Landslide Susceptibility Zonation

Using

Analytic Hierarchy Process – A case study from

Kalimpong-I C.D.Block, Darjeeling District, West

Bengal

Presented bySuchismita Mukherjee

Outline

Concept of landslide

Necessity of landslide susceptibility zonation

Analytic Hierarchy Process

Application of AHP into LSZ mapping

Conclusion

Concept of Landslide geological phenomenon which includes a wide range of ground movement.

can occur in offshore, coastal and onshore environments.

action of gravity is the primary driving force for a landslide to occur , --  other contributing factors affecting the original slope stability.

triggering factors -- oversteepening of slopes by erosion associated with rivers,

glaciers, or ocean waves; heavy snowmelt which saturates soil and rock; or

earthquakes that lead to the failure of weak slopes.

II

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JL. NO. MOUZA NAME JL. NO. MOUZA NAME040 KAFFIR FOREST 063 PEMLING FOREST059 SLOK BHIR KHAS MAHAL 061 LULAGAON KHAS MAHAL058 YOKPRINTAM KHAS MAHAL 064 PEMLING KHAS MAHAL087 CHUNA BHATIBAZAR D.I.F. 060 SAMAL BONG KHAS MAHAL089 UTTAR FULBARI KHAS MAHAL 071 TUNANG FOREST085 MANG PONG FOREST 062 LULAGAON FOREST086 LISH FOREST 074 RIYONG FOREST084 PANBU FOREST 041 KAFFIR KHAS MAHAL090 RAMTHI FOREST 073 RING KING PONG FOREST088 CHURANTHI FOREST 072 COMESI FOREST066 NOBGAON KHAS MAHAL 042 KANKE BONG KHAS MAHAL081 LISHCATCHMENT AREA FOREST 054 TASHIDING FOREST083 GULLING FOREST 057 BONG KHAS MAHAL082 YANG MAKUM KHAS MAHAL 052 TISTA BAZAR D.I.F.067 PARINGAR KHAS MAHAL 051 MANGBER FOREST091 SUNTALAYKHAS MAHAL 053 MANGWA FOREST076 RAMBI BAZAR D.I.F. 055 KALIMPONG KHAS MAHAL065 NIMBONG KHAS MAHAL II KALIMPONG (M)069 SAMETHERKHAS MAHAL 046 PUDUNG KHAS MAHAL068 SAMTHER FOREST 048 DUNGRA KHAS MAHAL080 SURUK KHAS MAHAL 047 SINDIBONG KHAS MAHAL078 BIRIK FOREST 045 ICHA KHAS MAHAL075 TURZAM FOREST 050 KALIMPONG DANSONG FOREST077 RIAYANG RAILWAY STATION 028 HOMES ST.AND GRAIHMS079 MAZEOK FOREST 049 BHALUKHOP KHAS MAHAL070 SINGI KHAS MAHAL 026 BHALUKHOP FOREST

Index Map of Darjeeling District

List of Mouza with J.L. No. (1991 Census)

West Bengal State Council of Science and Technology

Prepared by:

Index

J.L of kalimpong-I C.D.Block

Index Map of West BengalLOCATION MAP KALIMPONG I C.D. BLOCK, DARJEELING DISTRICT, WEST BENGAL

Necessity of

Landslide Susceptibility Zonation

most widespread natural phenomena that are witnessed in the Darjeeling

Himalayan terrain.

causing colossal damage to property and infrastructure, besides loss of

human lives and livestock almost every year.

to reduce the risk emanating from potential landslide, there is a need to

generate a comprehensive Landslide Susceptibility Zonation (LSZ) map

for effective and efficient disaster management, risk and vulnerability

assessment etc.

Methods of landslide susceptibility zonation :

Information Value method

Index Overlay

Weight of Evidence

fuzzy logic

Analytic Hierarchy Process

Artificial Neural Network

“ The Analytic Hierarchy Process (AHP) is a theory of measurement

through pairwise comparisons and relies on the judgements of

experts to derive priority scales .“

- Thomas L. Saaty

Analytic hierarchy process developed by Thomas L. Saaty in 1980.

popular and widely used method for multi-criteria decision making.

Allows the use of qualitative, as well as quantitative criteria in evaluation.

Problems are decomposed into a hierarchy of criteria and alternativesProblem

Criteria 1

Criteria 1.1

Criteria 1.2

….

Criteria 2

Criteria 2.1

Criteria 2.2

…..

