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INTERNATIONAL JOURNAL OF GEOMATICS AND GEOSCIENCES Volume 2, No 1, 2011

© Copyright 2010 All rights reserved Integrated Publishing services

Research article ISSN 0976 – 4380

Submitted on September 2011 published on November 2011 121

RS & GIS Based Landslide Hazard Zonation of Mountainous Terrains A Study from Middle Himalayan Kullu District, Himachal Pradesh, India

Vishwa B. S. Chandel1, Karanjot Kaur Brar

2, Yashwant Chauhan

3

1- Map Curator, Centre of Advanced Study in Geography, Department of Geography, Panjab

University, Chandigarh

2- Associate Professor, Centre of Advanced Study in Geography, Department of Geography,

Panjab University, Chandigarh

3- Product Specialist (Remote Sensing), ESRI Muscat, Oman

[email protected]

ABSTRACT

Landslides are short lived and suddenly occurring natural phenomena; it is just a hazard

when it occurs in an uninhabited place, however it turns into a disaster causing extraordinary

landscape changes and destruction of life and property when it occurs in the vicinity of

human habitation. Landslides are particularly common and cause massive damage in

tectonically active Himalayas. This work conducts a landslide hazard zonation in western

Himalayan district of Kullu in Himachal Pradesh using remote sensing and GIS. The western

Himalayan district of Kullu with a location on the southern side of Pirpanjal mountain range,

an established history and inherent susceptibility to massive landslides has been chosen for

landslide hazard zonation. The satellite imageries of LANDSAT ETM+, IRS P6, ASTER

along with Survey of India (SOI) topographical sheets formed the basis for deriving baseline

information on various parameters like slope, aspect, relative relief, drainage density,

geology/lithology and land use/land cover. The weighted parametric approach was applied to

determine degree of susceptibility to landslides. The landslide probability values thus

obtained were classified into no risk, very low to moderate, high, and very high to severe

landslide hazard risk zones. The results show that over 80 per cent area is liable to high-

severe landslide risk and within this about 32 per cent has very high to severe risk.

Keywords: Landslide, Hazard Zonation, Remote Sensing & GIS.

1. Introduction

Landslide activities are intimately associated with the tectonically active Himalayan

Mountains (Sarkar et al. 1995; Rautela & Thakur, 1999; Anbalagan et al. 2008; Chauhan et al.

2010). Landslide is one of the most common natural hazards in Kullu district; it can be

disastrous with massive destruction to life and property and may also lead to large scale

landscape transformations. There are records of several massive landslides (Punjab

Government, 1926; The Tribune, 12 September 1995; Gardner, 2002; The Tribune, 18 March

2008) occurring in the past that caused massive damage to property and infrastructure along

with human casualties in the study area. The district is also experiencing large scale

developmental activities related to hydro-power, tourism and transport networks which are

leading to terrain alteration and other negative impacts on environment. These facts make it

essential to develop a Landslide Hazard Zonation (LHZ) delineating the threat area to reduce

the risk from potential landslides. Landslide hazard zonation (LHZ) demarcates an area into a

number of subclasses according to their susceptibility to landslide activities based on certain

selected parameters (Varnes, 1984; Hansen, 1984; Anbalagan 1992). Physiographic

RS & GIS Based Landslide Hazard Zonation of Mountainous Terrains: A Study from Middle Himalayan

Kullu District, Himachal Pradesh, India

Vishwa B. S. Chandel, Karanjot Kaur Brar, Yashwant Chauhan

International Journal of Geomatics and Geosciences

Volume 2 Issue 1, 2011 122

characteristics such as slope, aspect, relative relief, geological character, drainage and

landuse/land cover play a major role in deciding the potential sites for slope failure. Such

analysis is a complex task involving numerous factors affecting slope failure and requires

inclusion of several parameters and analytical techniques. Several scholars have proposed

different schemes for landslide hazard zonation using qualitative approaches or quantitative

approaches (Carrara et aI., 1977, 1978; Yin and Yan 1988; Choubey & Litoria 1990; Gupta &

Joshi, 1990; Pachauri & Pant 1992; Anbalagan & Singh, 1996; Soeters and van Westen,

1996; van Westen et al. 1997; Aleotti and Chowdhury 1999; van Westen, 2000; Dai & Lee,

2002; Lin and Tung, 2003; Mathew et al., 2007; Sharma and Kumar, 2008; Chauhan et al.,

2010, Das et al., 2010). These approaches to landslide hazard zonation range from

qualitative/semi quantitative techniques involving parameter-weighting method, weighted

landslide hazard mapping, geomorphological methods to quantitative techniques such as

multivariate statistical methods including linear regression, discriminant analysis and logistic

regression as well as bivariate statistical method for LHZ.

