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1

Chapter I

Introduction

1.1 Background

After tsunami hazard predominantly damaged Nanggaroe Aceh Darussalam

(NAD) Province in December 2004 and Earthquake in The Special Region of

Yogyakarta in 2006, those cases increase the awareness impact of natural hazard

for many stakeholders. Natural hazard have wide terms, but common case have

been caused by geological hazards. Geological hazards are dangerous situation

caused by geological processes (Noor, 2006). The kinds of geological hazards are

landslide, mountain eruption, earthquake, flooding, erosion, salination, and

drought (Noor, 2006).

Geological hazard caught avoided by hazard mitigation. The concept of hazard

mitigation is decreasing risk from geological hazard with impacts on property

damage and death toll (Noor, 2006). Spatial planning must consider about hazard

mitigation, because it consists of land use arrangement; such as allocation of

settlement area, industrial area, conservation area, etc. Analyzing land allocation

in spatial planning based on geological hazard has objective to prevent from

natural hazard damaging.

Spatial Planning Act No. 26 /2007 describes about how to hazard tackling with

determine hazard vulnerability area. In article 42 verse 1: implementation and of

spatial planning have been done to decrease hazard risk, which consist of applying

spatial planning regulation, safety standard, and apply sanction for scofflaw.

To determine hazard vulnerability area in spatial planning is developed using

many factors. Most of the factors are related to geological information map.

2

stability of area from impact of geological hazard. Types of geological

information are: structure and physical properties of rock, slope, earthquake

intensity, and existing fault line. All those factors have close relation with

stability of area, or describe underground condition. On the surface, existing land

use, characteristic demographic of population and economic are the most factors

affected in vulnerability from earthquake hazard.

Combination between susceptibility from (geological) hazard cause by earthquake

and vulnerability is defined as a risk (Figure 1.1). Risk means the expected

number of lives lost, persons injured, damage to property and disruption of

economic activity due to a particular natural phenomenon, and consequently the

product of specific risk and elements at risk (UNDRO, 1979) (Fournier, 1986) in

Kjatsu, (2005). Risk assessments in urban area have benefit to help and

clarify decision making for disaster management and the development of

mitigation strategies (Khatsu, . (2005).

Figure 1.1 Risk concept; Function Hazard and Vulnerability

Two ways analysis have been done; first is hazard analysis, which measured from

geological information (rock structure, slope, earthquake intensity, geological

structure, and existing fault line), and second is vulnerability analysis which

measured and compared all criteria’s (physical, demographic, and social), and

produced rank of priority distribution vulnerability area.

It is difficult to make decision that involves many factors or information, and to

solve the problem for decision making concept. Decision making is a process of

or goals (Turban, 1995).

). SDSS can be defined as an interactive, compu

support a user or group of users in achieving

ision making while solving a semi structured spatial

ki, 1999).

of Research Problem

dly hazard in 20th millennium (UN, 2010), because

it come and what level of strength. BNPB (2007)

that earthquake and secondary impact of earthquake;

120.000 death victims, and more than 600.000 hous

Those facts describe at least 90% total from othe

landslide, and etc.

umber of death victim caused by natural hazard (BNPB, 2

4

Figure 1.3 Number of housing damage caused by natural hazard (BNPB, 2007).

Level of urbanization in Indonesia is still increasing; at least 119 inhabitants per

square kilometer is the population density in Indonesia, and particularly in Jawa

and Bali islands were 996 inhabitants per square kilometer (BNPB, 2007). The

Population growth followed by the increase of built up areas, can increase

vulnerability and risk level from natural hazard. As tool for development control,

spatial/urban planning has strategic position in mitigation concept to avoid natural

hazard.

One of the mitigation concepts to avoid high loss caused by earthquake is to

develop spatial planning based on natural hazard potential and vulnerability

factors. In facts, not all cities in Indonesia prepare spatial planning based on

natural hazard potential and vulnerability factors. Existing locations in Indonesia

are surrounded by tectonic and volcanic activities, which should be the priority

review for urban planning.

The latest spatial planning guide in Bantul, which was revised in year 1999, has

some refraction especially in determining for hazardous area. For example, in sub

district Sewon, Kasihan, and Banguntapan were set to urban settlements area. In

facts, in those area loss rates had reached high enough when earthquake occured

5

structure, the level of damage reached more than 21000 houses damaged, and

15000 were totally destroyed. Those situations require arrangement based on

earthquake hazard and vulnerability which aims to reduce lost in the future.

1.3 Aim of Research

This study has a purpose to define and describe about risk, which function of

hazard and vulnerability area related to support urban planning process. Until

now, there is not any clear term of risk, hazard, and vulnerability area noted in

determine in spatial context. In this case, to determine risk has two combinations

between hazard and vulnerability area.

1.4 Objective of Research

Objectives of this study are:

1. To determine hazard area based on geological information by using GIS

spatial analysis.

2. To determine vulnerability area based on physical, demographic and social

factors using multiCcriteria analysis.

3. To determine level of risk area by combining hazard map and vulnerability

map.

1.5 Research Questions

1. How to determine hazard, vulnerability, and risk area map based on

geological information by using GIS spatial analysis?

2. Which location is potentially susceptible from earthquake hazard?

3. Which location is vulnerable when earthquake occurs? Vulnerability was

observed from physical, demographic, and social factors.

4. How big is the risk probability degree in all area based on earthquake

hazard, and related to the spatial planning guide.

1.6 General Research Methodology

It generally has been shown in schematic research methodology flow chart in the

6

of methodology deals with review hazard and vulnerability literature particularly

determined the criteria. The criteria should represent in spatial format data which

will be used for spatial modeling.

The second part of methodology deals with multiCcriteria analysis, which use

pairwise comparison method (PCM) to assign criterion weighted. The third part of

methodology deals with modeling with spatial analysis using GIS capability,

which criteria weighted resulted from multiCcriteria analysis is used to simulate in

spatial analysis with weighted overlay method.

