identification of landslide hazard …topographic sheet nos. 58 c/13, 58 c/9, 58 f/4. several...

IDENTIFICATION OF LANDSLIDE HAZARD ZONATION IN

IDDIKI USING REMOTE SENSING

Dr. S. Vidhya Lakshmi*, Mohammed Harif.H**

* Associate Professor ** Final year, B.E., Civil Engineering

Department of Civil Engineering, Saveetha School of Engineering

Saveetha Institute of Medical and Technical Science, Chennai - 602 105, India

Email –[email protected], [email protected]

ABSTRACT:

Landslides are one of the most

common natural disasters which cause big

damage to our environment and properties in

terms of direct and indirect risk. The

expression "landslide" fundamentally implies

an ease back to fast descending development

of instable shake and flotsam and jetsam

masses under the activity of gravity which

can be sorted into different kinds based on

disappointment qualities Increase in

population and rapid urbanization has led to

increase of construction works in mountain

and hilly terrain has catapulted more number

of landslides to most area in recent decades.

Dangerous landslide area was identified in

Munnar, Iddiki, India. Landslide zonation in

Idukki, Kerala, India has been done using

GIS and Remote Sensing. Factor maps of

different territory parameters, for example,

slope, land use, relative relief, drainage

pattern, drainage density, landform, and

surface material were readied and their

joining did on a GIS platform. The delicacy

idea utilized as a part of this examination is a

quick and savvy demonstrate for

distinguishing avalanche inclined zones,

particularly in the Western Ghats.

KEYWORD: Landslide, slope, landuse,

relative relief, drainage pattern,

landform, drainage density, envi 4.5,

qgis 2.6.0.

1. INTRODUCTION:

Landslides is described as huge

movement, which is sudden down slope

moving of soil sediments and rocks due to

gravity. These can also cause due to intense

rainfall, earthquakes, Water-level changes,

storm or sudden stream erosion which have

cause a rapid increase in stress or decrease in

strength of slide-forming materials. These

include rainfall, earthquakes, water-level

increase, storm waves which cause a fast

increment in shear pressure or abatement in

shear quality of slant shaping materials. As

one of the major natural hazards, landslides

claim people’s lives almost every year and

cause huge property damage in mountainous

areas. The evolution of increase landslide

hazard has given greater attention from the

geological scientists, engineering, local

communities and all government in

International Journal of Pure and Applied MathematicsVolume 119 No. 17 2018, 3211-3221ISSN: 1314-3395 (on-line version)url: http://www.acadpubl.eu/hub/Special Issue http://www.acadpubl.eu/hub/

3211

numerous country. Traditionally,

susceptibility assessment or probability

mapping were carried out using laborious and

time-consuming because of the time required

and effort for the human handling and

processing of the data. As of late, geographic

data frameworks (GIS) have turned into an

essential apparatus for avalanche risk

evaluation. GIS is a PC based innovation

intended to catch, store, control,

examinations and show differing sets of

spatial or geo referenced information.

2. STUDY AREA:

The study area forms part of the

Western Ghats in Idukki district, Kerala

State. The study area is located around

Munnar within latitude 9° 46' & 10°

05’N and longitude 76° 45 ' & 77° 05' E

falling in the Survey of India

topographic sheet Nos. 58 C/13, 58 C/9,

58 F/4.

Several workers have investigated

slope failures in Western Ghats and

occurrence landslides in the Idukki

district (Seshagiri et al., 1982,

Kandaswamy et al., 1985 Krishnanath.et

al., 1985, 1993, 1996, Biju

Abraham.et.al., Krishnanath and

Sreekumar, 1996, Sreekumar, 1998

Sreekumar and Krishnanath, 2000,

Sankar, 1991; Earnestetal., 1995;

Thampi et al., 1997, Thampi 2006, 2009

and Sajinkumar et al., 2011, Biju

Abraham, 2011). Studies by Seshagiri et

al., 1982, Thampi et al., 1997, Thampi

2006 and Sreekumar et al, 2010,

Sreekumar and Arish Aslam (2011) have

proved that the slope failures in Western

Ghats are generally confined to the

overburden. Krishnanath et al., 1996,

Sreekumar and Krishnanath 2000, have

studied number of profiles within Idukki

and Pathanamthitta districts and

identified a number of profiles which are

at the geotechnical threshold.

A geological map of the entire study

area is prepared using topographic sheets

(scale 1:50,000), regional geological maps of

Geological Survey of India and from the data

generated in this study. The slope forming

material exposed along the road cuttings

consists predominantly of crystalline rocks,

and their highly weathered equivalents. The

main rock types include biotite gneiss

(granitic gneiss), hornblende biotite gneiss

(composite gneiss), granite gneiss,

charnockites and pyroxene granulite. These

rocks are intruded by basic, acidic and

alkaline intrusives . Pink granites are seen in

the Munnar area.

