Mohammad different datasets which are marked as causative

 

Mohammad Ibrahim Mazhar*

aInstitute of Geographical Informations Systems, School of Civil and
Environmental Engineering, National University of Scinces and Technology,
Islamabad.

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Abstract. The frequency of landslide occurrence in Balakot Valley along
the main road was very high which often blocks the main road of the valley
causing severe problems for the locals and the domestic as well as
international tourists which use that road in summers to reach famous tourist
spots in the country such as Gilgit, Hunza, Skardu, Naran and Kaghan etc.
Therefore a need of measuring different aspects related to landslides and the
cause of their occurrence was considered necessary to further devise mitigating
plans to reduce the destructions and the problems caused by the frequent
occurring of landslides. A qualitative index based approach in GIS environment
was applied to assess the landslide susceptibility in the region which assumes
that the causative factors triggering future landslides will be the same
factors that have influenced landslides in the past. In the first step raster
layers of different datasets which are marked as causative factors such as
slope, aspect, elevation, land use, land cover, distance from roads, distance
from rivers for determination and analysis of occurrence of landslides were
prepared followed by performing multi-criteria analysis (MCA) using the
technique of Analytical hierarchy process (AHP) and assigning numerical weights
to each causative factor to measure landslide susceptibility and finally
preparing susceptibility map to classify the study area into very high, high,
moderate, and low susceptible zones. The landslide susceptibility reveals that
most of the study area falls in high and very high susceptibility zones because
of the presence of faults and very high steep slopes. Therefore, those areas
which are near the faults and on steep slopes are unsafe for future
construction and other developments. On the basis of these results, Balakot
city, is considered and predicted to be unsafe and is likely to be prone to
landslide in the future. However moderate susceptible zones require some
geotechnical investigation before any construction.

 

 

1  
Introduction

Landslide susceptibility map is considered very
important for engineers, geologists, and land use planners for prevention and
mitigation of landslide hazard in the area. Various causes and factors involved
in triggering landslides include morphological, topographical, and geological
aspects. The occurrence of landslide differs from location to location.
Landslides is one of the most prevalent hazards in the Himalayas and can be
particularly devastating when it occurs adjacent to human settlements and
infrastructures, such as towns, roads, bridges and utilities1. Landslides triggered by the
2005 Kashmir earthquake have the highest rate of occurrence in Balakot and its
surrounding areas which is common in the Himalaya because of the active
seismicity, great relief, heavy monsoon rains, and accelerated erosion due to
deforestation and construction2. In the wake of this recent disaster,
it is ever more apparent that new standards in home and road construction, and
planning based on geomorphic and tectonic data are needed to help mitigate
future disasters. For effective landslide hazard reduction the analysis of
slope failures requires a comprehensive analysis of the landscape using modern
technologies and data exchange to ensure that the proper procedures and
policies are put into effect in a timely fashion. Landslides are considered as
third in the list of natural hazard in terms of degree of hazard a natural
disaster may pose. Like many other developing countries, Pakistan has been
frequently subjected to a variety of natural hazards including landslides3. Apart from the vast alluvial
Indus plains where people are mostly vulnerable to devastating floods, a
significant part of the country is geomorphological active mountainous terrain.
Being underestimated, landslide hazard is not a much investigated subject in
Pakistan. External or internal factors, e.g. slope steepening, removal of
support from slope, adding water in different forms, inherently weak material,
etc. may trigger landslides. Therefore, landslide susceptibility mapping is an
important step prior to landslide assessment planning, management and disaster
mitigation. Identification and detailed assessment of this underestimated
hazard is needed in effective landslide hazard reduction through disaster
mitigation planning and development strategies

 

The work presented here addresses the sites
investigation problem to identify the areas having potential to experience
landslides. Assessment of spatial problem may involve taking into consideration
of numerous criteria. This study presents landslide susceptibility analysis for
the part of tehsil Balakot, NW Himalayas, Pakistan, in order to reduce the
landslide damages in the future. The study area was selected because it was one
of the worst landslide-affected areas during and after the 2005 Kashmir
earthquake. Moreover, a large extent of landslide occurrence in this area was
undocumented. This research is an attempt to produce landslide susceptibility
map and indicate the hazard zones that are susceptible for landslides in the
future.

