Abstract / Introduction / Study Area / Method / Results / Conclusion / References
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Energy and Wetlands Research Group
Centre for Ecological Sciences
Indian Institute of Science, Bangalore 560 012

METHOD

Method adopted for landslide susceptibility analysis is given in Fig 2. Field investigations were carried out in the Sharavathi river basin located in central Western Ghats. Major components of the study are:

1. Identification of causal variables : Review of literature indicates the major causal variables are: topographical (aspect, slope, curvature, drainage network), geo-morphological (lineament, genesis), lithological (lithology, soil texture, soil permeability and soil depth), infrastructure (road network, location of buildings), land cover (NDVI), land-use (agriculture, waterbodies, forests, built-up, barren land). Field surveys were carried out of landslide spots (temporal as well as latest ones), attribute data of training polygons of land use analysis using pre-calibrated GPS.

Fig 2 : Flow chart of landslide susceptibility analysis


Table 1: Spatial data

Classification
Sub-classification
Data Type
Scale

Base layers

Topographic

Lines and points

1:50000

 

Geological

Lines and polygons

1:250,000

 

Soil

Polygon

1:250,000

 

Elevation

GRID (SRTM)

90m x 90m

Remote sensing data

Land cover

GRID (IRS-1D)

23.5m x 23.5m

 

Rainfall

Points

Taluk level

Geological Hazard

Landslide

Points

 

2. Creation of base layers of spatial data – soil, geology, topography, geo-morphology, land use, etc. These information were collected from the respective government agencies and supplemented with the remote sensing data and other spatial layers. Indian Remote Sensing (IRS) 1C/1D satellite, LISS III (linear imaging self scanner) data of spatial resolution 23.5 m (acquired during Nov 2004),  of bands 2, 3 and 4 (corresponding to G, R and IR bands of electro magnetic spectrum) were used for land use and land cover (NDVI) analysis.  Supervised classification using Gaussian maximum likelihood classifier was carried out for deriving seven land use categories- agricultural, barren land, built up, moist deciduous forest, plantation, semi-evergreen forest and water body. Road and drainage networks with administrative boundaries were digitised from Survey of India (SOI) topographic maps (1:50,000 scale). Soil types and spatial extent were digitised from the soil map of  National Bureau of Soil Sampling and land use planning (NBSS& LUP) of 1:250,000 scale. From this, texture, depth and permeability were derived. Spatial data with type are listed in Table 1.

Geomorphological variables such as lithology, lineament, rock type were extracted from geological and structural maps of Geological Survey of India (1:250,000 scale). Shuttle radar topographic mapping (SRTM 3 arc-sec) of 90 m resolution was used to derive layers of slope, aspect and curvature. This constitutes predisposing factors for the landslide activity.

Slope was classified into 10 classes. Aspect represents the angle between the geographic north and a horizontal plain for a certain point. This was classified in eight major orientations (N, NE, E, SE, S, SW, W, NW). The curvature controls the superficial and subsurface hydrological regime of the slope and the classes considered are concave, flat and convex slope areas, which were directly derived from the DEM.

The distance from drainage and road was calculated using the vectorised drainage and road from the topographical sheets of scale 1:50,000. The drainage and road buffer was calculated at 90 m intervals. The lithology and genesis was extracted from the available geology map prepared by the Geological Survey of India (GSI). In addition the lineament database from GSI, was used to create distance from lineaments map. The lineament buffer was calculated at 90 m intervals.

3. Development of spatial database : Considering the spatial resolution of the data available, all data layers were resampled to 90 m. Landslides (both latest and earlier ones) corresponding to 120 occurrences were used for  computing LSI as well as for sensitivity analysis. 

4. Frequency ratio : Frequency ratio is the ratio of occurrence of probability to non-occurrence probability, for specific attributes. In the case of landslides; if landslide occurrence event is set to B and the specific factor’s attribute to D, the frequency ratio for D is a ratio of conditional probability. If the ratio is greater than 1, greater is the relationship between a landslide and the specific factor’s attribute; and if the ratio is less than 1, the lower the relationship between a landslide and the specific factor’s attribute.

5. Computation of Landslide Susceptibility Index (LSI) : Landslide Susceptibility Index (LSI) is the summation of each factor’s frequency ratio values as in Eq. 1. Landslide susceptibility value represents the relative hazard to landslide occurrence, as higher values are associated with landslide hazards.

 
(where, LSI: Landslide Susceptibility Index; Fr: rating of each factor’s type or range). The landslide hazard map was made using the LSI values.

Table 2 : Frequency ratio – Spatial relationship between landslides and related factors

Factors with domain
No of pixels in domain
No of landslide
% of domain
% of landslide
Frequency ratio

Aspect

South

15924

24

0.135

0.261

1.939

South-West

16018

13

0.135

0.141

1.044

North-West

16308

13

0.138

0.141

1.026

North-East

13337

11

0.113

0.120

1.061

South-East

12758

12

0.108

0.130

1.210

West

16085

5

0.136

0.054

0.400

East

11159

6

0.094

0.065

0.692

North

16795

8

0.142

0.087

0.613

Land use

Agriculture land

25933

40

0.219

0.435

1.985

Barren Land

4536

6

0.038

0.065

1.702

Builtup

1145

2

0.010

0.022

2.248