EARTHQUAKE VULNERABILITY MAPPING OF ... saputra.pdfJl. A. Yani Kartasura Tromol Pos 1 Surakarta 57102 [email protected] , [email protected], [email protected] ABSTRACT

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Asia Geospatial Forum, 17-19 September 2012, Hanoi, Vietnam

EARTHQUAKE VULNERABILITY MAPPING OF RESIDENTIAL

BUILDINGS BASED ON THE GEOLOGICAL AND BUILDING

FOOTPRINT CHARACTERISTIC IN PLERET SUB-DISTRICT BANTUL

REGENCY, 2012

Aditya Saputra

(1), Priyono

(2), Yuli Priyana

(3), Agus Anggoro Sigit

(4)

(1), (2), (3), and (4) Lecturer staff in Geography Faculty of Muhammadiyah University of Surakarta

Jl. A. Yani Kartasura Tromol Pos 1 Surakarta 57102

[email protected] , [email protected], [email protected]

ABSTRACT

Pleret sub-district is one of the earthquake prone areas. It was proved, in the

earthquake event of May 27, 2006 in Yogyakarta, Pleret Sub-District was badly damaged.

This research was conducted to determine the earthquake vulnerability condition of

residential buildings using rapid visual screening of building for potential seismic hazard

procedure. The method used in this research was integration between remote sensing,

geographic information system and field observation. There are four lithologycal units in

Pleret Sub District based on the visual intepretation result using ASTER composite 3, 4,

PCA 56789. Those lithologycal units are Recent Merapi Volcano Deposite (Qmi),

Alluvium from denudational processes in Semilir and Nglanggran Formation (Qa),

Nglanggran Formation (Tmn) and Semilir Formation (Tmse). Those fourth lithologycal

units give the different appearance in ASTER composite 3, 4, PCA 56789. Semilir

Formation is dominated by alternately breccia pumice and breccia-tuff, give bright blue

with brownish red spotting appearance. Nglanggran Formation is dominated by volcanic

breccia and lava flow, give darker color i.e. brownish red with bright blue spotting

appearance. Recent Merapi Volcano deposites and Alluvium from denudational

processes in Semilir and Nglanggran Formation give bluish green and brownish red

appearance. Based on the intepretation of Quickbird imagery can be seen that the roof

type of residential buildings in Pleret Sub District are dominated by regular “kampung”

type i.e. 89.50%, while the buildings structure are dominated by reinforced masonry with

rigid diaphragm (RM2) i.e. 92.08%. The RM2 type have high score of rapid visual

screening of building for potential seismic hazard i.e. above the value 1.75. This score

shows that RM2 type has low level of earthquake vulnerability. From the results also

shown that all of the building structure types except wood structure (W1), if located in

moderate to high level of hazard indicated by unconsolidated surface material like

aluvium and located in dense area tend to have moderate until high degree of buildings

vulnerability level.

Keywords : Buildings vulnerability, lithology, buildings structure

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I. INTRODUCTION

1.1 Research Background

Earthquake is defined as sudden motion or trembling of the earth caused

by release of strain accumulated within or along the edge of Earth’s tectonic plate.

The energy released from that process is seismic vibration radiating in the earth

and felt as earthquake after reaching the Earth’s surface (Bath, 1979). This natural

phenomenon is closly related to the geological condition and tectonic plate

configuration in particular area. Areas located in the edge of Earth’s tectonic plate

tend to have high earthquake susceptibility.

Indonesia is located between three junction of active tectonic plates tend

to have high susceptibility of tectonic earthquakes occurrence. Earthquake can

occur anytime in Indonesia. It was proved, on May 27, 2006 big earthquake was

occur in Yogyakarta, located in the northern zone of the Eurasian Plate and

Indian-Australian Plate subduction zone. This earthquake caused badly damage

and causing many casualties in part of Yogyakarta. One of them is Bantul

Regency which is located closest to earthquake epicentrum according to USGS

version. As much as 26,045 building units were badly damaged, 29,582 building

units were moderate damaged, and 24,262 building units were slightly damaged.