Criteria 3 Criteria 4

……

Alternatives 2Alternatives 1 Alternatives 3

Criteria for landslide susceptibility zonation :

I. Slope

II. Soil

III. Lithology

IV. Darinage density

V. Lineament density

each layer used in zoning is broken into smaller factor - more precise is the

judgment

The pair wise comparisons are made using a scale of absolute judgements -

how much more, one element dominates another with respect to a given

attribute.

The judgements may be inconsistent, and how to measure inconsistency

and improve the judgements, when possible to obtain better consistency is a

concern of the AHP

Using the priorities scale – global priority obtained

Methodology of

Analytic Hierarchy Process

Step 1: Structure a hierarchy. Define the problem, determine the criteria and identify the alternatives.

Step 2: Make pairwise comparisons. Rate the relative importance between each pair of decision alternatives and criteria.

Step 3: Synthesize the results to determine the best alternative. Obtain the final results.

Step 4: Check for consistancy

Both qualitative and quantitative information can be compared using informed judgements to derive weights and priorities.

Landslide Susceptibility Zonation

using

Analytic Hierarchy Process

An important part of Analytic Hierarchy Process is to accomplish these three steps :

State the objective:

- select susceptible zone of landslide in

Kalimpong Block-I

Define the criteria:

• slope

• Soil

• Lithology

• drainage density

• lineament density

Pick the alternatives:

- zone 1, zone 2, zone 3

This information is then arranged in hierarchical tree

Select landslide susceptabile zones

Slope Soil Lithology

Lineament Density

Drainage Density

Objective

Criteria

Alternatives

Zone 1 Zone 2 Zone 3

the information is then synthesized to determine relative rankings of alternatives

both qualitative and quantitative criteria can be compared using informed judgments

to derive weights and priorities

Determination of the relative importance of the criteria

Pairwise comparisons are made with the grades ranging from 1-9

If attribute A is absolutely more important than attribute B and is

rated at 9, then B must be absolutely less important than A and is

valued at 1/9.PREFERENCE LEVEL

Equally preferred

Equally to moderately preferred

Moderately preferred

Moderately to strongly preferred

Strongly preferred

Strongly to very strongly preferred

Very strongly preferred

Very strongly to extremely preferred

Extremely preferred

NUMERICAL VALUE

1

2

3

4

5

6

7

8

9

Getting a ranking of priorities from a pairwise matrix :

EIGENVECTOR

[ Dr. Thomas L. Saaty, currently with the university of pittsburgh,

demonstrated mathematically that the eigenvector solution was

the best ]

Reference : the analytic hierarchy process, 1990, Thomas L.

Saaty

Steps to obtain the eigenvector:

to obtain this ranking is to raise the pairwise matrix to

powers that are successively squared each time.

the row sums are then calculated and normalized.

The sum of priority criteria vector is one

The largest value in the priority weight is the most

important criterion

when the difference between these sums in two

consecutive calculations is smaller than a prescribed

value - calculation stop

Criteria Slope Soil lithologyLinement

densityDrainage density

Slope 1 3 2 1/6 1/5

Soil 1/3 1 1/5 1/9 1/7

lithology ½ 5 1 1/3 5

Linement density 6 9 3 1 3

Drainage density 5 7 1/5 1/3 1

1 3 2 0.1667 0.2

0.333 1 0.2 0.111 1/7

0.2 5 1 0.333 5

6 9 3 1 3

5 7 0.2 0.333 1

remove the names andconvert into the

fractions to decimals

1 3 2 1/6 1/5

1/3 1 1/5 1/9 1/7

½ 5 1 1/3 5

6 9 3 1 3

5 7 1/5 1/3 1

1. squaring the matrix1 3 2 1/6 1/5

1/3 1 1/5 1/9 1/7

½ 5 1 1/3 5

6 9 3 1 3

5 7 1/5 1/3 1

resultsin this

5 18.9 5.166 1.4 73285

2.1476 5 1.4476 0.39 1.2857

19.6666 35.5 5 2.3055 7.8142

31.5 72 208 5 17.4857

14.5 33.667 13.0667 2.3889 5

compute our first eigenvector (to four decimal places)first, sum the rows

5 18.9 5.166 1.4 73285

2.1476 5 1.4476 0.39 1.2857

19.6666 35.5 5 2.3055 7.8142

31.5 72 208 5 17.4857

14.5 33.667 13.0667 2.3889 5

= 37.7952 0.1132

= 10.2730 0.0307

= 70.2865 0.2105

= 146.7857 0.4397

= 68.6222 0.2056

333.7627 1.0000second, sum the row totals

finally, we normalize by dividing the row sum by the row totals(i.e. 37.79524 divided by 333.7627 equals 0.11324 )

the result is our eigenvector

0.1132

0.0307

0.2105

0.4397

0.2056

5 18.9 5.166 1.4 73285

2.1476 5 1.4476 0.39 1.2857

19.6666

35.5 5 2.3055 7.8142

31.5 72 208 5 17.4857

14.5 33.667 13.0667

2.3889 5

this process must be iterated until the eigenvector solution does not change from the previous iteration