 

1.1.Study
Area

The
study was carried out on is a town on Balakot tehsil which lies in the Mansehra
District in the Khyber-Pakhtunkhwa province of Pakistan
located at the banks of Kunhar river .This city has a historical importance
regarding natural disasters as it was completely destroyed in a
destructive earthquake on 8 October 2005, but was later rebuilt with the
assistance of the Government of Pakistan and Saudi Public Assistance
for Pakistan Earthquake Victims (SPAPEV). The fault line of BBF
(Bagh-Balkot) almost passes through the heart of the city and most common
types of landslides in Balakot are debris falls triggered by rainfalls.

Figure 1.
Study Area: Balakot

2  
Materials and Methods

In this study it is believed that the accuracy of (GIS)
based susceptibility mapping increases with the availability of data about
event-controlling parameters such as lithology, structure, tectonics,
geomorphology, topography, precipitation, temperature, infiltration, runoff,
land cover, and road construction. Unfortunately, due to the limitation of data
availability for the whole study area, a qualitative index based approach in
GIS environment was applied to assess the landslide susceptibility in the
region which assumes that the causative factors triggering future landslides
will be the same factors that have influenced landslides in the past. As there
is no universal guidelines for selecting the parameters that influence
landslides in susceptibility mapping slope, aspect, elevation, land use, land
cover, distance from roads, distance from rivers were selected as causative
factors as a result of the research consequences and field studies related with
active landslides.

 

Data/Tools

Details

Digital Elevation Model

Aster GDEM (30 × 30 meters)

Landsat 8 satellite Imagery

 (30 m resolution)

ArcMap 10.1.4

Collecting, Analyzing,
Processing and manipulating Digital Elevation Model (DEM)

Easy AHP Tool

multi-criteria approach to assist decision making

 

Table1. Tools and data used for landslide susceptibility

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

. Table2.Methodology flowchart of the study

 

2.1. Slope angle

The main parameter of the slope
stability analysis is the slope angle which is directly related to the
landslides and is frequently used in preparing landslide susceptibility map.
Movement of rock mass down the slope is extremely common when slopes are
steeper than the natural angle and when there is not enough strength in the
soil to stop  slope failure. The angle is
typically 25–40° for unconsolidated materials to inhibit rock mass movement.
The GIS work shows that most of the land sliding occurred on slopes of (31–45).
Land sliding is less on gentler (16–30) slopes, with least occurring on very
gentle (0–15°) and very steep (> 45°) slope.

 

 

 

 

Figure2. Slope Angles classes

2.2. Aspect

Aspect map of
the study area was produced to show the relationship between aspect and landslide.
Analyses for the study area revealed that there are more southwestern and
western facing slopes than other directions which make those hill slopes most
vulnerable to land sliding.

 

 

 

 

 

Figure3. Aspect classes

2.3. Elevation

GIS analysis shows that most of the land sliding occurred at
elevations below 2500 meters.Land sliding was scarce at high elevations
above 3000 feet.

 

 

2.4. Distance to the Road/Streams

Buffer zones
were set to 25 m and 50 m. The GIS work showed that much of the land
sliding occurred within the buffer zones along roads and the main river which
is Kunhar River. These results highlight the human impact and effect on slope
failures and conclude that human factors contributed to a large percentage of
slope failures.

2.5. Land Cover/Land use

The land cover
map is one of the important controlling factors for landslide occurrence. To
prepare land cover map, the Landsat 8 image obtained from the
official website of USGS. The map was prepared by using a supervised
classification in ERDAS imagine software and six classes were identified.

.

 

Techniques used

3.1 Multi-criteria analysis

In this study, multi-criteria evaluation (MCE) method was
used for landslide susceptibility mapping. MCE is a decision-making-supportive
procedure in order to obtain a single-composite resultant by using a set of
event-controlling parameters (Malczewski 1999). MCE combines these criteria to
build a single composite. A single composite is obtained by assigning weight
values to each attribute. The expert opinion, field scenario, local variability
in geology, and land cover pattern get importance in this method. There are a
number of various methods used in MCE, some of them qualitative in nature such
as the Analytical Hierarchy Process (AHP; Saaty 1990) and weighted linear
combination (WLC). Other methods are purely statistical in nature such as
bivariate statistical analyses (BSA) and the multivariate statistical approach
(MSA; Ayalew et al. 2004).