The death toll reached 4,121 people and injured victims reached 12,026 people

(Table 1 and 2).

Table 1. Buildings Damage Data in Yogyakarta Special Province

Regency Number of Buildings (2003) Collapse Moderate Slightly

damage

Bantul 181,991 26,045 29,582 24,262

Gunungkidul 158,570 11,323 5,355 16,360

Sleman 196,965 4,719 14,403 29,910

Yogyakarta 78,079 1,948 4,119 2,355

Kulonprogo 87,940 3,485 4,726 7,999

Source: Bappenas, 2006

Table 2. The Number of Victim in Yogyakarta Special Profince

Regency Death Toll Injury

Bantul 4,121 12,026

Sleman 240 3,792

Yogyakarta 195 318

Kulonprogo 22 2,179

Gunungkidul 81 1,086

Source : Bappenas, 2006

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Pleret Sub-District is located near the Opak Fault which was estimated as

the location of earthquake epicentrum on last May 27, 2006. Pleret was badly

damaged in that eartquake event. According to FEMA the main factor causing

high number of death toll are the building damaged due to earthquake trembling.

Therefor, the buildings vulnerability mapping become the important activity in

Pleret Sub-District. In addition to that Pleret is one of the area in Bantul Regency

that has high level of earthquake hazard. It means that earthquake can occur

anytime in the future time in this area.

Remote sensing and Geographic Information Systems (GIS) is a modern

technology which support the mapping activity including mapping activity in

residential buildings vulnerability. In the other hand rapid visual screening of

building for potential seismic hazard (RVS) is a procedure in vulnerability

assessment of residential building which is developed by FEMA. RVS is one

earthquake vulnerability procedure and able to do the identification,

inventarisation and do the buildings classification regarding to earthquake. With

this procedure the assessment activity become more effisient and efective both in

time and financial point of view. The integration between remote sensing and

geographic information system (GIS) and rapid visual secreening of buildings for

potential seismic hazard can bring best improvement especially in data acquisition

, analysis, visualisation and information distribution regarding to vulnerability of

residential buildings.

1.2 Problem Statement

In 27 Mei 2006 earthquake occur in Yogyakarta Special Province and

Pleret become one of the area which has high number of death toll. Furthermore,

Pleret is classified as earthquake prone area. Pleret is also located near the Opak

Fault. Based on the earthquake record, In 1867 big earthquake also occurred in

this fault. Therefore, study of earthquake disaster with integration between all of

aspect and based on risk reduction concept is recommended to be done in research

area.

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Vulnerability mapping of residential buildings can be applied to reduce

the impact if earthquake happen again in thr future time. The mapping activity

using detail scale of mapping unit can give the acurate description from the real

condition of vulnerability of residential buildings and its spatial distribution.

Therefore, the last condition of earthquake impact on 27 May 2006 will not

happen agai if earthquake occur in Pleret Regency. In the other side, this mapping

activity can gives the important information in study of earthquake risk reduction

throught acurate spatial data such as building footprints data and its vulnerability

level. Those two data are very needed and become the preliminary need in disaster

study based on risk reduction. The main objective of this research is to know the

vulnerability level of residential buildings and its distribution in Pleret Sub-

District

II. RESEARCH METHODOLOGY

The method used was integration between remote sensing, geographic

Information system and field observation using rapid visual screening of building

for potential seismic hazard procedure. Those three tecnique was comprehensively

done in vulnerability analysis of residential buildings in Pleret Sub-District.

Remote sensing and geographic information system was conducted in

data aqcuisition process of geology and building footprints information in

research area. Geology data extraction was done by visual interpretation of

ASTER imagery recorded in 2007, while the visual interpretation of Quickbird

imagery recorded in 2010 was used for building footprints analysis. Both

informations are very needed in vulnerability analysis of residential buildings

using RVS procedure.