Figure 1.4 Schematic diagram of research methodology

1.7 Scope of Research

This research is focusing how to determine hazard, vulnerability, and risk area

with simulation in GIS. GIS spatial analysis is used to simulate for hazard map

model which represent geological information combination. The vulnerability

map used was physical, demographic, and social aspects.

A. Hazard Analysis

Geological information is described in attribute and map (spatial data), and it was

7

of Mineral and Energy Resources. The geological information is classified into 5

(five) information:

1. Rock Structure and Physical Characteristic.

2. Geomorphology (Slope and Relief).

3. Existing fault line.

4. Earthquake Intensity.

B. Vulnerability Analysis

Vulnerability analysis consist of 3 (three) factors; physical, demographic

(demographic of population), and social.

1. Physical Factor

Representative of physical aspects in urban risk analysis can be divided in

three categories: density of built up area, number of structure, and type of

structure.

2. Demographic Factor

The main factor of demographic vulnerability is described in characteristic

demographic population that represents some data; 1) Total population, and

2) Density distribution, and 3) Population growth rates. Those criteria will

transform into spatial data, which is subCdistrict administrative as a boundary

unit.

3. Social Factor

Representative of physical aspects in urban risk analysis could be

differentiated in three categories; 1) low income distribution, 2) Gender, and

3) Age structure (elderly and children).

C. Risk Analysis

Risk is the function of hazard and vulnerability, it means that the combination

between hazard map and vulnerability map will produce risk map. Risk is

multiplication between hazard and vulnerability function, which can be expressed

in the following mathematical form:

8

1.8 Location of Research

The research location was in the Bantul Regency, Yogyakarta Province. The

coordinate geographic position was in latitude 07°44'04" S C 08°00'27" S, and

longitude between 110°12'34" E C 110°31'08 E. The climate was influenced by sea

in south (Indian Ocean), and the majority of land used for settlement and

agriculture. Topographic conditions were steep in the west side, and flat in rest

area such as coastal area.

Figure 1.5 Location of Research

The capital city of Bantul Regency located in District Bantul. Bantul regency

consists of 17 districts. Bantul Regency has boundary with Yogyakarta and

Sleman City in north, Gunung Kidul in east, Kulon Progo in west, and Indian

Ocean in south. Some area were parts of expansion from Capital of Yogyakarta,

where located in north Bantul (Subdistrict Kasihan, Sewon, and Banguntapan).

9

1.9 Research Output

The main output this study is;

1) Hazard area map based on geological information (ground stability), which is

susceptible from earthquake.

2) Vulnerability area map based on multiCcriteria analysis.

3) Risk map, which is the combination between hazard map and vulnerability

map. Risk map is used to assess the spatial planning map that already exists.

1.10 Limitation of Study

This research is focus on hazard, vulnerability, and risk area from impact of

earthquake hazard. Some limitation based on early investigated explain the

limitation of this study are;

1. In the world, vulnerability concept is multiCinterpretation; it wasn’t consensus

to exactly define the meaning of vulnerability. That fact cause vulnerability

analysis cannot use single solution problem, or as problems which possess

multipleCsolutions and contain uncertainty about the concepts, rules, and

principles involved to reach these solutions (Rashed and Weeks, 2003)

(Cutter, L.S., Boruff, J. B., and Shirley, L. W., 2003). So, in this research

tried to generate the criteria related with hazard (earthquake) vulnerability,

especially to determine the criteria. Widely examination of relevant literature

was used to select the criteria.

2. Some of spatial data are not in the same basic scale or source, and it can

decrease spatial accuracy. For example geological map has a scale of

1:100000 while administrative map has a scale of 1:25000.

3. To transform nonCspatial data (in example; density of population) to spatial

information used sub district administrative boundary as spatial analysis unit.

The application theory to mapping statistical data was explained by Menno,

Kraak J., and Ormeling F. (2009), which defined as choropleth map.

Choropleth map a thematic map in which areas are shaded or patterned in

proportion to the measurement of the statistical variable being displayed on

10

Chapter II

Hazard Analysis: Ground Stability Analysis in

Urban Area

2.1 Introduction

Earthquakes are considered as natural hazards, which become the main interest of

environment experts. Impacts of earthquakes are producing environment physical

damage until cause of death. Refers to BNPB (2007), the impact of earthquake

caused at least 120.000 death victims among 2002 to 2006. That impact also

brought economic loss and regional development incline. Experiences in Aceh

tsunami (2004), Yogyakarta earthquake (2006), and the newest occurrence in

Padang (2009) made experts to reach solution to minimize the impacts of

earthquake.

The effort to avoid impact of earthquake hazard uses mitigation approach, which

can be depend as an activity to avoid impact of natural hazard or manmade hazard

for public and nation (Sutikno, (2006)). Mitigation is divided into two

important parts, structural and nonCstructural. Structural mitigation is done by

structural approach such as land suitability, building resistance, type of material

structure, and etc. Non structural mitigation is done by “soft structure” such as

dissemination, education, training, institution development, etc. Both of concepts

should parallel in those implementations.

Spatial planning is a part of nonCstructural mitigation, which considers all of

hazard and the impacts. Based on hazard and the impacts, land use planning and

regulation should consider hazard potential and susceptibility. In case of

earthquake hazard, geological information and phenomena are important factors

11

Spatial planning process must be supported by geological information to identify

where location susceptible from earthquake hazard. By using geographic

information system (GIS) can manage and utilization of (earthquake) hazard

information (DGME, 2004). Spatial analysis capability in GIS is possible to

produce hazard map, which is become important part in land use planning

process.

2.2 Objective of Research

The objective of earthquake hazard in this research to determine hazard area based

on geological information by using GIS spatial analysis. Geological information

consist of 4 (four) main factors which influence to ground stability; rock structure,

slope, earthquake intensity, and fault way.

2.3 Literature Review

2.3.1 Definition of Hazard

Hazard is potentially damaging physical event, phenomenon, or human activity

that may cause the loss of life or injury, property damage, social and economic

disruption, or environmental degradation (ISDR, 2007). Following the ISDR term,

hazard can include latent conditions that may represent future threats and have

different origins: natural (geological, hydroCmeteorological and biological) or

induced by human processes (environmental degradation and technological

hazards). Hazard can be single, sequential or combined in their origin and effects.

