ghat hill ranges in the south west and the Nilgiris in the south. The important factors for these landslides are active tectonics in the Himalayas, slope erosion and rock-fall in the Western Ghats and rainfall in the Nilgiris (Seshagiri et al. 1982). This study deals with the preparation of a landslide-prone 2017 AARS, All rights reserved. * Corresponding author: prkgtmsa@yahoo.co.in Phone:

2 Mapping Landslide Prone Areas in Ooty Region, South India Using Remote Sensing, Geographic Information System and Geotechnical Data area map by using remote sensing, Geographical Information System, analysis of soil samples from the field and by limited field check in the Ooty region. A landslide hazard zonation map is useful for selecting suitable locations to implement developmental schemes in the Ooty mountainous region as well as for adopting mitigate measures in very high hazard zones. An attempt has been made to suggest suitable remedial measure for the highly susceptible zones. Accordingly the objectives of this study are i) To study and analyse the various factors that are responsible for triggering landslides in the study area using soil data, Remote Sensing and GIS with limited field survey. ii) To demarcate the probable landslide hazard zones in the study area. 2. The Nilgiris: Nilgiris is mostly a hill district located on Western Ghats hill ranges of India with an elevation of 300m above msl in Moyar Gorge to 2634m above msl in Doddabeta peak. The average annual rain fall is nearly mm. About 56% of the district is under forest cover and 20% is under tea, coffee, arecant, coconut and plantation. Grasslands, shola, eucalyptus, pine and other forest plantations are also seen in the district. Varying altitudes, high rainfall, varying temperature regimes have endowed Nilgiris with a diverse natural heritage (Hegde et al. 2001). The micro-climate conditions vary depending on the degree of slope, aspect, vegetation condition and soil condition. Normally, along the foothills and in broad valley region, summers are quite warm and at higher altitudes, winters are chill and severe. The region witnesses three distinct seasons. They are: i) Rainy season (June-November), ii) Winter (December-February) and iii) Summer (March-May). About 58% of the total rainfall is received through southwest monsoon and about 30% through north-east monsoon and pre-monsoon showers of 3% during the winter month (January and February) and about 9% during the summer month (between march and may),on an average, Nilgiri encounters 0 rainy days per year The area comprises archaean metamorphic rocks which include charnockite, biotite gneiss, magnetic quartzite, hornblende granulite, pegmatite, dolerite and quartz veins. Most of the lineaments identified on the IRS 1D LISS III imagery represent fractures in the Nilgiri plateau and adjoining regions along which there may or may not have been movement. Intense precipitation followed by dry periods has helped in the formation of considerable depth (up to 40 m) of weathering. On the Nilgiris plateau, laterite capping are found in large areas, over the charnockites, which are hard and aluminous (Seshagiri et al. 1982). The rocks found in Nilgiri district are of deep seated metamorphic origin and have undergone considerable deformation in Precambrian times. The regional foliation is towards eastnorth-east with steep dips. Generally two types of landforms have been identified in the district: the gentle mounds with thick soil development, stream meandering and general smoothening of hills. A greater part of Nilgiri is deeply weathered, as a result, development of thick soil is a common feature. A number of severe and major landslides in the Nilgiris occurred during 1978, when more than 0 landslides were recorded within an area of 250-squre kilometer. In 1979, more than 200 landslides were reported in the same area. In 1992, numerous landslides were occurred, causing damage to the roads and private property in the Coonoor region. During 1993, about 408 landslides have been reported, of which Marappalam area of the Coonoor region is the most severe one (Balachandran et al. 1996). 3. Study Area The study covers a region of the Coonoor to Ooty road stretch and is located in Nilgiris district, a mountainous terrain in the North West part of Tamil Nadu. It falls in the Survey of India topographic map number 58 A / 11 on 1: 50,000 scale (Figure 1). The area covers km x 14 km in east west and north south direction. Over 500 hotels and lodging houses, hundreds of restaurants and countless retailers depend on the tourist trade. Agriculture and horticulture activities are the main landuse practices. Indiscriminate extension of roads has been a main contributory factor for the growing geological instability of the region. Due to speedy completion of road projects, important geological considerations like selection of road alignment through reconnaissance and survey often do not get the attention they deserve. Again, due to considerations of economy and concern for speed, authorities have a tendency to restrict stabilization, drainage and protective measures (The Hindu, 2003). 