The color composite used was based on Landsat 7 ETM+ 4,5,7. In

Landsat 7 ETM+ band 4 is near infra red band which is good used for vegetation

identification, agricultural crops, vegetation density, and water body

identification. Band 5 is middle infra red channel which is used for humidity

identification of vegetation and soil, while band 7 is the second middle infra red

channel which is good for rock formation determination as well as lithology and

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mineral description (Santosa, 2003). Overall, the 4,5,7 composite of Landsat

imagery is best for emphasing the lithological border.

The analysis of vulnerability of residential buildings was conducted

through field observation based on rapid visual secreening of building for

potential seismic hazard procedure which is developed by FEMA in 2002. The

observed variables in this vulnerability assessment are building structur types,

buildings irregularity both plan and horizontal irregularity and surface lithology.

Unit analysis are based on the sample which was taken by stratified random

sampling method. The base of classification used was the shape of builfings

footprint and the shape of the roof. According to the shape of buildings footprint,

the residential building was devide into several groups. Those groups are reguler

building (has square shape of building footprints) and irregular building (has

certain shape of building footprint like L, U, H and O form).

The residential buildings are devided into 4 groups based on their roof

shape. Those 4 groups are joglo roof, limasan roof and cement roof (Ronald,

1997). The number of sampel are proportionally taken based on the total

population and building population on each class. In addition to that, the sample

taken are also considering about the different level of earthquake hazard. The

earthquake hazard classification refered to the surface material characteristic on

each lithological unit resulting from geology interpretation of ASTER imagery.

The hardness of surface material also influence the level of earthquake

ampification. The harder and more compat of surface material will produce the

lower of amplification level when earthquake happen, therefore can be assumed

that the more compact the surface material is the lower of earthquake hazard level.

The vulnerability index of residential buildings was resulted from the

analysis of the final score of RVS and the building density condition. Based on

that procedure the vulnerable buildings are the buildings which have the RVS

final score below the 1.75. The building density is defined quantitavely as the

number of building population per hectare. The building density also can be

measured through the basic koeficient of building density. In this research, the

density measurement used was the number of building unit in each hectare of

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block in spatial planning document (RDRTK Pleret District 2008). In this

analysis, the unit analysis used was different from the previous analysis. The

residential block from detail spatial planning document was used to calculate the

building density index. Based on that data, each village was devided into smaller

unit block. The density class used was from the detail spatial planning document

of Pleret Sub-District (2008), the classification can be shown in Table 3.

Table 3 Building Density Classification

Parameters Very low Low Moderate High

Build up Area 30% 30 – 45% 45 – 60% 60 – 75%

Building Koeficient > 5% 5 – 20% 20 – 50% 50 – 75%

Number of Building - 0 – 40 unit/Ha 40 – 80 Unit/ha 80 – 150 Unit/ha

Source: RDRTK Kecamatan Pleret, 2008

Weighted overlay on geographic information system was used to

combine those two variables. The weight score of both variable are determined

using pairwise comparison method. In this analysis the weight score was given

qualitatively according to researcher using comparison scale based on previous

study on the same topic. Overall, the flowchart of this research can be shown in

Picture 1.

III. HASIL PENELITIAN

Citra Quickbird Building footprint Visual Interpretation

Building footprint

Based on the roof

types

Classification Process

Residential

Building Sample

Sample design

RVS Score

RVS

ASTER Image

RGB

3,4,PCA,4,6,7,8,9

Geometric Correction

Layer Stacking

PCA

Lithologycal Unit

Intepretasi visual

Surface material

FEMA Classification

Building density

Pairwise method

Weighted Value Vulnerability map of

residential buildings Weighted overlay

Pictire 1 Research Work Flow

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III. Result and Discussion

3.1 Geologi Interpretation

Digital Image Processing for study of lithology using ASTER image is

consist several process such as layer stacking, geometric correction and RGB

transformation using principle component analysis (PCA). All of the processes

have single objective for prepare the better image with clear color composite to

show the lithological aspect in research area. According to the result of layer

stacking process, there was one group of channel consist visible and near infrared

(VNIR) channel and also Short Wavelength Infrared Radiometar (SWIR) channel

which have the same spatial resolution i.e. 30 meter.