2. Study Area

Kullu district situated in the lesser Himalayas between 31º20' - 32º26' north latitudes and

76º59' - 77º50’ east longitudes possesses an intricate system of mountain ranges which are

the result of successive compression movements of the earth’s crust (Burrard and Hayden,

1933). The district is bounded by Pir-Panjal range in the north; Bara Bhangal in the

northwest; the Greater Himalayas in the eastern boundary and Dhauladhar range in the

southwest while River Satluj marks the southern boundary of the district (map 1). The district

has very high absolute relief ranging from 750-6200 meters. The geomorphological character

of Kullu is influenced by both glacial and fluvial processes (Sah & Mazari, 2007); the area is

broadly divided into glaciers & permanent snow fields, rocky/barren slopes, valley slopes &

ridges, and main valley floor. The glaciers & permanent snow fields are found in most of the

eastern parts above an elevation of 4500 meters. The barren/rocky surfaces occupy the lower

parts of glaciers and permanent snow fields while valley slopes occupy a large part in the

district and consist of steep to moderately steep slopes, ridges and narrow valleys where

slopes usually have an inclination of 30-40 degrees. The main valley floor of River Beas is

dominated by outwash fan, alluvial fans and river terraces.

The district has a total population of 381571 persons housed in 76902 households located in

172 villages and 4 towns. The average density of population in the district is 69 persons per

km². Kullu district is the most rapidly growing district in the state in terms of population; the

rural population grew by 24.89 per cent which was the highest rural growth in the state while

urban population growth was 43.22 per cent during 1991-2001. This growth is attributed to

the development of tourism industry, horticulture development and initiation of hydro-power

generation ventures on a large scale which has attracted large number of people from the

other areas.






Map 1: Kullu District: general physiography

2.1 Data Source, Methodology and Input Parameters

The analysis is based on maps from Survey of India and Geological Survey of India and

satellite imageries (table 1). A landslide occurrence database was generated from newspaper

archives for 1971-2009 and GPS measurements were taken during field survey. Various

thematic maps pertaining to slope, aspect, relative relief, drainage, geological structure and

landuse/land cover were generated with the help of ArcGIS 9.3 and ERDAS 9.3 software for

Kullu district. The slope, aspect and relative relief layers were derived from ASTER DEM

using ‘Modeler’ tools in ERDAS IMAGINE, while drainage density analysis was performed

using ‘Hydrology’ tools and ‘Fishnet’ analysis in ArcGIS. The NDVI analysis was

undertaken to enhance the spectral variation in LANDSAT ETM+ (2005) and IRS P6 (2005)

satellite imageries in order to derive meaningful land use/land cover classification

Table 1: Data type/source for landslide hazard zonation

DATA TYPE DATA DESCRIPTION USE/ PURPOSE

1 Topographical Sheet Scale 1:50,000

Satellite Data ASTER

Spatial Resolution 30m

DEM: Slope (degree), Aspect,

Relative Relief, Drainage

network and Density

2 LANDSAT ETM+

2005 and IRS-P6 LISS III 2005

Spatial Resolution 15m and

23.5m Land use/land cover

3 Geological Map Scale 1:250,000 Geology: Lithology and

structure 4 Field Data GPS Locations Landslide Locations

N

N

Vertical Exaggeration- 1:3






5 Secondary Data Source

Newspaper Archives 1971-

2009 Landslide Locations

Figure 1: Methodology for Landslide Hazard Zonation

The approach followed (figure 1) in this analysis is based on the empirical relationship

between landslide activity and causative factors. Inherent causative factors depending upon

their influence in causing slope instability were given rates/weights. Different classes within

each causative factor were also given weights according to their significance in causing

instability. The information on existing landslide sites collected during the field visits and

interpreted from the satellite data was also incorporated to arrive at a more accurate weighted

score for each causative factor and their respective sub classes. This formed the basis for

giving weight to each parameter and defining their relative significance in inducing landslides.

These weighted factor maps were overlaid using multivariate criteria analysis to prepare a

landslide hazard zonation (LHZ) map for Kullu district.

3 Analysis & Discussion

3.1 Slope and Aspect

Slope and aspect are important triggering factors that determine the hazardousness of an area.

The slope degree refers to the rate of change in elevation over distance with lower the slope

value representing flatter terrain and higher values representing steeper terrain (figure 2,

equation-I). Aspect defines the down slope direction of the maximum rate of change or the

direction of steepest slope in x-y plane (figure 2, equation-II).






In Kullu district gentle slopes (below 20°) form nearly 1/3 (34.25%) of total area of the

district and such slopes are found either along the river’s course or on ridge tops. The

moderately steep and steep slopes account for 35.35% and 24.55% area (map 2) respectively;

about 6 percent of the total area possesses very steep to precipitous (above 40°) slopes. The

aspect distribution in the district has an even distribution as all eight directions have 10-15

per cent of total area (map 3). The aspect has significance in understanding the slope stability.