4. Methodology The methodology used for this study is as follows. Landuse map and lineament maps are prepared from the IRS 1D LISS III satellite imagery by visual interpretation. Contour map was created from the Survey of India (SOI) topographic map and converted in to digital format. From that Triangulated Irregular Network (TIN), slope and aspect map are created. Drainage map is also generated from the SOI topographic map. Drainage frequency map of 0.50 x 0.50 km grid was prepared manually and converted into digital format. Soil map is drawn from Geological Survey of India map on 1: 50,000 scale and digitized for converting into digital format using GIS software and transformed into World Co-ordinate 2

3 Asian Journal of Geoinformatics, Vol.17,No.2 (2017) Figure 1. Location map of the study area. System for overlay analysis. Road network map is also drawn from SOI topographic map and buffer operation is carried out. From the field, soil samples are collected at various locations and depths, and then laboratory test was carried out and soil type and soil depth thematic maps are created and converted into digital format. All the thematic maps are converted into world co-ordinate system and proper rank and weights are assigned and overlay analysis is carried out. The result is a map showing landslide prone areas of various categories. Validation was carried out by extensive field survey. 5. Result and Discussion This study involves the use of Remote Sensing and GIS for an analysis of the various factors that are responsible for the occurrence of landslides in Ooty area. These factors are discussed in detail as follows:- 5.1 Landuse Landcover is one of the major factors for influencing the occurrence of landslides. Frequently changing the vegetation cover often results in modified landslide behavior (Glade 2002). From various investigations it is learnt that landuse / vegetation cover, especially of a woody type with strong and large root system helps to improve the stability of slopes (Gray and Leiser 1982). Deep-rooted vegetation (forest) that stabilized the top soil was a very important factor lowering landslide hazard especially as slope increased in southern Honduras (Perotto-Baldiviezo et al. 2003). According to Greenways (1987) vegetation roots penetrate throughout the soils and increase their shear strength. The areas with denser vegetation were considered to be less susceptible to sliding with respect to the area with less or no vegetation (Gokceoglu and Aksoy 1996). However, in Dehradun and Mussoorie in India, 91% of the landslides occurred in non-forested areas (Panikkar and Subramanyan 1996). The root system of the Figure 2. Landuse map of the study area. vegetation in the forest increases the shear resistance of the mass and through creation of negative pore pressure, increases soil cohesion (Seshagiri et al. 1982). Landuse changes in the study area indicate that some activities have taken in the particular area i.e forest land might have been converted in to agriculture or some other landuse. In this study, IRS 1D LISS III imagery was interpreted for preparing landuse / landcover map on 1: 50,000 scale (Figure 2) by visual interpretation method. In this study area, landuse is categorized into nine types. They are urban, rural, tea / coffee, vegetable / potato, waterbody, open to dense forest, forest plantation; open to dense scrub and paddy / sugar. Of the total area 51% fell under vegetables /potato cultivated areas, 13% under forest and 11% under tea / coffee plantation. Tea / coffee plantations were generally found on the slopes. Rank for all the landuse categories were assigned (Table 1) 3