Based on the result of geometric correction, researcher can get new

image of ASTER with new spatial reference and the true north orientation. The

facility used in this process is image to image regristration with the help of the

previous record of ASTER image in 2006. This facility was used due to the work

efficiency. With this facility researcher do not need use the ground control point

to register the unregistration ASTER image which need longer time.

The PCA analysis was applied in SWIR band. PCA analysis will

combine those 5 channels on SWIR band become one channel without any

elemination of information carried by each band. As a result, this process gives

one new band equal to band 7 in Landsat 7 ETM + which has 2.08-2.35 µm

wavelenght. The comparison between ASTER image and Landsat 7 ETM+

regarding this process can be seen on Picture 2.

Visible – Near IR Short Wave IR Thermal IR

Picture 2. The comparison between band in ASTER image and Landasat ETM 7+

Source: Abrams and Hook, 2003 in Nurwihastuti, 2008

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There are 4 lithological units based on the visual interpretation results.

Those four lithological units are Semilir Formation (Tmse), Nglanggran (Tmn),

Aluvium (Qa) and Young Merapi Deposite (Qmi). Each lithological unit has

different configuration of rock material. The interpretation result can be seen in

the Table 4.

Table 4 Lithological Types in Pleret Sub-District

No Symbol Lithology Rock Area

Ha %

1 Qa Alluvium Gravel, sand, silt and clay from Smilir

Formation and Nglanggran Formation

Material

267.94 11.24

2 Qmi

Young Volcanic

Deposits of

Merapi Volcano

Tuff, ash, breccia, agglomerat and

leleran lava tak terpisahkan 1,086.68 45.62

3 Tmn Nglanggran

Formation

Volcanic Breccia, Flow Breccia,

agglomerate, lava and tuff 82.16 3.44

4 Tmse Semilir

Formation

Interbedded tiff-breccia, pumice

breccia, dacite tuff and andesite tuffs,

tuffaceous claystone

945.03 39.68

Sumber: Primary data processing, 2011

Semilir Formation can be easily identified using ASTER image composite

3,4,PCA 56789. Based on that color composite this lithological unit gives bright

blue color with brownish red spots. The bright blue color shows open land and

moor, while the brownish red spots shows the woody vegetation. This pattern

indicates that the Semilir Formation is dominated by open land (breccia pumice

mining areas) and dry field farming such as moor. In this lithological unit also has

coarse texture impression which indicates many grooves of erosion on the flank of

Semilir hills.

Nglanggarn Formation has distinctly different colors with Semilir unit.

The Nglanggran unit give brownish red color with blue spots. The brownish red

color shows woody vegetation, while the blue spots indicates open land and rock

outcrops. The color defference on both Semilir and Nglanggaran unit mean that

Semilir and Nglanggran have different of rock arrangement. Nglanggran

Formation is consist of compact rock which is dominated by breccia andesite and

lava flows. The color of Nglanggran rock formation is darker than the Semilir

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unit. That rock color indicates the level of acidity. Bright color of rock means that

the rock has higher level of acidity, while the darker color means low level of

acidity. The soil layer on this litholigical unit have developed well which is

indicated from the high density of vegetation in this unit. The other characteristic

is texture. This formation has smoother texture that the Semilir unit. The spatial

distribution of this units is on the top of Baturagung hills.

Alluvium is the denudation material from Semilir and Nglanggaran

Formation which is carried away by water and deposited nearby foothills. In the

ASTER, this material have smooth texture besause located in gently slope. The

color is dominated by bluish green and many brownish red spots along the river.

This brownish red spots are settelements. The other existing color in this unit is

dark green color which indicated the agricultural crops,

The Young Deposites of Marapi Volcano is dominated by bluish green

and reddish brown color. The bluish green shows the combination of settlements

area and farming field, while reddish brown shows the vegetation. Glance, This

lithological unit is similar with the alluvium unit because of their spatial

distribution. However, in the further analysis shown that Young Deposits of

Merapi Volcano have fertile soils from volcanic product which is used for farming

area. In addition to that in this lithological unit has less clay content comparing to

the alluvium matrial. It is proven that in this area is commonly found the clay

bricks artisans, because the clay content in this lithological unit is not too high and

suitable for raw materials of clay bricks production. The higher of clay content

cause the resulting bricks easily to crack. The interpretation result can be shown in

Table 5.