Each hazard is characterized by its location, intensity, frequency and probability

(ISDR, 2007).

2.3.2 Geological Hazard

One of the types of hazard is cause by natural factor. As mentioned by

International Strategy Disaster Reduction (ISDR), natural hazard is classify into 3

(three) types; by geological, hydro meteorological, and technological hazards.

12

kinds of geological hazards are landslide, mountain eruption, earthquake,

flooding, erosion, salination, and drought (Noor, 2006).

The types of geological hazard which have often been occurring are cause by four

factors; soil movement, mountain eruption, debris avalanches, and earthquake

(Noor, 2006). That kind of geological hazard is the main hazard which cause more

property damage and death toll. In this research study, the focus is in geological

hazard caused by earthquake.

2.3.3 Earthquake

Earthquake is a shaking and trembling of the crust of the earth, caused by collision

between ground plates, active fault from volcanic activity, and detritus of rock

(BNPB, 2007). An earthquake is a sudden, rapid shaking of the earth caused by

the breaking and shifting of rock beneath the earth's surface (Earthquake, 2007).

Earthquake is an energy released phenomenon that cause dislocation in the inside

part of earth with instant change.

Refer to USGS (2008), term of earthquake is the vibration, sometimes violent, of

the earth's surface that follows a release of energy in the earth's crust. This energy

can be generated by a sudden dislocation of segments of the crust, by a volcanic

eruption, or event by manmade explosions.

The main causes of earthquakes (BNPB, 2007) can be classified as follows:

1. Tectonic activity caused by ground plate displacement.

2. Fault activity in earth surface.

3. Local geomorphologic displacement, for example soil detritus.

4. Volcanic activity.

13

Figure 2.1 Illustration earthquake caused by tectonic activity (Bakornas PB,

2007).

Earthquakes can occur at any time without warning. An earthquake sequence

happen in the place where earthquakes occurred in the past and it will happen

again (Earthquake, 2007).

2.3.4 Impacts of Earthquake

The impact of earthquake depends on many factors related to ground seismicity

and activities on the surface. The factors depend on each other’s and it can

strengthen the earthquake. The most earthquake effect is building damage caused

by ground shaking and trembling.

Refers to Bell (Bell, 1999), the most serious direct effect of earthquake in terms of

building and structures is ground shaking. Researchers prove ground condition is

a main factor shaking effect and it cause damaging for building and structures.

Although building and structures standing on the firm bedrock, it can still be

affected, so the susceptible buildings should not be located near to a fault trace.

The most effects caused by earthquake classify into 4 (four) types (Upseis, 2008):

1. Ground Shaking

Buildings can be damaged by the shaking itself or by the ground beneath them

14

Figure 2.2 Friday earthquake in Anchorage, Alaska (Walker, 1982)

Figure 2.3 The ruins in Bantul, Yogyakarta Province, 2006.

2. Ground Displacement

The second main earthquake hazard is ground displacement (ground movement)

along a fault. If a structure (a building, road, etc.) is built across a fault, the ground

displacement during an earthquake could seriously damage or rip apart that

structure.

3. Flooding

The third main hazard is flooding. An earthquake can rupture (break) dams or

levees along a river. The water from the river or the reservoir would then flood the

area, damaging buildings and maybe sweeping away or drowning people.

4. Fire

The fourth main earthquake hazard is fire. These fires can be started by broken

gas lines and power lines, or tipped over wood or coal stoves. They can be a

serious problem, especially if the water lines that feed the fire hydrants are

broken, too.

2.3.5 Yogyakarta (and Bantul) Earthquake

Yogyakarta earthquake occurred on 27th May 2006, which destroyed all

settlements and public facilities surrounding Yogyakarta. The strike hit not only in

Yogyakarta city, but it happened also in Bantul and Klaten regencies. Those areas

15

The epicenter Yogyakarta earthquake located in the west side of Opak fault line,

which has geographic coordinate; 8.24º S and 110.43º E (USGS, 2006) in Haifani,

. (2008). Alongside that coordinate is the central of damaging, which was

through in Merapi alluvial materials formation. That formation are consists of

alluvial, tuff, breksi, agglomerate, and lava current (Haifani, 2008).

Figure 2.4 Epicentrum Yogyakarta Earthquakes (UNOSAT, 2006)

The numbers of victims in Yogyakarta earthquake were 4,680 people killed, and

19,897 injured (Table 2.1). The administrative area has a lot a number of death

tolls located in Bantul Regency with 4,141 people, that statistic is over than 90

percent all sum of dead people. Almost the dead victims were caused by struck

down of building materials.

Table 2.1 Victim Data in Yogyakarta Earthquake

No.

16

Yogyakarta earthquake also caused a lot of destruction of many houses in some

area. Bantul has the highest number of damaging houses compared to other areas,

at least 96,360 houses were totally damaged (totally loss), and 70,769 heavily

damaged (Table 2.2).

Table 2.2 Number of house damage in Yogyakarta Earthquake

No.

Source: Yogyakarta Earthquake Media Center (2006) in Haifani, . (2008).

2.4 Methodology

2.4.1 Method of Research

The method of research mapping earthquake hazard is shown in figure 2.5. First

part research method is to review and identify hazard potential factor. Those

factors were selected and examined by geological experts, which was explained in

manual of spatial planning for mountain eruption vulnerability area, and

earthquake vulnerability area. Rock structure, slope (and relief), earthquake

intensity, and geological structure are the most affected when earthquake occurs.

17

2.4.2 Review and Identify Earthquake Hazard Criteria

There are many criteria related to earthquake hazard that can determine the level

of damage. Most of the researchers believed the closeness to fault way were the

most important criteria in earthquake hazard (Bell, 1999, ITC, 2005, BNPB, 2007,

Erdik, 2007). Bell (1999) explained although a land had solid firm bed rock

wasn’t effect when in the land had or through fault way. Some experiences

describe which higher damage area located near or precise in fault way.