Usually southeast (SE) to south (S) and southwest (SW) slopes are comparatively more prone

to slope failure and sliding activities.

3.2 Physiography and Relief

The area possesses high relative or local relief which refers to the difference between the

highest and the lowest altitude in an area. The higher values indicate rapid rise in altitude and

presence of faults, lower relief signifies mature topography. A determinant of morphological

character of an area, relative relief has noteworthy alliance with landslide by acting as a

triggering factor. As a risk agent, relative relief plays a decisive role in the vulnerability of

settlements, transport network and land. In Kullu district, there is wide variation in relative

relief (map 4) ranging from low to very high. About 13.39 %, 60.13% and 26.48 % area has

low (below 200m), moderate (200-400m) and high (above 400m) relative relief respectively.

INPUT FACTOR/PARAMETRIC LAYERS

Map 2

Map 3

Figure 2 SLOPE DEGREE AND ASPECT CALCULATION

SLOPE (Degrees) = ATAN (√([dz/dx]2 + [dz/dy]2)) * 57.29578 ------ equation I Where: dz/dx = The rate of change in the x direction, and dz/dy = The rate of change in the y direction

ASPECT = 57.29578 * atan2 ([dz/dy] - [dz/dx]) ------------------ equation II Where [dz/dx] = The rate of change in the x direction and [dz/dy] = The rate of change in

the y direction.






Map 4

Map 5

INPUT FACTOR/PARAMETRIC LAYERS

Map 6

Map 7

3.3 Geological Structure

In Kullu district, a broad central zone of crystalline unfossilliferous rocks consisting of

granite, gneisses, schist and other metamorphic rocks forms the axis of the Himalayas

(Kayastha, 1964). Five major litho-tectonic units (map 5) express the geology of the area and

these are referred to as (1) Vaikrita Group (2) Jutog Group (3) Kullu Group (4) Larji Group,

and (5) Rampur Group. The area is dissected by several major thrusts, namely Jutogh Thrust,






Kullu thrust and Vaikrita thrust along with several local faults/lineaments. These thrusts are

still active and play a major role in the neo-tectonics of the area (Choubey et al., 2007). The

Jutogh thrust separates rocks belonging to Kullu group and Jutogh group while Kullu thrust

or Chail thrust (Bhargava and Bassi, 1994) defines boundary between the rocks of Rampur-

Larji group and Kullu group. Structurally, the main Kullu Valley is a synclinorium/gently

folded antiform having River Beas following its axial plane along a fault running NNW-SSE

from the upper catchment to near Aut where it is intersected by a cross fault almost at right

angles (Sah & Mazari, 2007). This fault is a dextral tear fault with a dislocation of nearly 1.5

km (Shankar & Dua, 1978). The rivers follow these fault traces which are well reflected in

the trellis like drainage pattern (Das et al. 1979). The rivers Beas, Parbati, Hurla Nala, Sainj

Khad, Tirthan Khad etc. follow such fault traces. The area west of river Beas from Bhuntar

and south of Parbati River to Rampur along the course of Satluj River is very unique.

Structurally the area forms 'window in a window' structure also known as Kullu-Larji-

Rampur Window (KLRW). Here, rocks of Kullu formation thrust over rocks of Larji group as

well as Banjar group thrust over Larji group.

3.4 Drainage Character

The drainage patterns in the area are an outcome of long time interaction between the

geological structure, topography and slope. The overall drainage reflects early stage of

dendritic pattern with visible traces of parallel dendritic and trellis patterns in between. A

mathematical expression of drainage morphometry of an area is drainage density which is a

measure of the length of stream channel per unit area of drainage basin (figure 3). The

measurement of drainage density is useful in determining landscape dissection and runoff

potential. Higher values denote higher degree of dissection of land, as well as indicate the

higher probability of slope failure.

The drainage density in the study area (map 6) can be divided into low (below 1.0 km²) to

very high (above 3.0 km²). About 2/3 area has low density mostly comprising of mountain

tops, major ranges and ridges. The valley floors of all the major streams have high to very

high drainage density. Such areas account for only 8 per cent of total area of the district.