Table 5. ASTER Imagery Characteristic in Visual Interpretation of Geological Aspect

Lithology Tone/ Color Texture Vegetation Landuse

Semilir Bright blue with brownish

red spot

Rough Low Dry field and open

area (mining area)

Nglanggran Brownish red with blue

spots

Moderate to

rough

Dense Cultivation and non

cultivation vegetation

Alluvium Bluish green with

brownish red spots

Fine Low Rainfed farming land

Young Deposites of

Merapi Volcano

Blue with red spots Fine Low Settlements and

farming area

Source : Interpretation result, 2011

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3.2 Building Footprints Interpretation

Building objects identification was done by the visual interpretation

process on Quickbird imagery recorded in 2010. The interpretation process was

produced 17,513 building objects. Tone or color, shape, shadow and association

are the most used elements in visual interpretation. The most common color

reflect the building objects are dark brown, blue, green and grey. Those colors are

the color of roof material of buildings. Dark and light brown color indicate that

the building use clay tile, while the green and blue are painted clay tile. The white

color is zinc and asbestos roof materials, while gray color is cement roof type.

The building shape is dominated by regular shape both square shape and

rectangular shape. However, there are also several buildings object which have

irregular shape such as L, U, O and H shape. Shadow is the most important aspect

in the building identification process. Sometimes, an object has similar color with

building, but if the object does not has shadow nearby, it means the object is not a

building. The other key of interpretation is association, a building object is usually

located near the road network.

The separation process between residential buildings and non residential

buildings was done by the analysis of several key parameters such as shape, size,

and association. The separation process produced 16,318 buildings object

classified as residential building and 1,195 classified as non redisedential building

such as office, hospital, shopping complex, traditional market, cattle sheds, etc.

Based on the roof shape, The most striking feature is 89.50% residential buildings

use the kampung roof type, while limasan only about 9.60% from the total

residentian buildings resulted from visual interpretation. The other minority roof

design are Joglo with only 0.63%, sement roof type 0.12%, Kampung irregular

0.06% and Limasan irregular 0.04%. This classification process is usefull to ease

the vulnerability analysis and generalisation the building groups.

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3.3 Rapid Visual Screening of Buildings for Potential Sismic Hazard

The rapid visual screening of buildings for potential seismic hazard

procedure was conducted to sevaral samples buildings. The number of sample are

calculated proportionally from the number of building population. The building

samples distribution can be shown in Table 6.

Table 6 Sample Distribution by its classification and its number

Building

Shape

Roof Types

Joglo Limasan Kampung Cement roof

L M H L M H L M H L M H

Regular 6 - 24 9 2 33 30 5 199 - 2 15

Irregular - - - - - 6 1 1 7 - - -

Sumber: Pengolahan data primer, 2011

L represent the low level of earthquake hazard areas, M represent moderate areas,

and H represent high areas. From the table can be known that Kampung roof type

is dominated in all of level of hazard zonation.

Based on the field observation, most of residential buildings are used

reinforced masonry with rigid diaphragms structure (RM2). The other building

structure used in research area are wood (W1), reinforced masonry with flexible

diaphragms (RM1) and unreinforced masonry (URM). The presentation of

building structure can be seen on Picture 3, while the presentation of building

structure based on their roof types can be seen on Picture 4 below.