5 18.9 5.166 1.4 73285

2.1476 5 1.4476 0.39 1.2857

19.6666

35.5 5 2.3055 7.8142

31.5 72 208 5 17.4857

14.5 33.667 13.0667

2.3889 5

square this matrix

317.5654

719.9452

203.9067

50.8292 162.4395

80.9388 188.4948

50.5271 13.3363 46.7637

458.8393

1155.781

328.0658

83.1746 308.2286

1132.238

2642.436

703.4586

187.0556

318.4281

549.531 1246.583

304.0087

87.5143 318.4281

result

compute the eigenvector (to four decimal places)

317.5654

719.9452

203.9067

50.8292 162.4395

80.9388 188.4948

50.5271 13.3363 46.7637

458.8393

1155.781

328.0658

83.1746 308.2286

1132.238

2642.436

703.4586

187.0556

318.4281

549.531 1246.583

304.0087

87.5143 318.4281

= 1454.6860 0.1247

= 380.0601 0.0325

= 2334.0872 0.2002

= 4983.6160 0.4274

= 2506.0654 0.2149

11658.5154

total

compute the difference of the previous computed eigenvector to this one

0.1132 -

0.0307 -

0.2105 -

0.4397 -

0.2056 -

0.1247

0.0325

0.2002

0.4274

0.2149

= -0.0115

= - 0.0018

= 0.0103

= - 0117

= - 0.0093

to four decimal places there’s not much difference

Criteria Slope Soil lithologyLinement density

Drainage density

Slope 1 3 2 1/6 1/5

Soil 1/3 1 1/5 1/9 1/7

lithology ½ 5 1 1/3 5

Linement density 6 9 3 1 3

Drainage density 5 7 1/5 1/3 1

o computed eigenvector gives us the relative ranking of our criteria

Slope 0.1132

Soil 0.0307

lithology 0.2105

Linement density0.4397

Drainage density0.2056

the most important criterion

the least important criterion

Select landslide susceptabile zones1.0000

Slope0.1132

15-2020-2525-3030-35>35

Soil0.0307

Ramman SeriesChunabhati Series

Chhota Mangwa SeriesChhota Mangwa Series

Lithology0.2105

Damuda FormationGorubathan Formation

Lingtse Granite GneissRangit Pebble Slate

Lineament Density0.4397

<1.771.77-2.132.13-2.482.48-2.84>2.84

Drainage Density0.2056

<33-44-55-6>6

Objective

Criteria

Alternatives

Sub- Criteria

Zone 1 Zone 2 Zone 3

In terms of sub-criteria, pairwise comparisons determines the preference of each alternative over another

15-20 20-25

25-30

30-35

>35

15-20 1 1/3 1/7 1/9 1/7

20-25 3 1 1/3 1/7 1/6

25-30 7 3 1 1/4 1/6

30-35 9 7 4 1 1/5

>35 7 6 6 5 1

SLOPE RANGE

Soil Series Ramman Chunabhat

i Chhota Mangwa Barbung

Ramman Series 1 1/3 1/6 1/8

Chunabhati Series 3 1 1/4 1/6

Chhota Mangwa Series 6 4 1 1/3

Barbung Series 8 6 3 1

SOIL

DRAINAGE DENSITY(km/sq

km) <3 3-4 4-5 5-6 >6

<3 1 1/3 1/5 1/9 1/7

3-4 3 1 1/5 1/7 1/5

4-5 5 5 1 1/3 1/5

5-6 9 7 3 1 1/3

>6 7 5 5 3 1

DRAINAGE DENSITY

LINEAMENT DENSITY

(km/sq km) <1.771.77-2.13

2.13-2.48 2.48-2.84 >2.84

<1.77 1 1/2 1/3 1/5 1/71.77-2.13 2 1 1/5 1/7 1/92.13-2.48 3 5 1 1/3 1/52.48-2.84 5 7 3 1 1/3