Fault Way

Fault way is the vulnerable place when interCplate movement and intraCplate

movement occur, which is divided into two categories; horizontal and vertical

movements (Gulati, 2005) (Figure 2.6). The movement plate in fault way is the

primary threat, which causes ground shaking effect. The bigger intensity in

ground shaking cause higher damage for building and infrastructure (Bell, 1999).

(a) Dip Slip Fault (b) Dip Slip Fault (c) Strike Slip Fault

Figure 2.6 Type of slip plate movement at fault (Kadarisman) (Gulati, 2005)

Earthquake Intensity

Second criterion which is important in earthquake hazard is earthquake intensity.

Earthquake intensity is the function of magnitude, distance from epicentrum,

vibration time, earthquake deep, soil condition, and structure condition (PIRBA).

The measurement of earthquake intensity states in mercalli modified intensity

(MMI). Earthquake intensity is closely related to another intensity criteria; gravity

force (α), and richter scale (Table 2.3). Levels in MMI scale can be described as

follows in state earthquakes (Table 2.4).

18

Table 2.3 Earthquake intensity, gravity force, and richter scale

MMI αααα Richter

Table 2.4 Descriptive Scale of Earthquake Intensity in MMI

MMI Descriptive scale of earthquake intensity

I Not felt

II Felt by persons at rest

III Hanging object swings; vibration like passing light trucks IV Vibration like passing of heavy trucks

V Felts outdoors; awake sleepers; unstable objects move VI Felts by all; glassware broken; books of shelves VII Hard to stand; noticed in cars; damages some masonry VIII Collapses some masonry; moves some frame housing

IX General panic; foundation damage; cracks in ground X Most structures destroyed; landslides; water thrown XI Rails greatly bent; underground pipes out of service XII Damage nearly total

Source: FEMA

Slope

Slope is a dangerous potential factor when earthquake occurs. Rock and soil

movement under influence gravity could trigger earthquake ground shaking

(USGS, 2001). In some slope condition, rock and soil movement become

dangerous when earthquake occurs. Landslide follows with soil and rock fall is

main the threat when earthquake occur in slope area. Degree of slope represents

threat when earthquake occurs; it is more extreme can decrease the level of hazard

19

Table 2.5 Slope classification

No Percent of Slope Information

1. 0 – 7 % Flat

2. 7 – 30% Moderate Steep

3. 20 – 140% Very Steep 4. > 140% Very very steep Source: Ministry of Public Work, Rep.of Indonesia (2007).

Rock Structure

Strength of rock from earthquake effect depends on physical characteristic;

cohesiveness and material configuration. Those factors influence to reduce

vibration and ground shaking from earthquake effect, and then secure structure

from damage. Rock structure and strength from earthquake effect are classified

into 4 classes (Rudi Suhendar, 1998) (Table 2.6).

Table 2.6 Rock type classification from earthquake resistance and Landslide probability

No Classification Rock Type

1. I Andesite, Granite, Diorite, Metamorf, Vulcanic Breccia, Aglomerate, Sediment Breccia, Conglomerate

2. II Sandstone, AndesiteCBasaltic Tuff, Silt Stone, Arkose, Greywacke, Limestone

3. III Silt Sand, Mudstone, Marl, FineCGranide Tuff, Shale 4. IV Clay, Mud, Organic Clay, Peat Moss

Source: Ministry of Public Work, Rep.of Indonesia (2007).

Rock classification is divided into 4 (four) classes, class I has the most solid

physical structure, and class IV have physical weak or it’s not resistance from

ground shaking and slip fault.

2.4.3 Data Preparation and Processing

Various spatial data were prepared and used to build hazard model. The spatial

data which was used to hazard modeling, based on geological and topographical

20

this research were acquired from previous geological and topographic research

report. The spatial precision and validation were done by each institution.

Table 2.7 Main data hazard research

No. Information Type of

Data

Scale Source Year of Published

1. Rock Structure Polygon 1:100,000 ESDM 1) 2007

2. Slope DEM 30 X 30 meters SRTM 2) 2007

3. Earthquake Intensity Polygon 1:100,000 ESDM 2007

4. Existing Fault Polygon 1:100,000 ESDM 2007

1) Ministry of Mineral Resources and Energy – Republic of Indonesia, Center for Volcanology & Geological Hazard Mitigation.

2) Shuttle Radar Topographic Mission (SRTM). 30 meter spatial resolution. http://www2.jpl.nasa.gov/srtm/dataprod.htm.

21

Figure 2.8 Map of DEM visualization by SRTM in study area

22

Figure 2.10 Map of Fault line in study area

2.4.4 Multi Criteria Analysis

MCDA or could be defined as MCDM (multi criteria decision making) techniques

have largely been aspatial (Malczewski, 1999), but they are different in GIS

context. Spatial MCDA which is applied in GIS requires both data on criterion

values and the geographical locations of alternatives (Malczewski, 1999).

According to Malczewski (1999), the main concept combination between MCDA

and GIS is to support the decision maker in achieving greater effectiveness and

efficiency. Some technique used to support MCDA in decision making by using

decision rules, to choose the best or the most preferred alternatives. There are

some decision rules to tackle MCDA/MCDM in this research.

Decision Rules; Weighted Linear Combination

The main method in weighted linear combination (WLC) assigns relative weight

23

compose geological spatial information which has score and weighted value based

on reference (Table 2.9). The combination between score and weighted value in

geological information determines the level of ground stability. Ministry of Public

Work Government of Indonesia (2007) has classified the level of stability into 3

(three) classes which are; not stable, less/moderate stable, and stable. Each class

has cumulative score based on the combination between attribute values in

geological information (Table 2.8). The equation of hazard analysis related with

ground stability shows below:

= ∑ (3)

Where;

Hazard zone based on ground stability, resulted by weighted overlay

in GIS

= Total weight rock structure

=Total weight slope

= Total weight earthquake intensity

= Total weight geological structure

Geological information has score and ability value. Weighted value has range

value 1 up to 5. Value 1 indicates the high importance level of geological

information, which means that geological information, is really necessary to know

24

Table 2.8 Weighting Matrix for Area Stability about Ground Stability from Earthquake

No. Geological Information Information Class

Criteria

Score*) Weight *)

Total Weight

1. Rock Structure ( ) a. Andesite, Granite, Diorite, Metamorf, Vulcanic Breccia,

Aglomerate, Sediment Breccia, Conglomerate 1

3

12

b. Sandstone, AndesiteCBasaltic Tuff, Silt Stone, Arkose,

Greywacke, Limestone 2 6

c. Silt Sand, Mudstone, M arl, FineCGranide Tuff, Shale 3 9

d. Clay, Mud, Organic Clay, Peat Moss 4 12 Source: Ministry of Public Work. 2007. Manual Spatial Planning For Mountain Eruption Vulnerability Area, and Earthquake Vulnerability Area.