RM2= Reinforced masonry with rigid diaphragms; RM1= Reinforced masonry with flexible

diaphragms; URM= Unreinforced masonry; W1= Wood structure

Picture 3. Building composition based on their structure types

Source: Primary data processing, 2011

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Picture 4. Building Structure Presentation by their roof types


Gambar 5 Tingkat Kerentanan Bangunan Tempat Tinggal Menurut Tipe Atapnya

Sumber: Pengolahan data primer, 2011

Based on the result of vulnerability assessment using RVS procedure, it

can be known that Joglo, the traditional Javanese roof type, has the highest score

of RVS for abour 3.54 (Picture 5). This score is average value from the final score

and it means that this buildings is not vulnerable (above the limit 1.75). The

higher the RVS score indicates that the stronger the building and the lower of

probability of building collapse. The vulnerable building which has lower score of

RVS are buildings with kampung and limasan roof design and have irregular

2,1 %

1,3 %

0,4 %

Vulnerability Limit FEMA 154, 2002)

Joglo

Kampung (regular)

Limasan (irregular)

Limasan (regular)

Cement roof type

Kampung (irregular)

Low Hazard Area Moderate Hazard Area High Hazard Area

Cement

roof type

Limasan

Irregular Kampung

Irregular

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shape. The main factor cause this condition are the plan irregularity of building

and located in certain lithological unit that associated with the moderate and high

level of earthquake hazard. The RVS score on this building group is only 1.70.

To get the vulnerability index between 0 – 1 (0 means not vulnerable and

1 mean vulnerable), researcher have converted the final score of RVS using cost

standardization factor method. The conversion result can be seen in the Table 7.

Table 7 Building Vulnerability Index Based on Cost Standardization conversion

Roof Type Low hazard Moderate hazard High hazard

Score RVS Index Score RVS Index Score RVS Index

Joglo 3.54 0.48 - - 3.30 0.51

Limasan 2.80 0.59 2.20 0.68 2.20 0.68

Kampung 2.75 0.595 2.20 0.68 2.20 0.68

Sement Roof - - 2.20 0.68 2.20 0.68

Limasan (irregular) - - - - 1.70 0.75

Kampung (irregular) 2.30 0.66 1.70 0.75 1.70 0.75


3.4 Building Density Analysis

Building density analysis was done by using the settlement block as

analysis unit. Based on the building density calculation, it can be known that

majority settlemente block in Pleret Sub-District have low level of building

density for about 0 – 40 building units per hectare. There are only three settlement

blocks which have moderate level of building density above 40 building units per

hectare. Those three blocks are block number 18 Wonokromo, 9 Pleret and 5

Bawuran.

3.5 Building Vulnerability Index

Building vulnerability index was obtained from compound score of RVS

and the level of building density. Most of residential building have moderate

vulnerability except Wonolelo village which has low vulnerability. Most of

residential buildings in Wonokromo village that located in Young Deposites of

Marapi Volcano have moderate vulnerability level. The high level of vulnerability

in this village is concentrated in block 18 Kanggotan Sub-village. In this sub-

village, most of buildings are kampung (91.6%). The building density on this

block is 40 – 80 units/ ha.

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In Pleret village, the vulnerable buildings are located in block 9 i.e. east

part of Kaputren sub-village. The roof type composition on this villages are

94.5% kampung, limasan (4.8%) and joglo (0.7%). The building density reach 40

– 80 units/ ha and categorized as moderate building density. Overall, the

vulnerability level of residential building in Pleret village are moderate.

In Bawuran village, the high vulnerability buildings are concentrated in

block 5 (Bawuran Dua sub-village). The characteristic on this block is similar to

the previous mentioned block. Dominated by kampung roof type followed by

limasan with only around 5 % and joglo with only 0.1%. The building density in

this block is relatively high with 40 – 80 units/ ha. Overall, Bawuran village is

dominated by residential buildings which have moderate level of earthquake

vulnerability likewise in Segoroyoso and Wonolelo. It also can be conclude that

stiff material like Semilir and Nglanggran are able to absorb the seimic tremor

when earthquake happen. The vulnerability map of residential buildings can be

seen in Appendix 1.

