Journal of Global Resources
Volume 6 (01)August 2019-January 2020
Page 64-70
UGC–CARE Listed Journal in Group D
ISSN: 2395-3160 (Print), 2455-2445 (Online)

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A STUDY ON LANDSLIDE PRONE ZONES IN SAKALESHAPUR TALLUK, WESTERNGHATS, KARNATAKA, INDIA
Aneesah Rahaman1 and Madha Suresh.V2
Research Scholar CNDHS, University of Madras, Chennai, India
2
Professor and Head, CNHDS, University of Madras, Chennai, India
Email: aneesah0786@gmail.com
1

Abstract: Landslides are the common phenomena in the hilly terrain of Western Ghats region
due to the heavy rainfall. The occurrence of landslides in the study area Sakleshpura andBelthanggudi Talluk in Karnataka state is quite less in comparison to Himalayan region. In theyear 2018, during monsoon season the study area faced divesting floods and landslides. The
aim of this study is to identify the landslide prone zones using Frequency Ratio Model with thehelp of ArcGIS software. The factors considered for this study are slope, soil, drainage density,
distance from drainage and rainfall. All the spatial data have been calculated using frequency
ratio model and each grid factor has been summed up into three categories such as high,moderate and low hazard zone. The results of this study reveals that that 160 sq.km areas isunder very low with landslide density (LD) of 0.01, 894 s.km area is under medium zone with
LD of 0.02, 75.36 sq.km area is under high hazard zone with LD of 0.05. The study also reveals
that the soil is more vulnerable factor for landslide on the basis of frequency ratio value flowedby rainfall, slope, distance from drainage and drainage density in the study area. The final
output of the map can be helpful for the local government of the study area.
Key words: Landslide, frequency ratio, hazard zone, GIS, Western Ghats.
Introduction
Landslide is the downward movement of the earth materials under the impact of gravity. On thebasis of various physical factors in the study area such as geological, geo-environmental,
geomorphological and hydrological, usually landslide happens under these various conditions(M. Geertsema et al., 2009). There are many natural processes that shape the earth’s surface,landslide is one of them. It has been said that landslide took third position in the world as anatural disaster that can leads many damages (Zillman, 2000). It is happened only when thelandslide threatens to human beings as a hazard. In hilly mountainous region landslide is themost natural hazards (Rammohan et al., 2011). It is very common that in each year number ofpeople gets damaged and also loses their lives, property in landslides all over the world. The
hilly slope may unstable due to the deficiency of proper geotechnical investigation and leads tothe adverse effects on the geo-environment in that region (R. Anbalagan et al., 2008). By these
phenomena the local and global economy is also affected. Since 25 years or more, many
government, local organization and international institute are investing resources to manage
and mitigate the landslide hazards with the help of Susceptibility Map throughout the world(Guzzetti et al., 1999). For the study of landslide hazard mapping some temporal factors should
be included such as earthquake, rainfall, variation of temperature (Guzzetti et al. 2006;
Pradhan et al. 2010; Dahal et al. 2012). To mitigate the landslide hazard, the Landslide Hazard
Evaluation Factor (LHEF) rating can be done and this factor is based on the existence of
causative factors in the area of study. The similar technique has been applied in the rock massclassification e.g., RMR and the Q system (Barton et al., 1974; Bieniawski, 1979). For
susceptibility of landslide mapping in GIS environment, tools and techniques have beenclassified into two approaches such as subjective and objective and the mapping of invention
and analysis of expert are existed in subjective approaches (Lee et al. 1991; Soeters and Van
Western 1996; Wang et al. 2009). In case of indirect mapping of susceptibility approaches,
many studies have been done through the application of very popular tool such as Geographic
Information System (GIS) (Bignell and Snelling, 1977). It is possible to identify the slope failure
area as well as vulnerable to slope in the form of maps of landslide susceptibility with the help64