3.1.1 AHp

The AHP is a theory of calculations through pairwise
comparisons of different factors and based on the expert judgments to gain
priority scales (Saaty 2008). It involves a matrix-based pairwise comparison of
the contributing factors for landsliding. For this study, in a pairwise
comparison matrix, each factor was rated between 1 and 9 against every
intersecting factor, when the factor on the vertical axis was more important
than the factor on the horizontal axis. Conversely, when the factor on the
vertical axis was less important than the factor on the horizontal axis, the
value varies between 1/2 and 1/9 (Saaty 2008). Both weight values and rating
values were assigned through expert knowledge and field observations and
calculated through pairwise comparison matrix using a common rating scale. It
is also necessary total weight must be one. Pairwise comparison matrix scale is
shown in Table 1. In order to understand the consistency of judgments, a
consistency ratio was also calculated

 

Pair-wise comparison matrix as described by Saaty
(1990)

Importance

Definition

Explanation

1

Equal importance

Contribution to objective is equal

3

Moderate importance

Attribute is slightly favored over another

5

Strong importance

Attribute is strongly favored over another

7

Very strong importance

Attribute is very strongly favored over another

9

Extreme importance

Evidence favoring one attribute is of the highest possible
order of affirmation

 

3.1.2Consistency ratio (CR)

           
The quality of the comparison is described by
the consistency ratio (CR).A (CR) close to 0 indicates the probability that the
matrix’s rating was randomly generated. Saaty (1990) recommended the CR to
be < 0.1 to be valid. The CR in our study is 0.05   3.1.3 Weights Allocation Slope is the most heavily weighted factor followed by aspect and elevation   Land cover and distance to roads have a moderate influence     Pair-wise comparison matrix for calculating factor weights   Attribute Slope Elevation Aspect Land Cover Roads Streams Factor weights Slope 1 0.0267 Elevation 2 1 0.0358 Aspect 6 5 1 0.1607 Land Cover 7 6 3 1 0.2840 Roads 4 4 1/3 1/5 1 0.0790 Streams 4 4 1/3 1/5 1 1 0.0790   Landslide susceptibility map               After applying the AHP technique on raster data layers, the resultant map was reclassified into four susceptible zones as q   Very high q   High q   Moderate q   Low   Results Ø  The landslide susceptibility reveals that most of the study area falls in high and very high susceptibility zones because of the presence of faults and very high steep slopes Ø   Therefore, those areas which are near the faults and on steep slopes are unsafe for future construction and other developments Ø  On the basis of these results, Balakot city, is considered and predicted to be unsafe and is likely to be prone to landslide in the future. Ø   However moderate susceptible zones require some geotechnical investigation before any construction.

 

Mohammad Ibrahim Mazhar*

aInstitute of Geographical Informations Systems, School of Civil and
Environmental Engineering, National University of Scinces and Technology,
Islamabad.

We Will Write a Custom Essay Specifically
For You For Only $13.90/page!


order now

 

Abstract. The frequency of landslide occurrence in Balakot Valley along
the main road was very high which often blocks the main road of the valley
causing severe problems for the locals and the domestic as well as
international tourists which use that road in summers to reach famous tourist
spots in the country such as Gilgit, Hunza, Skardu, Naran and Kaghan etc.
Therefore a need of measuring different aspects related to landslides and the
cause of their occurrence was considered necessary to further devise mitigating
plans to reduce the destructions and the problems caused by the frequent
occurring of landslides. A qualitative index based approach in GIS environment
was applied to assess the landslide susceptibility in the region which assumes
that the causative factors triggering future landslides will be the same
factors that have influenced landslides in the past. In the first step raster
layers of different datasets which are marked as causative factors such as
slope, aspect, elevation, land use, land cover, distance from roads, distance
from rivers for determination and analysis of occurrence of landslides were
prepared followed by performing multi-criteria analysis (MCA) using the
technique of Analytical hierarchy process (AHP) and assigning numerical weights
to each causative factor to measure landslide susceptibility and finally
preparing susceptibility map to classify the study area into very high, high,
moderate, and low susceptible zones. The landslide susceptibility reveals that
most of the study area falls in high and very high susceptibility zones because
of the presence of faults and very high steep slopes. Therefore, those areas
which are near the faults and on steep slopes are unsafe for future
construction and other developments. On the basis of these results, Balakot
city, is considered and predicted to be unsafe and is likely to be prone to
landslide in the future. However moderate susceptible zones require some
geotechnical investigation before any construction.