>2.84 7 9 5 3 1

LINEAMENT DENSITY

lithology Damuda Gorubathan Lingtse RangitDamuda Formation 1 3 9 3

Gorubathan Formation 1/3 1 7 ½Lingtse Granite Gneiss 1/9 1/7 1 1/7

Rangit Pebble Slate 1/3 2 7 1

LITHOLOGY

Select landslide susceptabile zones1.0000

Slope0.1132

15-2020-2525-3030-35>35

Soil0.0307

Ramman SeriesChunabhati Series

Chhota Mangwa SeriesChhota Mangwa Series

Lithology0.2105

Damuda FormationGorubathan Formation

Lingtse Granite GneissRangit Pebble Slate

Lineament Density0.4397

<1.771.77-2.132.13-2.482.48-2.84>2.84

Drainage Density0.2056

<33-44-55-6>6

Objective

Criteria

Sub- Criteria

0.03350.06540.17780.30020.4231

0.070

0.125

0.288

0.515

0.523

0.181

0.038

0.256

0.045

0.051

0.129

0.264

0.511

0.033

0.058

0.146

0.302

0.460

Step 3 – Checking for consistency

Consistency Index (CI) : The degree of logical consistency among pair-wise comparisons. CI =

Suppose, Ax = max x ; where x is the priority vector

1 3 2 1/6 1/5

1/3 1 1/5 1/9 1/7

½ 5 1 1/3 5

6 9 3 1 3

5 7 1/5 1/3 1

0.7207

0.0549

2.4277

9.6734

2.7824

= = λmax

0.0335

0.0654

0.1778

0.3002

0.4231

x

λmax=average{0.1745/0.0335, 0.3386/0.0654, 0.9201/0.1778, 1.6986/0.3002, 2.6062/0.4231 }=5.2426

Consistency index is found by CI=(λmax-n)/(n-1)=(5.2426-5)/(5-1)= 0.0606

0.1132

0.0307

0.2105

0.4397

0.2056

Consistency Ratio (CR) : indicates the amount of allowed inconsistency in the pair-wise comparison . CR =

CI = Consistency IndexRI= Random Index

Randon Index table :

• upper row is the order of the random matrix• lower is the corresponding index of consistency for random judgements.

An inconsistency of 10% or less implies that the adjustment is small compared to the actual values of the eigenvector entries. A CR as high as, say, 90% would mean that the pairwise judgements are just about random and are completely untrustworthy

CR = CI / 1.12 = 0.0606 / 1.12 = 0.0541 (value of Consistency Index is less than 0.1, so the evaluations are consistent)

The landslide susceptibility index (LSI) value for each considered pixel was computed by summation of each factor ’s

weight multiplied by class weight (or rating) of each referred factor (for that pixel) written as follows :

LSI =

Susceptibility classes

Susceptibility index

values% of

Area

% of landslide

points

Frequency ratio

(FR)

Very low susceptibility (VLS) 0.06-0.12 38.47 4.37 0.11

Low susceptibility (LS) 0.12-0.18 28.48 11.26 0.4

Moderate susceptibility (MS) 0.18-0.24 19.88 16.55 0.83

High susceptibility (HS) 0.24-0.30 7.93 27.74 3.5

Very high susceptibility (VHS) 0.30-0.36 5.24 40.07 7.65

Landslide Susceptibility Zonation :

Allocation of the reference landslide area within the defined landslide susceptibility classes and the associated frequency ratio (FR) of each class

VHS HS MS LS VLS0.00

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45.00

% of Area% of landslide points

% o

f la

ndslide p

oin

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27°3'0"N 27°3'0"N

27°1'30"N 27°1'30"N

27°0'0"N 27°0'0"N

26°58'30"N 26°58'30"N

26°57'0"N 26°57'0"N

26°55'30"N 26°55'30"N

26°54'0"N 26°54'0"N

26°52'30"N 26°52'30"N

LANDSLIDE SUSCEPTIBILITY ZONATIONUSING

ANALYTICAL HIERARCHY PROCESS

Landslide distribution map of Kalimpong-I Block,Darjeeling District

µ

0 3 6 91.5Kilometers

INDEXLandslide Susceptibility

zonation

Very Low

Low

Moderate

High

Very High

KALIMPONG -I C.D. BLOCK, DARJEELING DISTRICT, WEST BENGAL

Thank you