of distribution of previous spatial data of landslides and their related causative factors(Nagarajan et al., 1998; Fernandez et al., 2003).
In the present study area Sakeleshpur Taluk in Hassan District, landslide happened in theyear of 2018 due to torrential downpour. Since four days’ heavy rainfall of an average of 11.9
cm had been received by the district. Total 120 landslides have been detected with the help ofsatellites such as ISRO Resource-sat 2, Worldview 2, spot 7 in Kodagu and Hassan Districts in
Karnataka State. Out of the total landslides 25 has occurred in the study area
(newindiaexpress.com). Besides heavy rainfall, the clay type soil, steep slope, number ofdrainages and also land use land cover caused the landslides in the study area. The study area
is situated in Sahyadri folded mountain belt which is lithologically prone to landslides. The study
area is covered by red gravelly clay type soil in which occurrence of landslides depended. This
area has a loose and unconsolidated soil. Weathering is influenced by the climatic condition of
the Western Ghats which is also one of the major causes of landslides. Most of the landslide isdebris type in the study area. In the year of 2018 the heavy rainfall caused the massive
landslides.
Study Area
Geographically the study area Shekeleshpur Talluk, consists of 221 villages of Hassan Districtof Karnataka State is located 12.943°N 75.775°E with a geographical area of 1,129.68 sq.km.
Geomorphologically it is situated in the Sahyadri folded mountain of Western Ghats with anelevation of 956 m above Mean Sea Level (MSL). The Hemavathy and Kavery is the main riverin this region which is empties into the Arabian Sea. Weathering and erosion is very high due tothe heavy intensity of rainfall. The average annual rainfall is 2178 mm and the average annual
temperature is 22.7 degree Celsius. According to 2011 census total population of the study
area is 23, 352 among them the total male population is 11,558 and female population is11,754.
Figure 01: Study Area

Objective The objective of this study is to identify the root cause of landslide in this region.
 To demarcate the landslides prone zone using Frequency Ratio Model with the help of
the ArcGIS software.
Database and Methodology
In this present study five causative factors have been used such as slope, soil, distance fromdrainage, rainfall and drainage density. Table 1 show the data used of this study.
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Table 01: Data Used in the Present Study
Data Type
SourceData Derive
Carto DEM (1 m resolution)
Bhuvan, NRSC
Slope, distance from drainage
and Drainage Density Map
Soil
Raitamitra.kar.nic.in
Soil Type Map
Landslide
Sentinel 2B and Google
Landslide Inventory Map
Earth
Rainfall
IMD, Karnataka
Rainfall Distribution Map
There are number of bivariate statistical method that can be used to prepare thesusceptibility of landslide mapping, among them Frequency Ratio (FR) Model is one and in thepresent study, FR model has been used (Pradhan and Lee, 2009). The FR model can build thespatial relationship between the location of landslide and the factors of landslides (Lee, 2005).
GIS based Frequency Ratio Model has been applied based on the causal relationship between
the causative factors and the occurrence of landslide in this area. It has fixed value of 1. The
value more than 1 indicates the higher correlation between the causative factors and theoccurrence of landslide. On the other hand, value less than 1 shows the lower correlation.
After creating all the thematic layers have been converted into raster and reclassification has
also been done using ArcGIS 10.4 software. Occurrence of landslide (LS), percentage of LS
occurrence, total number of pixel, percentage of pixel have been identified and frequency ratio
have been calculated of each factor such as slope, soil, distance from drainage, drainage
density and rainfall of the study area. All the layers have been summed up and finally thelandslide hazard prone map has been done with three classes namely high, moderate and low
in the study area.
RESULTS AND DISCUSSION
Relationship between Soil and Landslides
The type of soil has been classified into four classes including water such as red gravelly clay
soil, coastal lateritic soil, and lateritic gravelly soil and water bodies. The maximum number oflandslides has occurred in red gravelly clay type soil 13 out of the total landslides 25, followedby coastal laterite, lateritic gravelly and water bodies. Figure 3 shows the soil map of the study
area. Table 1 describes that the frequency ratio of each soil types. In this table the soil type redgravelly clay shows the maximum number of landslides of 13 out of total landslides 25 which is
52 percentages. The frequency ratio of the soil class has been calculated with the percentageof landslide occurrence divided by the percentage of pixel domain which is 5.78. Likewise,
frequency ratio of all the other soil type has been calculated.
Table 01: Frequency Ratio of Soil to Landslide occurrences
Soil class
Red Gravelly Clay
Soil
Coastal Laterite
Soil
Lateritic Gravelly
Soil
Waterbodies
Total