 

 

1  
Introduction

Landslide susceptibility map is considered very
important for engineers, geologists, and land use planners for prevention and
mitigation of landslide hazard in the area. Various causes and factors involved
in triggering landslides include morphological, topographical, and geological
aspects. The occurrence of landslide differs from location to location.
Landslides is one of the most prevalent hazards in the Himalayas and can be
particularly devastating when it occurs adjacent to human settlements and
infrastructures, such as towns, roads, bridges and utilities1. Landslides triggered by the
2005 Kashmir earthquake have the highest rate of occurrence in Balakot and its
surrounding areas which is common in the Himalaya because of the active
seismicity, great relief, heavy monsoon rains, and accelerated erosion due to
deforestation and construction2. In the wake of this recent disaster,
it is ever more apparent that new standards in home and road construction, and
planning based on geomorphic and tectonic data are needed to help mitigate
future disasters. For effective landslide hazard reduction the analysis of
slope failures requires a comprehensive analysis of the landscape using modern
technologies and data exchange to ensure that the proper procedures and
policies are put into effect in a timely fashion. Landslides are considered as
third in the list of natural hazard in terms of degree of hazard a natural
disaster may pose. Like many other developing countries, Pakistan has been
frequently subjected to a variety of natural hazards including landslides3. Apart from the vast alluvial
Indus plains where people are mostly vulnerable to devastating floods, a
significant part of the country is geomorphological active mountainous terrain.
Being underestimated, landslide hazard is not a much investigated subject in
Pakistan. External or internal factors, e.g. slope steepening, removal of
support from slope, adding water in different forms, inherently weak material,
etc. may trigger landslides. Therefore, landslide susceptibility mapping is an
important step prior to landslide assessment planning, management and disaster
mitigation. Identification and detailed assessment of this underestimated
hazard is needed in effective landslide hazard reduction through disaster
mitigation planning and development strategies

 

The work presented here addresses the sites
investigation problem to identify the areas having potential to experience
landslides. Assessment of spatial problem may involve taking into consideration
of numerous criteria. This study presents landslide susceptibility analysis for
the part of tehsil Balakot, NW Himalayas, Pakistan, in order to reduce the
landslide damages in the future. The study area was selected because it was one
of the worst landslide-affected areas during and after the 2005 Kashmir
earthquake. Moreover, a large extent of landslide occurrence in this area was
undocumented. This research is an attempt to produce landslide susceptibility
map and indicate the hazard zones that are susceptible for landslides in the
future.

 

1.1.Study
Area

The
study was carried out on is a town on Balakot tehsil which lies in the Mansehra
District in the Khyber-Pakhtunkhwa province of Pakistan
located at the banks of Kunhar river .This city has a historical importance
regarding natural disasters as it was completely destroyed in a
destructive earthquake on 8 October 2005, but was later rebuilt with the
assistance of the Government of Pakistan and Saudi Public Assistance
for Pakistan Earthquake Victims (SPAPEV). The fault line of BBF
(Bagh-Balkot) almost passes through the heart of the city and most common
types of landslides in Balakot are debris falls triggered by rainfalls.

Figure 1.
Study Area: Balakot

2  
Materials and Methods

In this study it is believed that the accuracy of (GIS)
based susceptibility mapping increases with the availability of data about
event-controlling parameters such as lithology, structure, tectonics,
geomorphology, topography, precipitation, temperature, infiltration, runoff,
land cover, and road construction. Unfortunately, due to the limitation of data
availability for the whole study area, a qualitative index based approach in
GIS environment was applied to assess the landslide susceptibility in the
region which assumes that the causative factors triggering future landslides
will be the same factors that have influenced landslides in the past. As there
is no universal guidelines for selecting the parameters that influence
landslides in susceptibility mapping slope, aspect, elevation, land use, land
cover, distance from roads, distance from rivers were selected as causative
factors as a result of the research consequences and field studies related with
active landslides.

 

Data/Tools

Details

Digital Elevation Model

Aster GDEM (30 × 30 meters)

Landsat 8 satellite Imagery

 (30 m resolution)

ArcMap 10.1.4

Collecting, Analyzing,
Processing and manipulating Digital Elevation Model (DEM)

Easy AHP Tool

multi-criteria approach to assist decision making

 

Table1. Tools and data used for landslide susceptibility

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

. Table2.Methodology flowchart of the study

 

2.1. Slope angle

The main parameter of the slope
stability analysis is the slope angle which is directly related to the
landslides and is frequently used in preparing landslide susceptibility map.
Movement of rock mass down the slope is extremely common when slopes are
steeper than the natural angle and when there is not enough strength in the
soil to stop  slope failure. The angle is
typically 25–40° for unconsolidated materials to inhibit rock mass movement.
The GIS work shows that most of the land sliding occurred on slopes of (31–45).
Land sliding is less on gentler (16–30) slopes, with least occurring on very
gentle (0–15°) and very steep (> 45°) slope.