FIG.1 STUDY AREA

3. DATABASE

From the current study two satellite

imageries are downloaded from the United

States Geological Survey web site

(http://glovis.usgs.gov) over the twenty two

years of time period (1989 - 2011). the main

points of the satellite imageries, acquisition

International Journal of Pure and Applied Mathematics Special Issue

3212

date and resolution has shown in below table.

each the information sets are projected in

UTM projection with zone number 43 and

WGS 84 datum. Satellite image of 1989 has

been thought of because the base knowledge

and image of 2011 is co-registered

victimization initial order polynomial model

with that base information with 0.5 picture

element (RMSE) accuracy.

Sensor

type

Acquisition

date

Spatial

resolution

Landsat

TM 5

18 May

1989

30 m

Landsat

TM5

5 March

2011

30m

TABLE :1 Database

Fig 2:Landsat ETM+(2017) Satellite Image.

4. METHODOLOGY

Landslides are very unpredictable events that

take place in the hilly regions. In India,

annual losses due to landslides are estimated

at $1 billion or more. The fatalities that are

caused by landslides cannot be counted in

monetary form. A landslide depends upon

various factors like slope, type of soil,

geology of area, construction activities, land

use of the area etc. One can forecast the

landslide potential of an area with the help of

remote sensing data. The remote sensing data

about the different factors on which the

occurrence of landslide events depend upon

can be incorporated in Geographical

Information System environment and the

degree of these factors can be estimated.

Satellite imagery and remote sensing data can

be used to know the effect of different factors

on which the occurrence of a landslide event

depends upon. This data is processed in GIS.

Each factor responsible for the occurrence of

landslide is taken into account and then their

combined effect can be calculated in GIS

environment.


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Fig 3: Methodology

5. LANDSLIDE HAZARD

MAPPING

Over the past twenty five years, government

and analysis establishments have invested

with resources in assessing landslide hazard,

and in trying to provide maps depiction its

abstraction distribution. Over the past twenty

five years, government and analysis

establishments have invested with resources

in assessing landslide hazard, and in trying to

provide maps depiction its abstraction

distribution. many entirely alternative ways

and techniques for evaluating landslide

hazard and risk square measure projected or

tested. Work of the literature reveals that a

handful of reviews of the ideas, principles,

techniques and methodologies for landslide

hazard analysis square measure projected.

amazingly, little or no work has been done on

the systematic comparison of assorted

techniques, outlining blessings and

limitations of the projected ways that or to the

necessary discussion of the elemental

principles and underlying assumptions of

landslide hazard analysis. Likewise,

exclusively few tries square measure lliade to

stipulate, conceptually or operationally,

landslide risk.

the bulk of papers discuss specific tries at the

analysis of landslide hazard in restricted

areas. exclusively a handful of authors report

on long comes on the analysis of slope

instability conditions, and additionally the

connected hazard and risk, over big regions.

Notable examples square measure drawn by

the work carried out in city County, CA, by

the U.S. natural science Survey by the

proposal created by the French Bureau des

Recherches Geologiques et Minieres for a

geomorphologically primarily based analysis

of landslide hazard by the work carried out at

the Geotechnical Engineering geographic

point, in metropolis and by the appliance of

variable mathematics techniques in pilot

areas of Southern and Central European

nation. Operational and abstract variations

include: general underlying assumptions; the

sort of mapping unit elect for the

investigation.

Preparation of thematic maps showing slope,

landuse, geological, drainage, lineament,

runoff and soil components of the landslide

house pattern remote sensing photos. These

square measure analyzed and square measure

numerically weighted supported their relative

importance. The study house has been

classified into four zones of instability and

landslide hazard zonation map is formed.

6. RESULTS AND DISCUSSION:

6.1. Preparation Of Thematic Maps

For the preparation of various type maps the

data have been collected from various

sources like Survey of India Toposheets

(SOI) No.58A/11 of scale 1:50,000 of 1972,

IRS1C LISS III +PAN incorporate satellite

image information, field information and

numerous different sources are used.


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6.2. Base Map

Base map was ready from the Survey of India

Toposheet. It offers the boundary of the study

space. There are more river, dam and

waterfall have been flown in iddiki

district.This map helps to find the watershed

on iddiki district.

Fig 4:Base Map

6.3. Slope

Slope is a vital consider the analysis of

landslide. Because the slope will increase the

chance of the incidence of landslide will

increase as a result of because the slope angle

will increase the shear stress of the soil. The

stability of a slope phase relies on numerous

factors like slope angle, slope form, slope

length, material of that it's fashioned,

antecedent wetness content. The slope angle

was thought-about the most parameter of the

slope stability it absolutely was ordinarily

utilized in getting ready landslide status

analyses because the shear stress will

increase with progressive inclination. Slope

is that the live of surface gradient and

measured in degrees. Slope angle is

incredibly oftentimes utilized in landslide

status studies since land sliding is directly

regarding slope angle.

Fig 5:Slope Map

6.4. Landuse

The Land use map shows the various sorts of

land cover pattern gift within the study space.

Vegetation cover is a vital issue that

influences the prevalence and movement of

the precipitation that triggers the landslide.