4 Mapping Landslide Prone Areas in Ooty Region, South India Using Remote Sensing, Geographic Information System and Geotechnical Data Table 1. Ranks for landuse categories in the study area Landuse / landcover Rank Landslide frequency Area in percentage Urban Rural Tea / Coffee Vegetable / potato Waterbody Open to dense forest Forest plantation Open to dense scrub Paddy / sugarcane after careful observation and studying the relative significance of each landsue unit in landslide associated hazards. From the statistical analysis it was ascertained that in the Nilgiris, most of the landslides are occurred along the roads and railway line, fallow and intermittently cultivated areas, slopes with tea and coffee cultivated areas and settlement as compared to forest area where the frequency was less Slope Slope constitutes an important parameter in landslide studies, since its stability form the basis for the frequency and intensity of landslide. It may be defined as a plane tangent to the surface at any given point and may be measured in degrees or in percentage. Slope gradient has a great influence on the susceptibility of slope to landslide. The landslide frequency is generally higher for concave side slopes, and for rock outcrop followed by straight side slopes. As slope increases, the percentage of land affected by landslides may also increase. Storms quickly saturate the topsoil creating landslide hazard on steep slopes that were not stabilized by deep roots or physical barriers. Bare soils, crops and grass fallow cover types have the highest frequency of landslides as slopes increase. Deeprooted vegetation that stabilizes the topsoil is a very important factor lowering landslide hazard especially as slopes increase. On steep slopes, landslide hazard is about 13 times greater on bare soil ground than on forest and about five times greater on sites under crop production or grass fallow than on forest (Baldiviezo et al. 2004). The study of Gokceoglu and Aksoy (1996) showed that around Mengen, NW Turkey landslides occurred at locations where slope angles exceed 20. It was reported by Baldiviezo et al. (2003) that occurrence of landslide increased dramatically in areas in southern Hounduras where slope is between 6º and 45º. The occurrences of many landslides in Nilgiris were in the slope range of 18 to 45 (Panikkar and Subramanyan 1996). In 1993, the Marapalam landslide near Coonoor took place in slope forming material on a slope of about 30 (Balachandran et al. 1996). Dai and Lee (2002) reported that landslide was imum, when the slope angle between 35 and 40 and it decreases when slope is > 40. Bhasin et al. (2002) reported Figure 3. TIN derived slope map of the study area Table 2. Rank for slope categories Sl. No. Slope in degrees Rank > 45 3 that in the Chanmari landslide at Gangtok, Sikkim Himalaya, the terrain in the source area had an average slope of about 31. In this study, slope angle was derived and used as one thematic layer for landslide analysis (Figure 3). Contour lines were digitized from the Survey of India topographic maps. TIN (Triangulated Irregular Network) model for the study area has been developed from the digitized contour map. TIN is a terrain model that uses a sheet of continuous, connected triangular facets based on a delaunay triangulation of irregularly spaced nodes or observation points (Burrough and McDonnell 1998). It was inferred that most of the study area falls under the 4

5 Asian Journal of Geoinformatics, Vol.17,No.2 (2017) Figure 4. DEM of the study area slope ranging between 26 and 90. The slope (in degree) is grouped in to 4 types (Table 2). It was observed from the field with the help of GPS survey, the slope range of 26 to 45 is more susceptible to landslides. Hence, a higher rank value is assigned to this category. Slopes greater than 45 are mostly of rocky and partially weathered rock, and are less susceptible to landslide, hence low rank was assigned Drainage One of the major influencing elements for the occurrence of landslides in hilly areas is drainage. Drainage frequency describes the degree of topographic dissection of the landscape. Higher drainage density means higher probability of the occurrence of mass failure. As the distance from the drainage line increases, landslide frequency generally decreases. Streams may affect the stability by either eroding the toe or saturating the slope. Terrain modification caused by gully erosion may also influence the initiation of landslide (Dai and Lee 2002). To understand the role of drainage in the Ooty region, a drainage map (Figure 5) was prepared from topographic map on 1: 50,000. The drainage is radial at many locations because of dominant high peaks. It is influenced mainly by the joint pattern and foliation trends of the rocks. In the study area, the incidents of landslides are more in radial with local dendritic to sub-dendritic drainage pattern (Seshagiri et al. 1982). The drainage map was overlaid on a grid cover of size 0.50 km x 0.50 km. The number of drainage lines present in each grid is counted which will give the drainage frequency value; from that drainage frequency map was prepared. The study area has been classified in to 8 types