No. ofPixels3914

Landslideoccurrence
13

Landslideoccurrence %52

Pixelsdomain3914

Pixelsdomain %
8.99

Ratio

18488

8

32

18488

42.49

0.75

15501

2

8

15501

35.62

0.22

5610
43513

2
25

8
100

5610
43513

12.89
100

0.62
7.38

5.78

Relationship between Rainfall and landslides
The average rainfall has been classified into five classes as 1761 mm, 1833 mm, 1904 mm,
1976 mm and 2047mm. The maximum number of landslides has occurred in 1976 mm average
rainfall class of 17 out of the total landslides 25, followed by 1904, 1833 and 1761 mm. Figure 4
shows the rainfall map of the study area. Table 2 explains the frequency ratio of each averageof rainfall classes. In this table the maximum number of landslides has occurred in 1904 mm
rainfall class are 11 out of total landslides 25 which are 68 percentages. The frequency ratio of
this class has been calculated with the percentage of landslide occurrence divided by thepercentage of pixel domain which is 3.13. Likewise, frequency ratio of all the other rainfall classhas been calculated.
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Rainfall
(mm)
1761
1833
1904
1976
2047
Total

Table 02: Frequency Ratio of Rainfall to Landslide occurrences
No. ofLandslide
Landslide
PixelsPixelsPixels occurrence
occurrence %domaindomain %
13913
0
0
13913
32.52
8169
1
4
8169
19.09
5525
7
28
5525
12.91
9281
17
68
9281
21.69
5892
0
0
5892
13.77
42780
25
100
42780
100

Ratio
0
0.21
2.17
3.13
0
5.51

Relationship between Distance from drainage and Landslides
The distance from drainage to landslide has been classified into six classes such as 250m,
500m, 750m, 1000m, 1250m and 1500m by using buffer tools. The maximum number oflandslides has occurred in 250 m, followed by 500m, 750m, 1000m, 1500m and 1250m. Figure
5 shows the drainage distance from landslide map of the study area. Table 3 shows that thefrequency ratio of each drainage buffer categories. In this table the drainage class of 250m
shows the maximum number of landslides of 9 out of total landslides 25 which is 34.62
percentages. The frequency ratio of the buffer class has been calculated with the percentage oflandslide occurrence divided by the percentage of pixel domain which is 0.97. Likewise,
frequency ratio of all the other buffer classes has been calculated.
Table 03: Frequency Ratio of Distance from Drainage to Landslide occurrences
Distance fromNo. ofLandslide
Landslide
PixelsPixelsRatiodrainage (m)Pixels occurrence occurrence % domain
domain %
250
15876
9
34.62
15876
35.69
0.97
500
13377
8
30.77
13377
30.07
1.02
750
8588
5
23.08
8588
19.30
1.19
1000
3136
2
7.69
3136
7.05
1.09
1250
1813
0
0
1813
4.08
0
1500
1699
1
3.85
1699
3.82
1.00
Total
44489
25
100
44489
100
5.29
Relationship between Slope and Landslides
Slope has been classified into five categories such as, 0 – 7°, 7°- 12°, 12° – 20°, 20° – 30°,>30°. The maximum number of landslide has occurred in the slope category of 20° – 30°,
followed by >30°, 7°- 12°, 12° – 20°, and 0° – 7°. Figure 6 shows the slope map of the study
area.
Table 04: Frequency Ratio of Slope to Landslide occurrences
Slope
No. ofLandslide
Landslide
PixelsPixels
Ratio
class
Pixelsoccurrence occurrence %domaindomain %0--72840342
7.69284034
28.41
0.27
7--12
331028519.2333102833.11
0.58
12--202291064
19.2322910622.92
0.84
20--30114667
8
30.77
114667
11.47
2.68
30--60
40804
6
23.08
40804
4.08
0.00
Total
99963925
100999639100
4.43
Table 1 shows the frequency ratio of each slope category. In this table the slope
category of 20° – 30° shows the maximum number of landslides of 8 out of total landslides 25
which is 30.77 percentage. The frequency ratio of the slope has been calculated with thepercentage of landslide occurrence divided by the percentage of pixel domain which is 2.68.
Likewise, frequency ratio of all the other slope classes has been calculated.
Relationship between Drainage Density and Landslides
The density of drainage has been classified into five classes as 0-1.2, 1.3-2.3, 2.4-3.5, 3.6-4.6
and 4.7-5.8. The maximum number of landslides has occurred in 1.3-2.3 of 11 out of the totallandslides 25, followed by 0-1.2, 2.4-3.5, 3.6-4.6 and 4.7-5.8. Figure 7 shows the drainage
density map of the study area. Table 4 shows that the frequency ratio of each drainage density
classes. In this table the class interval 1.3-2.3 shows the maximum number of landslides of 1167