IV. CONCLUSION

Majority residential buildings in Pleret sub-district have moderate level

of earthquake vulnerability (between 0.55 – 0.65 of vulnerability index). This

vulnerability index was produced from three main aspects calculation i.e. geology

charachteristic, RVS score and building density. The high level of earthquake

vulnerability are concentrated on several locations in Pleret Sub-District such as

Block 18 at Wonokromo village, Block 9 at Pleret Village and Block 5 at

Bawuran village. Those three village have the same moderate level of building

density. The low level of earthquake vulenarability are accupied on Wonolelo

village which has stiff surface material (Semilir and Nglanggran Formation)

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DAFTAR PUSTAKA

Anonim. 2002. Keputusan Menteri Permukiman dan Prasarana Wilayah No

403/KPTS/M/2002 tentang Pedoman Teknis Pembangunan Rumah

Sederhana Sehat (Rs SEHAT).

Badan Perencanaan Pembangunan Daerah Kabupaten Bantul. 2008. Rencana

Detail Tata Ruang Kawasan (RDRTK) Kecamatan Pleret. BAPPEDA

Kabupaten Bantul. Yogyakarta

Bappenas. 2006. Preliminary Damage and Loss Assessment. Consultatif Group

Indonesia. Jakarta.

Bath, M. 1979. Introduction to Seismology,Second Edition. Birkhauser. Verlaag.

BPS. 2010. Pleret Dalam Angka. Badan Pusat Statistik (BPS). Yogyakarta

Carter. 1991. Disaster Management: A Disaster Manager’s Handbook,1. Asian

Development Bank. Manila Philippines.

FEMA. 2002. Rapid Visual Screening of Buildings for Potential Seismic Hazards:

A Handbook FEMA 154, Edition 2. The Federal Emergency Management

Agency (FEMA). Washington, DC.

Jimme. 2006. Seismic Vulnerability and Capacity Assessment at Ward Level A

Case Study of Ward No.20, Lalitpur Sub-Metropolitan City, Nepal. MSc

Thesis, ITC. Enschede, Netherland.

Nurwihastuti. 2008. Integrasi Pemrosesan Citra ASTER dan Sistem Informasi

Geografis Untuk Kajian Geomorfologi Studi Kasus di Sebagian Daerah

Istimewa Yogyakarta. Tesis S-2. Fakultas Geografi UGM. Yogyakarta.

Ronald, A. 1997. Ciri-Ciri Karya Budaya Di Balik Tabir Keagungan Rumah

Jawa: Cetakan kedua. Penerbitan Universitas Atma Jaya. Yogyakarta

Santoso, S. 2003. Studi Potensi Bahan Galian Sebagai Bahan Baku Industri

Keramik di Kabupaten Blitar Bagian Selatan (Ditinjau Dari Aspek

Geologi dan Geomorfologi). Skripsi S-1. Fakultas Geografi UGM.

Yogyakarta.

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APPENDIX 1. Earthquake vulnerability map of residential building in Pleret Sub-District

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PAPER INFORMATION

Paper reference No : PN-51

Tittle : EARTHQUAKE VULNERABILITY MAPPING OF

RESIDENTIAL BUILDINGS BASED ON THE

GEOLOGICAL AND BUILDING FOOTPRINT

CHARACTERISTIC IN PLERET SUB-DISTRICT

BANTUL REGENCY, 2012

Name of Presenter : Aditya Saputra

Authors : Aditya Saputra, Priyono, Yuli Priyana, Agus Anggoro

Sigit

Mailing Address : Jl. A. Yani Kartasura Tromol Pos 1 Surakarta 57102

Email Address : [email protected]

Telephone Number : +6285729870149

Fax Number : -

Brief Biography : Graduated from undergraduated program in Geograpfy

Faculty of Gadjah Mada University majoring in

environmental geography in 2009. Master’s degree from

Geo Information for Spatial Planning and Risk Management

prostgraduate school of Gadjah Mada University Indonesia.

Now wark as teaching staff in geography faculty at

Muhammadiyah University of Surakarta Central Java.

Documents

EARTHQUAKE VULNERABILITY MAPPING OF ... saputra.pdfJl. A. Yani Kartasura Tromol Pos 1 Surakarta 57102 [email protected] , [email protected], [email protected] ABSTRACT