based on the drainage incidences. Proper ranks (Table 3) are assigned to Figure 5. Drainage map of the study area Table 3. Rank for drainage frequency Table 3. Rank for drainage frequency No.of drainage lines Rank per 0.25 km² grid the drainage frequency map for overlay analysis Lineament Incidence and Intersection Map Lineament represents features such as fracture, joints, faults, bedding, and ridges etc. The influence of these structures is conducive to infiltration and development of hydrostatic pressure on the slope forming material (Nagarajan et al. 1996). Faults and landslides have a close association; about 88% of the landslides were detected around Mengen, NW Turkey within an area closer than 250 m to major faults (Gokceoglu and Aksoy 1996). In the Song river section in India, all the landslides occurred on the escarpment side on the fault scarps, with the formations dipping into the hill (Panikkar and Subramanyan 1996). Study of lineaments in the form fractures and beddings are paramount in the analysis of landslide prone areas in the study area. 5

6 Mapping Landslide Prone Areas in Ooty Region, South India Using Remote Sensing, Geographic Information System and Geotechnical Data Table Table Ranks Ranks for for lineament lineament incidence incidence No. of occurrences Rank Table 5. Ranks for lineament incidence No. of intersections Rank Table 6. Rank for aspect (direction of slope) Direction Rank Flat 1 North, NE 2 East, SE, NW 3 West 4 SW 5 South 6 A lineament incidence map was prepared using IRS ID LISS III image data and taken as a factor that induces landslide in the study area. Most of the lineaments identified represent fractures in the Nilgiri plateau and adjoining regions along which there may or may not have been movement. There are also zones of sheared rocks which are away from the lineaments. The strikes of the four sets of joints are towards east-north-east, north-east, north-north-west and north-west respectively with steep dips (Seshagiri et al. 1982). The map was overlaid on a 0.50 km x 0.50 km grid size and the number of lineaments present in each grid was counted which gives the lineament frequency value. The final map was digitized and converted to digital form. An order of importance has been arrived based on the density level of lineaments and ranks are assigned accordingly (Table 4). To study the role of lineament intersection, the lineament map was overlaid manually with a gridded cover of grid size equal to 0.50 km x 0.50 km. The number of lineament intersection present in each grid is counted which gives the lineament intersection from that lineament intersection map was prepared. This final analogue product is then digitized and the value of lineament intersection in each grid is updated in the database in the digital coverage. More the number of lineament intersections, higher the probability of landslide occurrence. Accordingly, a criterion table was generated (Table 5). Figure 6. Aspect (direction of slope) map of the study area 5.5 Aspect Aspect represents the direction of slope and refers to the direction in which a mountain / hill slope faces a possible amount of sunshine and shadow. The aspect of the slope is one of the major contributing factors for a landslide. Slope aspect influence terrain exposure to storm fronts. It also affects fluctuations of pore water pressure and alternation of weathering environment brought on by wet / dry and / or freeze / thaw cycles (Brardinoni et al. 2003). Moisture retention and vegetation is reflected by slope aspect, which will affect soil strength and susceptibility to landslide. It has been reported that in Lantau Island, Hong Kong the landslide frequency is relatively low in north facing slopes, and it increases with the orientation angle, reaching the imum on south facing slopes and then declines (Dai and Lee 2002). Around Dehradun and Mussoorie in India, all the landslides occurred on south facing slopes (Panikkar and Subramanyan 1996). In the Mengen region of Turkey, 42% of the landslides observed in the area of dip towards north (Gokceoglu and Aksoy 1996). Approximately 75% of the landslides invented at Howe Sound, Capilano and Seymour watersheds in British Colombia exhibited a southerly aspect (Brardinoni et al. 2004). From the field investigation and the geological survey of India report by Seshagiri et al. (1982), most of the landslides were occurred in south facing aspect was caused by a higher amount of solar insolation in these slopes. It is learnt from reports that slope with higher insolation and associated higher temperatures have increased erosion. Areas where vegetation has been removed will receive direct sunlight, creating drier soil conditions, thus increasing the probability of landslide occurrences. DEM (Figure 4) was generated from TIN. Aspect map (Figure 6) was also derived from TIN. In the study area, nine 6