3.5 Land use/land cover

Landuse/land cover analysis reflects relationships between land use, disaster risk and

vulnerability to disaster events. The landuse/ land cover analysis for this study is based upon

LANDSAT ETM+ (2005) and (2000), IRS-P6 LISS-III (2005) and ASTER DEM. The

landuse classification of mountainous terrains suffer from certain drawbacks as high relief

results in shadow areas and confusion between land use classes like barren rocky surfaces,

water bodies and settlements. To reduce the error in classification, Normalized Difference

Vegetation Index (NDVI) was calculated to enhance the spectral difference between different

objects. NDVI is based on the formula:

Figure 3 DRAINAGE DENSITY CALCULATION

Drainage Density (Dd) = Stream Length (L)/ Basin Area (A)






NDVI= (NIR-R)/(NIR+R)

NIR represents spectral reflectance of objects in near infrared (NIR) band while R represents

the same in the red band. In addition, ASTER digital elevation model (DEM) was used to

eliminate the possibility of land use classes being wrongly categorized by adding some

criteria. The maximum likelihood classification (MLC) algorithm which is the most accurate

classifier (Foody et al., 1992; Richards and Jia, 1999; Saha et al. 2005) has been used. A

large part of the district which includes glaciers (17.61%), rocky barren surfaces (22.07%),

forests (32.86%), and open pasture lands (8.87%) is beyond the direct use by population. The

agriculture/horticulture activities are spread over 10 per cent of the total area while about

4.48 per cent is occupied by settlements/built up area. This implies that land use in study area

under direct human occupation has very high intensity particularly in the valley floor region.

This can be particularly seen in the Kullu valley of river Beas (map 7). Another very

important factor that emerges from the analysis with respect to the agriculture/horticulture

and built-up land use is that the officially declared area under revenue is just 10% of the total

geographical area of the district, whereas the combined sum of these two classes as derived

from this analysis is about 15% of the same. This additional area indicates the encroachment

on government land which is at locations vulnerable to disasters - these being largely in the

vicinity of the streams/river and other unsuitable sites.

4. Landslide Hazard Analysis: Conclusion/Findings

The analysis shows that almost entire district is prone to landslide risk of varying magnitude.

Over 80 per cent area is liable to high-severe landslide risk and within this about 32 per cent

has very high to severe risk while about 48 per cent of the total area has high risk of landslide

occurrence (table 3). Such areas include southern slopes of Pir-Panjal range in Rohtang-

Manali area, southern off-shoot of Pir-Panjal forming western border of Kullu valley and

slopes on the northern parts of Parbati river valley particularly in the areas around Malana

valley (map 8). Another section of high-severe risk comprise of Kullu-Larji-Rampur (KLR)

geological window which spread over Hurla, Sainj and Banjar areas of district. The rocks are

not only highly deformed but the area also possesses active faults/thrusts. The northern part

of Nirmand tahsil also falls in this very high landslide risk class.

Table 3: Kullu district: landslide hazard zones

Landslide Risk Category Area (km.²) Area (per cent)

1 No Risk 23.22 0.42

2 Low-Moderate 1068.65 19.42

3 High 2650.19 48.16

4 Very High-Severe 1960.94 32.00

Total 5503 100 Source: ASTER DEM, LANDSAT ETM+ (2005); IRS P6 LISS III (2005)

About 20 per cent area of the district has low to moderate risk of landslides. These include

the valley floors mainly of Kullu valley between Manali and Bajaura, parts of Ani tahsil and

adjoining areas, and high altitude areas of permanent snow and glaciers. Very small area

(0.42%) constituting river channel/streams is devoid of landslide risk.






The susceptibility to landslides is inherent in the natural characteristics of the landscape and

there is a definite relationship between landslide occurrence and geo-physical setup of the

area. The high slope angles, drainage density, high local relief and geological structure

produce suitable conditions for landslide occurrence; the torrential rainfall in monsoon season

is invariably the immediate trigger. Out of total of 49 landslides during 1971-2009, nearly

63.27 per cent occurred in monsoons; 26.53 per cent were recorded during winter months

(January-March) while pre and post monsoon seasons together recorded less than 10 per cent

landslides. In addition, the past events show that these have close association with the landuse

and were confined to the built-up (roads) and agricultural lands. The intensification of human

activities, encroachment on vulnerable land, uncontrolled settlement and rampant expansion

of roads adds to landslide vulnerability. It is pertinent to note that landslide activity is largely

confined to the inhabited part of the district primarily in the vicinity of the rivers and roads

and this is substantiated by field visits and data. These are the prime locations of all human

activities and this enhances the risk potential of this disaster.

Source: ASTER DEM, LANDSAT ETM+ (2005); IRS P6 LISS III (2005)

Map 8






The present study demonstrates high degree of hazarduousness of Kullu district of Himachal

Pradesh, India. The higher degree of landslide hazard is associated with geo-physical

elements especially slope, relative relief and lithology of the area. The presence of faults,

particularly in the vicinity of human occupancy enhances vulnerability. Vulnerability is

compounded by mindless and rampant expansion of settlement onto vulnerable land and

ambitious road construction that aids this settlement. In addition, anthropogenic activities

play a significant role in triggering such events.

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