The watershed space is defined by the dense

forest, degraded forest, agricultural land,

forest plantation, grass land, husbandry

plantation, land with or while scrub, forest

and villages. The gardening planting is found

because the major landuse within the

watershed. Land use is additionally one

among the key factors chargeable for the

prevalence of landslides, since, barren slopes

area unit additional at risk of landslides. In

distinction, vegetative areas tend to cut back

the action of environmental condition agents

admire rain, etc., thereby preventing the

erosion because of the natural anchorage

provided by the tree roots and, thus, area unit

less at risk of landslides. The landuse

categories of {the area unita|the world|the

realm} are designed up land, Crop land,

Fallow land, Forest evergreen, Forest

deciduous, Forest plantation, Land with

scrub, Barren rock, River/water bodies, Grass

land, Rubber, Mixed crop, Cardamom, Tea

and occasional. Evergreen Forest and rubber

plantations area unit the most land cowl

categories within the study space.Natural

vegetation coverage is crucial in influencing


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slope stability owing to higher bonding of the

slope material.

Fig 6: Landuse Map

6.5. Geology Map

Geology map is prepared from the geological

survey of India mineral map on a scale

1:50,000. Structurally the area is highly

disturbed and subjected to faulting. The

charnockite covers all the watershed area.

Fig 7:Geology Ma[

6.6. Drainage Density Map

The drainage map shows the flow of water

through munnar drainage area. Because the

distance from the drain line will increase the

likelihood of prevalence of landslide

conjointly increase. The drain density for the

study area have been categorized in to four

zones (very high, high, medium and low).

Most of the watershed have been fall

underneath high density class.

Drainage

Density

(Km/Km 2

)

Classification

> 0.008 Very High

0.006 – 0.008 High

0.004 – 0.006 Moderate

< 0.004 Low

Fig 8: Drainage Density Map

6.7. Lineament Density Map

The lineament map shows the lineaments

shaped within the study space thanks to the

geologic conditions. Water flows through the

cracks and therefore the soil over this

lineament would slide and thence this

triggers the landslide. A lineament map was

ready by visual interpretation of the satellite

information by characteristic the fractures

and fault lines. The lineament density is

classified in to four categories as terribly

high, high, moderate and low as show within

the table below. Majority of the watershed

falls beneath high density class.

Table 2: Lineament Density Map

Lineament Density

(Km/Km 2 )

Classification

> 0.004 Very High

0.002 – 0.004 High

0.001 – 0.002 Moderate

< 0.001 Low


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6.8. Runoff Map

The runoff map shows the depth of runoff

that was obtained because of precipitation.

The depth of runoff was calculated from the

precipitation information for the year 2004.

This information was obtained from HADP.

The runoff is high for the whole watershed,

with terribly high runoff in agricultural land

that ends up in severe erosion. Absence of

low runoff is noted within the study space.

The runoff lineament density is categorised

in to four categories as terribly high, high,

moderate and low as show within the table

below.

Table3:Runoff map

Range mm Runoff Class

7501600 Very High

500750 High

250500 Moderate

0250 Low

6.9. Soil Map

The soil map may be a map a

geographical illustration showing diversity of

soil sorts and soil properties within the study

space. It usually the top results of a soil

survey inventory. Soil map area unit most

typically used for land analysis, spacial

designing, environmental protection and

similar project.

Fig 9: Soil Map

6.10. Landslide Hazard Zonation Map

Landslide hazard zonation map is

ready by desegregation the result of varied

triggering factors. Landslide hazard zonation

mapping at regional level of Associate in

Nursing outsized area provides a broad trend

of landslide potential zones. This is often the

ultimate output of the project it offers the

elaborate regarding landslide hazard zone in

study space from low to high.

Table 4: Landslide Hazard Zonation

Map

S.NO Theme map Measure Maximum

Weightage

1 Land Use Type of land

cover

20

2 Slope Degree of

slope

20

3 Soil Thickness of

soil

15

4 Runoff Depth of

runoff

15

5 Geology Type of rock 10

6 Lineament Lineament

density

10

7 Drainage Drainage

density

10


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7. CONCLUSIONS:

Based on the suitableness index the

landslide condition levels area unit classified

into four categories. The susceptibleness

level decreases once the quality index is high

for a specific space. The areas which are

inclined for landslide are calculated as given

within the Below Table. The eastern region

of the watershed is below high inclined for

landslide whereas the villages within the

eastern aspect are beneath moderate

susceptible for landslide. The dense forest

that falls below the western region of the

watershed is found to be having intensity

susceptibleness. The village is discovered as

having low inclined for landslide than

different villages. The inclined maps of the

study space area unit shown in below.

Fig 10: Final Map

Susceptibility Classification

Susceptibility

Index

Susceptibility Class

0 – 185 Very High Susceptible

Area

185 285 High Susceptible Area

285 315 Moderate

Susceptible Area

315 400 Low Susceptible Area

Table 5: Susceptibility Classification

Landslide susceptible area

Different

categories

Area (km 2 )

% of

area

Zone of Very High and high susceptibility

13.26 90

Zone of

Moderate

Susceptibility

1.18 8

Zone of Low

Susceptibility

0.3 2

Table 6: Landslide susceptible area

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identification of landslide hazard …topographic sheet nos. 58 c/13, 58 c/9, 58 f/4. several...

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