7 Asian Journal of Geoinformatics, Vol.17,No.2 (2017) Table 7. Engineering classification of soils and their ranks Group classification Significant constituent material General rating as subgrade Rank A-1b Gravel and sand Excellent 1 A-3 Fine sand Good 2 A-2-4 Silty gravel and sand Good 3 A-2-5 Silty gravel and sand Good 4 Table 8. Ranks for soil depth Figure 7. Map showing soil types based on engineering properties types of aspect were derived. From the field condition and previous studies, rank and weights were assigned for aspect (Table 6). 5.6 Soil classification (engineering properties) Natural soil deposits are complex to deal with, because i) the stress-strain relationship for a soil depth is non-linear ii) soil deposits have a memory for stresses they have undergone in their geological history. Hence, their behavior is vastly influenced by their stress history; time and environment are other factors which may alter their behavior. iii) soil properties being far from homogeneous, exhibit properties which vary from location to location. A soil is permeable if it contains continuous voids. The permeability of soils has a decisive effect on the stability of foundation and slopes, seepage loss through embankments of reservoirs, drainage of subgrades etc. A soil-surface will allow infiltration to enter at a rate up to the saturated coefficient of permeability with respect to water and the remaining amount of rainwater will run off. Tsaparas et al. (2002) reported that by numerical analysis for a soil with high saturated coefficient of permeability (k-sat), the slope would become unstable under continuous of heavy rainfall with or without antecedent rainfall. Soils in nature do possess permeability which is different in the horizontal and vertical direction. The interaction between soils and percolating water has an important influence on the design of foundations and earth slopes. Shear strengths of soils get reduced due to the development of neutral stress or pore pressure (Murthy 2003). Increase in pore water pressure alters slope stability by reducing the effective normal stress and thus soil shear strength (Brardinont et al. 2003). Panikkar and Subramanyan (1996) reported that most of the landslides at Dehradun and Mussoorie in India occured after heavy rains, which serve to saturate the materials thereby increasing their effective weight, it can cause the weakening of materials like clay which swells up when moist. In the southern Apennine (Italy), the main scarps of the landslides are often located near the contact area between clays and carbonate rocks or detrital deposits, the clayey soils act as an impervious bounding for other lythotypes (Polemio and Petrucci 2002). The Chenmari landslide lies in the eastern part of Gangtok, Sikkim Himalaya, the top soil consists of medium grained sandy soil mixed with boulders and weathered mica gneiss (Bhasin et al. 2002). The soils of the study area were classified in to 4 categories based on AASHTO (Table 12) viz., (i) Silty gravel and sand (A-2-4), (ii) Silty gravel and sand (A-2-5), (iii) Gravel and sand (A1-b) and (iv) Fine sand (A-3). An insight into the geotechnical classification of soil is provided by Murthy (2003). Global Positioning System was used for identifying the soil sample locations in the field. From the X, Y and Z co-ordinates a map showing the distribution of the soil types was prepared (Figure 7). Using online digitization with the help of GIS software, this map was converted into digital format and projected into World Co-ordinate System for further analysis. From the field data and the local enquiry, proper ranks were assigned (Table 7) to each soil category based on the degree of contribution of the category to the occurrence of landslide and these parameters were used for preparing the soil classification (engineering properties) map. 5.7 Soil depth Soil depth (m) Rank < to to 12 3 >