2

25

Table 2.9 Classification of Weight Value

Weighted Classification

factor with weighted value 3, geological structure is less important than slope factor

in term of the most important information for hazard zone. The capability values

represent the stable conditions from geological hazard. Value equal 1 has means

highest level for the stability related with geological hazard, while on the contrary

with value equal 4, which represents the lowest level for stability (Table 2.10).

Table 2.10 Classification of Capability Value

Weighted Classification

combination. Score rating divided into 3 (three) categories, which are: high stability,

less stability, and low stability (Table 2.11). The total maximum score is 60, and for

minimum score is 15.

Table 2.11 Total Score Classes

Classification of Stability Rating Score

High Stability 15 C 30

Less (Medium) Stability 31 – 45

26

2.4.5 GISFMultiFcriteria Analysis

GIS has long experience in decision making and map design, and it can integrate with

MCDA system to support decision maker’s (Zhao and Garner, 2009). In this

research, GISCMCDA capabilities need to simulate different criteria to make hazard

map. The step in the preparation of spatial modeling after defining criteria; rock map,

slope map, earthquake intensity map, and fault map, it is to define the decision rules

and weighted value for each criterion (Figure 2.11), after that simulated in spatial

analysis by used raster calculator. The result spatial analysis was hazard map.

Figure 2.11 Schematic diagramGIS hazard modeling

2.5 Result and Discussion

This chapter presents the hazard map resulted from reCclassification rock and slope

from DEM (SRTM), earthquake intensity map, and fault path map. Spatial simulation

to produce hazard map use spatial analysis with multi criteria analysis method. The

process in combining all maps with spatial analysis using simply weighted method as

decision rules.

2.5.1 Rock Type and Structure

Almost all area in Bantul is classified in rock type and structure high stability from

earthquake (Table 2.6), but we should care in some spot area. District of Imogiri,

Kretek, Pajangan, Pleret, Sanden, and Srandakan have low stable area and they have

27

potential hazard when earthquake occurs (Table 2.12). Especially for district of Pleret

and Pajangan were categorized as urban areas.

Figure 2.12 Rock Capability Class

Table 2.12 Rock Stability Distribution

28

2.5.2 Slope

Topographical Bantul area has the characteristic as a coastal area in South Java;

inclined flat. Generating from DEM from SRTM with 30 × 30 meters shows almost

all area has 0C7% inclination (Figure 2.13). Steep area in Bantul located in east side

which was abutted with Gunung kidul Regency. Slope in east side of Bantul area

several dominated 7C30% or moderate steep, and only small area covered with slope

more than 30%. Another steep area was located in east side, especially in Pajangan

and Sedayu districts.

Figure 2.13 Map of slope classification in study area

2.5.3 Earthquake Intensity

Bantul is classified into 2 (two) earthquake intensity areas; north side has VCVI MMI

29

Bantul has dangerous potential from earthquake hazard, the effects from earthquake

can collaps, damage, and move the masonry’s frame.

Figure 2.14 Map of earthquake intensity in study area

2.5.4 Distance from the Opak’s Fault

Bantul area has Opak’s fault way longitudinal from south to north, which is a

potential danger in that area. Theoretically, around Opak’s fault is a weaker area than

others area without fault, because if the earthquake occurs, that place will fault in

plate; vertically or horizontally. Surface faulting categorized in primary seismic

hazard (FEMA) which will trigger hazard continuation like ground failure, landslide,

tsunami, and liquefaction.

The distance from fault determines the damage level caused by earthquake; only the

one that close to fault can hit primary the effect of an earthquake. Ministry of Public

Work (2007) has classified them into 4 (four) distance class from fault to describe

the existence of fault; less than 100 meter, between 100C1000 meter, and more than

30

1 to 4, where small value represents close distance with fault way (< 100 meter), and

contrary value (value=4) is restrain from fault way (> 1000 meter). Buffer analysis

area was used to implement the level of hazardous area in fault map.

Figure 2.15 Map of Distances from Fault

2.5.5 Hazard Analysis: Ground Stability Model

The result for simulating hazard map has the range between 20 C 49 score value

(Figure 2.16), which means for the minimum score reached in score 20, and for

maximum score reached in score 49. The visualization in hazard map show green

color representing high ground stability, and red color representing area with low

ground stability (Figure 2.16).

Based on stability rating in table 2.11, the first result hazard map reCclassified into 3

(three) scenario hazard zone; low stability, medium stability, and high stability

(Figure 2.17). Statistical hazard zone describes the majority level of ground stability

is medium. The second majority of ground stability is high stability, and then the rest

31

Figure 2.16 Distribution Ground Stability (Hazard) Map

32

Figure 2.18 Percentage level of ground stability in research area

Those facts describe half area should be considered carefully from earthquake hazard,

especially for low and medium stability area. The explanation is the combination of

earthquake intensity factor and fault impact area causes medium and high value. Most

of the research areas are potential hazardous area, and it is important to get more

attention. The probability loss impact in research area is medium to high, when the

vulnerability aspects haven’t got more attention. With that reality, it can be predicted

where the suitable location which is safe for living and activities.