 

 

 

 

Figure2. Slope Angles classes

2.2. Aspect

Aspect map of
the study area was produced to show the relationship between aspect and landslide.
Analyses for the study area revealed that there are more southwestern and
western facing slopes than other directions which make those hill slopes most
vulnerable to land sliding.

 

 

 

 

 

Figure3. Aspect classes

2.3. Elevation

GIS analysis shows that most of the land sliding occurred at
elevations below 2500 meters.Land sliding was scarce at high elevations
above 3000 feet.

 

 

2.4. Distance to the Road/Streams

Buffer zones
were set to 25 m and 50 m. The GIS work showed that much of the land
sliding occurred within the buffer zones along roads and the main river which
is Kunhar River. These results highlight the human impact and effect on slope
failures and conclude that human factors contributed to a large percentage of
slope failures.

2.5. Land Cover/Land use

The land cover
map is one of the important controlling factors for landslide occurrence. To
prepare land cover map, the Landsat 8 image obtained from the
official website of USGS. The map was prepared by using a supervised
classification in ERDAS imagine software and six classes were identified.

.

 

Techniques used

3.1 Multi-criteria analysis

In this study, multi-criteria evaluation (MCE) method was
used for landslide susceptibility mapping. MCE is a decision-making-supportive
procedure in order to obtain a single-composite resultant by using a set of
event-controlling parameters (Malczewski 1999). MCE combines these criteria to
build a single composite. A single composite is obtained by assigning weight
values to each attribute. The expert opinion, field scenario, local variability
in geology, and land cover pattern get importance in this method. There are a
number of various methods used in MCE, some of them qualitative in nature such
as the Analytical Hierarchy Process (AHP; Saaty 1990) and weighted linear
combination (WLC). Other methods are purely statistical in nature such as
bivariate statistical analyses (BSA) and the multivariate statistical approach
(MSA; Ayalew et al. 2004).

3.1.1 AHp

The AHP is a theory of calculations through pairwise
comparisons of different factors and based on the expert judgments to gain
priority scales (Saaty 2008). It involves a matrix-based pairwise comparison of
the contributing factors for landsliding. For this study, in a pairwise
comparison matrix, each factor was rated between 1 and 9 against every
intersecting factor, when the factor on the vertical axis was more important
than the factor on the horizontal axis. Conversely, when the factor on the
vertical axis was less important than the factor on the horizontal axis, the
value varies between 1/2 and 1/9 (Saaty 2008). Both weight values and rating
values were assigned through expert knowledge and field observations and
calculated through pairwise comparison matrix using a common rating scale. It
is also necessary total weight must be one. Pairwise comparison matrix scale is
shown in Table 1. In order to understand the consistency of judgments, a
consistency ratio was also calculated

 

Pair-wise comparison matrix as described by Saaty
(1990)

Importance

Definition

Explanation

1

Equal importance

Contribution to objective is equal

3

Moderate importance

Attribute is slightly favored over another

5

Strong importance

Attribute is strongly favored over another

7

Very strong importance

Attribute is very strongly favored over another

9

Extreme importance

Evidence favoring one attribute is of the highest possible
order of affirmation

 

3.1.2Consistency ratio (CR)

           
The quality of the comparison is described by
the consistency ratio (CR).A (CR) close to 0 indicates the probability that the
matrix’s rating was randomly generated. Saaty (1990) recommended the CR to
be < 0.1 to be valid. The CR in our study is 0.05   3.1.3 Weights Allocation Slope is the most heavily weighted factor followed by aspect and elevation   Land cover and distance to roads have a moderate influence     Pair-wise comparison matrix for calculating factor weights   Attribute Slope Elevation Aspect Land Cover Roads Streams Factor weights Slope 1 0.0267 Elevation 2 1 0.0358 Aspect 6 5 1 0.1607 Land Cover 7 6 3 1 0.2840 Roads 4 4 1/3 1/5 1 0.0790 Streams 4 4 1/3 1/5 1 1 0.0790   Landslide susceptibility map               After applying the AHP technique on raster data layers, the resultant map was reclassified into four susceptible zones as q   Very high q   High q   Moderate q   Low   Results Ø  The landslide susceptibility reveals that most of the study area falls in high and very high susceptibility zones because of the presence of faults and very high steep slopes Ø   Therefore, those areas which are near the faults and on steep slopes are unsafe for future construction and other developments Ø  On the basis of these results, Balakot city, is considered and predicted to be unsafe and is likely to be prone to landslide in the future. Ø   However moderate susceptible zones require some geotechnical investigation before any construction.

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