8 Mapping Landslide Prone Areas in Ooty Region, South India Using Remote Sensing, Geographic Information System and Geotechnical Data Table 9. Ranks for soil type Soil Type Rank Lateritic soils 2 Lateritic soil with top humic layer 3 Alluvial and Colluvial soils 4 Table. Weights for the thematic layers Figure 8. Map showing variation of soil depth in the study area Thematic map Weight Slope 9 Landuse 8 Soil depth 7 Soil Map 5 Soil type 6 Aspect 6 Drainage frequency 8 Lineament intersection 7 Lineament occurrence 6 Road buffer 8 Soil samples were collected at various locations and various depths. The location and depth data was processed and analyzed. From the above data, the study area was categorized into four ranges such as < 5m, 5 to 8 m, 8 to 12 m and > 12 m. Analyzing the existing report and landslide details available from field data, proper ranks and weights were assigned to each category (Table 8). Soil depth map (Figure 8) was prepared using GIS environment. 5.8 Soil type Soil map is prepared using the Geological Survey of India map on 1: 50,000 scale, and using online digitization, converted into digital format with the help of GIS software and transformed into World Co-ordinate System for overlay analysis. The study area has three types of soil. Proper rank and weightage were assigned to each category from field observation based on the severity of landslide in each of these soil types (Table 9). 5.9 Road network Formation of road and railway network is also one of the causes of landslides in the study area. Panikkar and Subramanyan (1996) reported that there were several minor landslides all along the road from Dehradun to Mussoorie, only 25 % of the major slides occur within a distance of 200 m from the road and 51.9 % of them occur at distances greater than 400 m. Road network map for the Ooty region has been prepared from Survey of India Topographic map in the scale of 1:50,000. A buffer of 50 m is applied from the Figure 9. Landslide susceptibility map of the study area centre line of the road for the entire length of the road. Due to formation of road and railway network, the soil above and below the centre line of the road has been disturbed, hence minor to major landslides are occurred along the road and railway network. The road network map was projected in to 8

9 Asian Journal of Geoinformatics, Vol.17,No.2 (2017) Table 11. Landslide susceptibility range Zone Landslide susceptible Landslide % Area Value Susceptibility < µ - 2σ 23 to 151 very low 1.54 µ - σ to µ - 2σ 152 to 190 low µ - σ to µ + σ 191 to 266 moderate µ + σ to µ + 2σ 267 to 304 high 9.51 > µ + 2σ 305 to 385 very high 1.82 General classification Group classification Sieve analysis Percent passing 2 mm mm mm Characteristics of fraction passing mm Liquid limit Plasticity index Granular materials (35 percent or less passing mm) Silt-clay materials (more than 35 percent passing mm) A-1 A3 A2 A-4 A-5 A-6 A-7 A-1a A- 1b A-2-4 A-2-5 A-2-6 A N.P min min min 36 min 40 Group index Usual types of significant constituent materials General rating as subgrade Table 12. AASHTO Soil Classification Stone fragments, gravel and sand Fine sand Silty or clayey gravel and sand Excellent to good Silty soils 36 min Fair to poor 36 min Clayey soils world co-ordinate system and proper rank i.e. 5 for inside of the buffer and 2 for the outside of the buffer was assigned and weights were also assigned for overlay analysis. 6 Overlay analysis The landslide susceptibility map (Figure 9) was prepared in a GIS environment. Ranks were assigned to each entity in thematic maps based on the frequency of occurrences of landslides for a particular theme. Each theme was assigned with a weightage (Table ) depending on the severity of the theme related to landslide occurrences. Overlay analysis was carried out for the geo-referenced thematic maps. Union operation was adopted for overlaying the ranked thematic maps and the output represents the Landslide Susceptibility Value. Statistical parameters such as minimum, imum mean and standard deviation were arrived for the final coverage and based on these the study area is classified into five landslide susceptible zones as shown in (Table 11). 7 Validation An overall assessment of the landslide susceptibility map has been made by studying the locations in which major landslides along the study area has already occurred. For validation a detailed map of landslides in the study area, GPS data and published report (Seshagiri et al. 1982) were used. There is a good correlation between areas defined as very highly susceptible and the known landslides. There were several landslides in the study area and many of them coincided with the very high to high susceptible zones. But a few places the known landslide location has not matched with the highly susceptible zones because of less slope with more soil thickness and landuse practice of settlement in nature, it indicates slope is the main contributing factor for landslide occurrences. 8 Conclusions 9