The point of interest in this research is a very hazardous area which longitudinally

cracked by Opak’s fault. The impact of earthquake in fault line caused heavy damage

for structure in the surface. Closeness to fault line area cannot be avoided although

we have implemented high technology for structure, in the same manner as explained

by Bell (1999). Totally 13% areas are close or get high impact from fault line, and in

fact that area is majority classified into settlement area (Figure 2.20). Illustration in

Figure 2.19 shows the distribution of settlement areas in fault line located in Pleret,

Jetis, and Imogiri. In those areas there are lots of house buildings and built up

environment (road, drainage, etc.).

The proportion analysis for hazard level in every sub districts shows overall ranking

for hazard level. To identify the hazardous area, we started from areas which have

33

Banguntapan, Sedayu, Pandak, and Bambanglipuro are classified into potential

hazardous area (Figure 2.20).

Figure 2.19 Area where is in place fault line (area insert in double red line)

Especially in Imogiri, Pleret, Pundong, Kretek, Piyungan, they have low ground

stability more than 20 percent (Figure 2.20). The close factor from fault line, steep

area, and high earthquake intensity caused the high total score.

The second hazardous areas are located and distributed in almost whole Bantul area.

The most area which covered by medium ground stability are Bambanglipuro,

Pandak, Bantul, Srandakan, Sanden, Jetis, Pajangan, and Pundong. Those areas have

medium stability area percentage of over 50% and may even exist over 90%. The

medium ground stability area means that area has less ground stability, or it cannot be

defined as permanent stable area.

Comparing two areas such as Imogiri and Bantul, it determines that Bantul is not

really safe area. The difference of those two areas is Bantul is situated for away from

34

probability for both areas are same (figure 2.14). Bantul also has almost flat

topography while Imogiri has a very steep topography. Physical characteristic of

Bantul is also similar with Pandak and Bambanglipuro which are located in flat

topography but it has high earthquake intensity.

Bambanglipuro, Pandak, Bantul, and others area, which are located in MMI VIII,

zone historically have earthquake occurred in previously. Refers to table 2.4, the

damage effect in MMI scale VIII can cause totally damage for masonry.

Figure 2.20 Proportion Ground Stability in Every Districts

The high stability area in research study is represented by district such as Sewon,

Kasihan, Banguntapan, Sedayu, and Dlingo (Figure 2.20). Those areas have over

50% which classified into stable area. The affecting factors relates to stability areas

are the physical characteristic areas which haven’t fault line, flat topography, and the

compactness of rock structure. Several areas should get attention although classified

into stable area. For example, Dlingo, Piyungan, Pajangan, and Pleret also have low

35

stability area. The level of earthquake intensity for stable area is still classified in

dangerous situation; in level V to VI MMI can be felt by all and low to medium

potential damage for structure and built up environment.

2.5.6 Comparative Model of Hazard with the Facts on The ground

Although several locations such as Sewon, Kasihan, and Banguntapan are classified

into high stability, they are not totally free from earthquake impact. The previous

earthquake research and evidence shown in Bantul and whole Jogjakarta Province are

susceptible from earthquake hazard. That fact can be described in preCassessment

damage area developed by United Nations Institute for Training and Research

(UNITAR) in 2006, which the damage impact of earthquake was distributed in

random (Figure 2.21).

36

The figure 2.21 shows the location of damage in the event of an earthquake in 2006.

Survey conducted at some point the damage location and damage pattern looks great

in the location near the fault in particular. District of Jetis, which located near fault

has experienced of most damage area. Level of damaged started from limited level

into extensive level. Another district which has damaged area was Pleret, Piyungan,

Pundong, Imogiri, Bantul, Pundong, Sewon, and Bambanglipuro. District of Pleret,

Sewon, and Imogiri has similar level of damaged area, which consist for all level of

damaged.

The location of damaged area was majority classified into medium and low stability

area. District of Jetis, Pleret, Imogiri, Piyungan, Pundong and Banguntapan has low

stability area which influenced from fault line location. The conditions exacerbated

by the number of activities centered in the area, for example District of Jetis, Pleret,

and Banguntapan has many economic activities and settlement area. Those districts

have attached Opak’s fault lines which right in the location of economic activity and

population settlements.

Ground checking activity used GPS shown that the location of damage is similar to

the observation by UNITAR in 2006 (Figure 2.22). Two kind’s data was used, first

developed by EERI (2006), and field survey activities part of this research in June

2009. Earthquake Engineering Research Institute (EERI) survey activity, which

coded naming L1 up to L6 shown damaged distribution in several area. The picture

on that point described about damaged effect in houses (L4, L3, and L6) and caused

landslide (L2). District of Jetis, Pleret, and Bambanglipuro included in the area were

severely damaged by the earthquake.

Activity field survey in June 2009 showed the former location of damage in some

places, which coded naming M1 up to M33 (Figure 2.22). Implementation of a survey

conducted with the help of local community guide in several districts. The former

37

Imogiri, Pleret, Piyungan, and Banguntapan. The survey results in 2006 did not much

different results of 2009 survey, which location affected by earthquake.

Yogyakarta media center in 2006 had recorded victims and structure damaged in

Bantul and Yogyakarta area. Some districts have high number of loss and located in

medium and low stability area (Figure 2.23), for example; District of Jetis, Pleret,

Imogiri, Pundong, Bantul, and Bambanglipuro. This fact proves that the relationship

between the level of ground stability and the large number of casualties. This was

caused in these areas are close to the location of faults or fault, besides that there are

many areas of housing and services.

38

Another fact which explains the relationship between the level of ground stability and

the amount of damage structure is a map of the distribution of building damage

(Figure 2.24). The attribute data was developed by Yogyakarta Media Center in 2006,

which recorded all damaged structure after earthquake occurs. The District of Bantul,

Jetis, Bambanglipuro, Pandak, Imogiri, Pleret, and Dlingo has the high number of

building damage. The area is largely into the category of low and medium stability

especially be passed by fault line.

39

Figure 2.24 Graphic map of the distribution of building damage during the Yogya earthquake 2006

2.6 Conclusion and Recommendation

2.6.1 Conclusion

The conclusion are described and structured in line with objective of this research.

• _{Based on the map analysis, the high stability of the land due to absence of fault}

factors in addition to steep slopes and rock structures that support. Areas

categorized as having a high degree of stability such as District of Sewon and

Kasihan.