out of total landslides 25 which is 44 percentages. The frequency ratio of the density class has
been calculated with the percentage of landslide occurrence divided by the percentage of pixel
domain which is 1.16. Likewise, frequency ratio of all the other drainage density has been
calculated.
Table 05: Frequency Ratio of Drainage Density to Landslide occurrences
Drainagedensity0-1.2
1.3-2.3
2.4-3.5
3.6-4.6
4.7-5.8
Total

No. ofPixels
17631
16201
7014
1821
145
42812

Landslideoccurrence
8
11
5
1
0
25

Landslideoccurrence %
32
44
20
4
0
100

Pixelsdomain
17631
16201
7014
1821
145
42812

Pixelsdomain %
41.18
37.84
16.38
4.25
0.34
100

Ratio
0.78
1.16
1.22
0.94
0
4.10

Reclassification using Frequency Ratios
In the present study five parameters have been taken as a causative factor for the preparationof landslide hazard map have been assigned the method of Frequency Ratio by using ArcGIS
software 10.4. For the preparation final map, all the thematic maps have been reclassified byusing ArcGIS Spatial Analyst extension tool. All the reclassified maps have been shown infigure wise.
Landslide Susceptibility Mapping (LSM)
In this study, the GIS based Frequency Ratio has been applied to prepare the Landslide
Susceptibility Map by using five causative factors such as slope, drainage density, and distanceto drainage, rainfall and soil. To calculate the Landslide Susceptibility Index (LSI) all theparameters has been converted into 30*30 m grid cells. The total number of cell is 42290 andthe total number of landslide is 25 in the study area. In the overlay analysis tool, the summationof each frequency ratio value has been given to calculate the LSI.
LSI= ΣFr (where Fr is the frequency ratio of each causative factors)
The landslide hazard zonation (LHZ) map has been created by using LSI assigned value toeach cell. According to frequency ratio table, the frequency ratio of soil is maximum of 7.38,
followed by rainfall is 5.51, distance to drainage is 5.29, slope is 4.43 and drainage density is
4.1. Therefore, all the frequency value has been multiplied by 100 and has been put on theweighted overlay table according to their highest to lowest weight by using ArcGIS software.
The final LHZ map has been presented in figure 8.
Validation
The final LHZ map of the study area should be validated in respect to each causative factor
with landslide inventory map to check the prediction is matched with the expected outcome ornot. All the parameters such as slope, soil, rainfall, drainage density and distance to drainage
maps have been considered with landslide and overlaid on the LHZ map and also the
distribution of landslide in each zone has been calculated which is shown in figure 8.
Table 06: Landslides, Area and Landslide Density in the LSM (Landslide Susceptibility)
LS Classes
Low
Medium
High
Total

LS
1
20
4
25

LS %
4
80
16
100

Pixel Domain
5337
29807
2512
37656

Pixel %
14.17
79.15
6.67
100

Area(sq.km) (A)160.11894.2175.36
1129.68

LS/A
0.01
0.02
0.05
0.08

The LHZ map has been classified into three zone such as Low, Medium and High hazard
zone by using Jenks method of natural break in ArcGIS software. The LHZ map shows that the
maximum number of landslide has occurred in medium zone are 20 and 4 in high zone and 1 inlow zone. Out of the total area of 1129.68 sq.km, medium hazard zone covered 894.21 sq.km
areas, high zone is 75.36 s.km and low zone covered 160.11 s.km areas. Therefore, the resultsof the present study reveal that the study area is fall under medium to high hazard zone (table
6).

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Figure 3: Soil

Figure 4: Rainfall

Figure 7: Drainage Density

Figure 5: Drainage Buffer

Figure 6: Slope

Figure 8: Landslide Hazard Zonation Map

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Conclusion
The landslide hazard zonation (LHZ) mapping based on the Frequency Ratio technique has
given the acceptable results. The study also reveals that the soil is more vulnerable factor forlandslide on the basis of frequency ratio value flowed by rainfall, slope, distance from drainage
and drainage density in the study area. Beside this hilly terrain with steep slope and the heavy
rainfall in 2018 also leads the major role on the landslides.
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