10 Mapping Landslide Prone Areas in Ooty Region, South India Using Remote Sensing, Geographic Information System and Geotechnical Data This study has demonstrated the need to include geotechnical properties of soil as an important input for remote sensing and GIS based studies on landslides. The approach used in this study could help to evaluate the current conditions of the landscape and determine, based on simple approaches, the vulnerability of areas to landslide activity. Variables derived from maps and imagery, such as slope, aspect and landuse can be used to develop hazard assessment tools to predict the spatial distribution of landslide hazards. Landuse, soils, aspect, drainage frequency, lineament intersection, lineament occurrence and aspect function well as predictors of landslide susceptibility. In the study area, the high and very high susceptible areas are characterized by non forested areas indicating the influence of vegetation on the initiation of slope instability. Landslide susceptibility was highest in the slope range of 25º to 45º. As the slope increased, deep rooted vegetation like shrub, fallow or forest stabilize the topsoil thus lowering landslide hazard. South facing slopes showed a greater potentiality for landslide susceptibility which may be attributed to the microclimatology and cultivation activities followed here. Fine soils with a greater depth found to be more susceptible to landslides. This may be due to infiltration of water to greater depths thus increasing the soil weight, decreasing the soil strength and loosening a large mass of soil triggering landslides. The susceptibility maps can potentially be used for assessing landslide hazard in the study area, hence providing a tool for planners and investors from organization working in the region. The maps would allow planners to allocate resources to areas where conservation practices can most effectively reduce the hazard of landslides. Preventive measures which should be undertaken include afforestation programmes, construction of toe walls to prevent lateral erosion and stream cutting and construction of retaining walls to stabilize slopes. References Balachandran,V., Thanavelu,C., and Pitchaimuthu.R., (1996), Marappalam landslide, The Nilgiri district, Tamilnadu, India, a case study. Proceedings, International conference on disasters and mitigation, Madras, India, January, (1996), Volume I, PP. A Baldiviezo, P.H.L., Thurow, T.L., Smith, C.T., Fisher, C.T., and Wu, X.B., (2004), GIS-based spatial analysis and modeling for landslide hazard assessment in Steeplands, Southern Honduras. Agriculture, Ecosystems and Environment, Brardinoni, F., Slaymaker, O., and Hassan, M.A., (2003), Landslide inventory in a rugged forested watershed : a comparison between air-photo and field survey data. Geomorphology, 54, Dai,F.C., and Lee,C.F., (2002), Landslide characteristics and slope instability modeling using GIS, Lantau Island, Hong Kong. Geomorphology, 42, Gokceoglu.C., and Aksoy.H., (1996), Landslide susceptibility mapping of the slopes in the residual soils of the Mengen region (Turkey) by deterministic stability analyses and image processing techniques. Engineering Geology, 44, Gray, D.H., and Leiser, A.T., (1982), Biotechnical slope protection and erosion control. Van Nostrand Reinhold Company, New York. Greenways, D.R., (1987), Vegetation and slope stability. In slope stability, edited by M.F.Anderson and K.S.Richards. Wiley and sons, New York. Hegde, V.S., Ranganath, B.K., Ganesha Raj, K., Diwakar, P.G., Manjula, V.B., Nanda Kishore, R., Srivastava, S.K., Thomas, J.V., bandyopadhyay, S., and Sameena,. (2001), Integrated mission for sustainable development, Nilgiris district, Tamil Nadu a project for eco-restoration and eco-development- part 1, technical report. Murthy, V.N.S., (2003), Principles of Soil Mechanics and Foundation Engineering, UBS Publishers Distributors Pvt. Ltd. Nagarajan,R., Anupam Mukherjee., and Aniruddha Roy., (1996), Landslide hazard assessment using remote sensing and GIS A case study. Proceedings, International conference on disasters and mitigation, Madras, India, January, Volume I, PP, A Panikar.S.V., and Subramanyan.V., (1996), A geomorphic evaluation of the landslides around Dehradun and Mussoorie, Uttar- Pradwsh, India. Geomorphology, 15, Perotto-Baldiviezo, H.L., Thurow, T.L., Smith, C.T., Fisher, C.T., and Wu.X.B., (2004), GIS-based spatial analysis and modeling for landslide hazard assessment in steeplands, Southern Honduras. Agriculture, Ecosystems and Environment, peter A. Burrough., and Rachael A. McDonnell., (1998), Principles of Geographic Information Systems. Oxford University Press, pp, Polemio, M., and Petrucci. O., (2002), Hydrogeological Monitoring and Image Analysis of a Mudslide in Southern Italy. Physics, Chemistry and Earth, 26,

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