• _{Fault way is a major factor in increasing the value of disaster of a region, this is}

evidenced by the number of victims killed or injured and damage to buildings.

40

exemplified in the district of Pundong, Imogiri, Pleret, Piyungan, and

Banguntapan.

• _{The second cause of a decreased level of ground stability is influenced by factors}

of slope, where the steep increase disaster factor. Slope factor as stated in earlier

studies may lead to further disasters in the form of landslides or rock avalanches.

Imogiri are examples of areas with steep slopes that have a low degree of ground

stability or in general in the east of Bantul Regency.

• The prevalence of deaths, injuries, and destruction of buildings at all levels of

ground stability possible existence of high vulnerability factor, especially in areas

categorized as having high stability factor, for example in District of Sewon and

Kasihan. Assessment of the level of disaster related to the fact the number of

casualties and damage requires understanding the concept of vulnerability.

• _{The resulting map is still too general as this disaster database because there is}

still no availability of data in detail scale. Possible differences in accuracy also

led to a general outcome.

• Determination of criteria for disaster needs further study include the use of

scoring and weighting that may only be applied in the study area.

• _{Involving local communities in the field survey and supported the GPS device is}

helpful in assessing the accuracy of maps of disaster.

2.6.2 Recommendation

Some recommendations for further investigation are related to hazard analysis:

1. It is necessary to scale geological map in more detail to improve the accuracy of

disaster prone areas.

2. Necessary to identify early on the impact of further disasters like landslides due

41

CHAPTER III

Vulnerability Analysis in Urban Area Related

Earthquake Hazard

3.1 Introduction

Increasing growth population followed by physical development in built up area will

increase susceptibility and probability earthquake impact in urban area. The

centralization activities in urban area can trigger urbanization which shows in

migration phenomena. Rapid urbanization in the world cause 50 percent population

will dwelling in the cities, and expected to be absorbed by the urban areas of less

developed regions (UNEP, 2007).

The importance to identify the vulnerability factor in urban area will protect people,

before the hazard occurrence, and prepare precaution for them (Haki, 2004).

The impact history of earthquake in urban caused the damage of the life system and

espeacially caused many casualities. The experiences about impact of earthquake in

urban area are the occurences in NAD (2004), BantulCSpecial Region of Yogya

(2006), Tasikmalaya (2009), and Padang (2009). The damage of life system is related

to vulnerability factors such as physical, socioCeconomic, demographic, and etc.

The analysis processes of vulnerability were classified in several factors such as

physical, demographic, and social. Physical factors in terms of disaster were

associated with everything built by humans. Demographic factors associated with

resident population of an area where increasing population and the intensity in a

region highly affected, while social factors were closely related to the ability of the

community in case of disaster. Vulnerability factors is vast and varied for a given

region, the selection of vulnerability factors depend on the characteristics of the study

42

GIS has the capacity to perform spatial simulation by combining multiple layers of

spatial information. By leveraging the advantages of GIS, it is possible that

vulnerability is made to be maps that combine the spatial distribution of physical,

demographic, and social factors.

3.2 Objective of Research

The objective of research is to determine vulnerability area based on physical,

demographic and social factors using multiCcriteria analysis, and simulation in GIS.

3.3 Literature Review

Vulnerability is characteristics and circumstances of a community, system or asset

that make it susceptible to the damaging effects of a hazard (ISDR, 2009). It is

important to understand about level of vulnerability which is vulnerability influenced

by strength disaster factor, because disaster will occur in the vulnerable situation

(BNPB, 2007). Level of vulnerability can be considered into 3 (three) types:

1. Physical Vulnerability; relating to vulnerability for regional infrastructure like

density of building, percentage of built up area, percentage of building,

emergency construction, road network, communication network, and etc.

2. Social Vulnerability describing about level of social fragility to facing hazard.

Several indicators for social vulnerability are density of population, growth rate

population, and gender (female) percentage.

3. Economic Vulnerability describing about level of economic fragility to facing

hazard. Some indicators for economic vulnerability are poor household and

worker.

Comprehension about vulnerability is very various meaning depend on scientific

groups (Taubenbock, 2008), and the discussion is still continue and did not reach

precisely (Birdman, 2006a) in Taubenbock, . (2008). Refer to Taubenbock

43

wide ranging criteria such as demographic, political, and ecological aspect. The

specific vulnerability criteria explained by CASITA (2004) which cultural of the

people become a part of vulnerability.

3.4 Vulnerability Analysis

3.4.1 Method of Research

The method of research vulnerability mapping is shown in figure 3.1. The first part of

method is review and identify vulnerability criteria related earthquake hazard. The

review was based on literature and experiences from scientific groups, and the

selected vulnerability criteria used to analysis process in this research. The second

part of method was assigned weight value for every criterion. The pairwise

comparison method (PCM) was used to produce weight value. The final part of

method was to implement vulnerability model in GIS spatial analyst, which combines

logic arithmetic from spatial attribute and used weighted overlay method.

Figure 3.1 Schematic diagram of vulnerability mapping methodology

3.4.2 Determine Vulnerability Criteria

Vulnerability criteria is important in vulnerab ility process, which is not simple to

44

groups. The general rule to selecting criteria is comprehension about problem

identification for getting better response (Malczewski, 1999). Furthermore, according

to Malczewski (1999) criteria should close related between decision model and the

problem situation, also consider about number of criteria which suggest taking small

number criteria (oversimplification). Oversimplification about number of criteria

have goal to reach data availability and quality.

Refer to Malczewski (1999), the technique for selecting criteria may be developed

through an examination of the relevant literature, analytical study, and opinions. For

this research study, the examination of the relevant literature was used to select the

vulnerability criteria. The references has been using from government documents,

scientific journal, and scientific reports. Some scientific journal and government

report was result from field experiences such as CASITA (2004), Taubenbock (2008),

FEMA (2000), BNPB (2007), Cutter, Mitchell, and Scott (2004), Cutter, Boruff,

and Shirley (2003), ERA (2008), Rashed, and Weeks (2003), and DGMAE (2004),

which is all criteria/sub criteria for vulnerability was validate in the field by them.

After examination the relevant vulnerability literature, comprehension relation

between model and problem situation, and consider about data availability and

quality has been chosen some criteria for research study;

a. Physical Vulnerability

Physical vulnerability is related with vulnerability for regional infrastructure like

density of building, percentage of built up area, percentage of building, emergency

construction, road network, communication network, and etc. In this research,

physical vulnerability was developed from combination density of built up area,

45

b. Demographic Vulnerability

Demographic vulnerability is close related with probability for people affected by

earthquake hazard, when the earthquake occurs people may death, injury, infected by

disease, and suffer from stress (CASITA, 2004). The scale of demographic

vulnerability can observe based on urbanCrural area typology, which urban area have

the high vulnerability as compared to rural because most population concentrate in

urban area. Likewise in Bantul regency, some sub districts are including in urban

area. In this research, demographic vulnerability was developed from combination

total population, density population, and growth rate population.

c. Social Vulnerability

Social vulnerability is described about the people and their community ways of life.

The conceptual social vulnerability related with marginalized people due to the

impact of a disaster (CASITA, 2004). Refer from CASITA (2004), the concept of

marginalized is who the weaker sections or groups or part of society, there are based

on economical class, ethnicity, religion, gender, and age. In this research, low income

(represent poor people), female distribution, and age (elderly and children) are basic

for social vulnerability analysis.

The relevant reason for every criteria and sub criteria are explained based on some

literature Table 3.2).

3.4.3 Main Data for Research

The research study has several main spatial data (Table 3.1). The data based on vector

data with data attribute. Some data has been developing with use administrative unit

(sub district) for unit analysis, for instance density population distribution, and

46

Table 3.1 Main Data for Research

No. Information Type of

2.2 Number of Structures 2) Polygon 1:25,000 Gov. of Bantul 2008

2.3 Type of Structure 2) Polygon 1:25,000 Gov. of Bantul 2005

II. Demographic 2)

3.1 Total Population Polygon 1:25,000 Gov. of Bantul 2008

3.2 Population Density Distribution Polygon 1:25,000 Gov. of Bantul 2008

3.3 Population Growth Rates Polygon 1:25,000 Gov. of Bantul 2008

III. Social 2)

4.1 Low Income Population Distribution Polygon 1:25,000 Gov. of Bantul 2008

4.2 Gender (Female) Polygon 1:25,000 Gov. of Bantul 2008

4.3 Age (Elderly and Children) Polygon 1:25,000 Gov. of Bantul 2008

Note:

1) National Coordinating Agency Surveys and Mapping (Bakosurtanal) 2) BPS – Statistics of Bantul Regency.

3.4.3.1 Data Preparation

Process to preparing spatial data for vulnerability started from collecting relevant

statistical data with research study. The list of statistical data and the source explain

in Table 3.1. After collecting statistical data, the next step is adding to attribute GIS

data, and then the latest step is visualizing in map (Figure 3.3). The district

administrative boundary was used as spatial unit analysis. The kinds of vulnerability

map are show in Figure 3.4, Figure 3.5, Figure 3.6, Figure 3.7, Figure 3.8, Figure 3.9,

Figure 3.10, Figure 3.11, and Figure 3.12. Statistical data relating to the

vulnerabilities contained in appendix 5.

47

Table 3.2 Description of Vulnerability Criteria

No Criteria Sub Criteria Description Sources

1. Physical BuiltCup Density The high percentage of built up area from total area is indicate high vulnerable when earthquake occur. Significant structure losses might be expected from hazard event. Limited access to open space or safety area will increase number of injured and death victim.

Taubenbock (2008), Cutter, Boruff, and Shirley (2003)

Number of Structure

The number of structure in a certain area increasing probability for damage structure or totally collapse, which endanger for people when the material from the building struck down.

Taubenbock (2008), CASITA (2004), ERA (2008)

Type of Structure Structure without well construction design for earthquake can cause high damage for the structure.

Taubenbock (2008), CASITA (2004), ERA (2008)

2. Demographic Total Population The high total number population increasing injured may even death victim. Growth Population Area experiencing rapid growth lack available quality housing,

and the social service network.

Cutter, Boruff, and Shirley (2003), Taubenbock (2008) 3. Social Low Income

People Distribution

Low income people did not have many resources to preparing for earthquake hazard. For example; low income people cannot build house resistance from earthquake. emergency actions to protect themselves during earthquake.

48

Physical Criteria

Figure 3.3 Built Up Density Figure 3.4 Total Number of Structure

Figure 3.5 Type of Structure

Demographic Criteria

Figure 3.6 Total Population Figure 3.7 Density

Population

Figure 3.8 Growth Population

Social Criteria

Figure 3.9 Low Income Figure 3.10 Female Distribution

49

3.4.3.2 Data Processing

First step for data processing is to standardize the entire number of attributes in every

criterion so that all have value between 0 to 1. Standardized criterion numbers of

attribute have objective transform various criteria into comparable units (Malczewski,

1999). There are many methods to standardized criterion map, and one of the ways is

using linear scale transformation (Malczewski, 1999). Benefit criterion is used as

new values which the higher score (score=1) represent the better performance, and

contrary (score=0) is worst performance.

The Benefit Criterion Equation (Malczewski, 1999);

′ =

(4)

Where;

X’ij = standardized score for the th object (alternative) and the th attribute

Xij = the row score

Xi max= the maximum score for the th attribute

For example; in the Figure 3.4 is show existing condition for built up density in

research study. The highest number (score=1) indicate area have high built up

density, in that figure also show in color gradation, which is dark color represent have

high number, and bright color represent have low number. All vulnerability maps

were transformed into grid system to compatibility in spatial analysis process. The

grid size was used 30 x 30 meters, which adjusts the size of the SRTM spatial

resolution.

3.4.4 Multi Criteria Analysis

The vulnerability analysis in this research is using spatial multi criteria decision

analysis (Spatial MCDA) as decision rules. MCDA or could defined MCDM (multi

criteria decision making) techniques have largely been aspatial, but it different in GIS