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1 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 Asia Geospatial Forum, 17-19 September 2012, Hanoi, Vietnam 2 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 Bantul 181,991 26,045 29,582 Gunungkidul 158,570 11,323 5,355 Sleman 196,965 4,719 14,403 Yogyakarta 78,079 1,948 4,119 Kulonprogo 87,940 3,485 4,726 Source: Bappenas, 2006 Table 2. The Number of Victim in Yogyakarta Special Profince Regency Death Toll Injury Bantul Sleman Yogyakarta Kulonprogo Gunungkidul Source : Bappenas, 2006 Asia Geospatial Forum, 17-19 September 2012, Hanoi, Vietnam 4,121 240 12,026 3,792 195 22 81 318 2,179 1,086 Slightly damage 24,262 16,360 29,910 2,355 7,999 3 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. Asia Geospatial Forum, 17-19 September 2012, Hanoi, Vietnam 4 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 SubDistrict 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 Asia Geospatial Forum, 17-19 September 2012, Hanoi, Vietnam 5 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 Asia Geospatial Forum, 17-19 September 2012, Hanoi, Vietnam 6 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. Parameters Table 3 Building Density Classification Very low Low Moderate Build up Area 30% 30 – 45% Building Koeficient > 5% 5 – 20% Number of Building 0 – 40 unit/Ha Source: RDRTK Kecamatan Pleret, 2008 High 45 – 60% 60 – 75% 20 – 50% 40 – 80 Unit/ha 50 – 75% 80 – 150 Unit/ha 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. Citra Quickbird Visual Interpretation Building footprint ASTER Image Geometric Correction Layer Stacking PCA Classification Process Building density Building footprint Based on the roof types RGB 3,4,PCA,4,6,7,8,9 Sample design Residential Building Sample Intepretasi visual Lithologycal Unit FEMA Classification Surface material RVS Pairwise method RVS Score Weighted Value III. HASIL PENELITIAN Weighted overlay Vulnerability map of residential buildings Pictire 1 Research Work Flow Asia Geospatial Forum, 17-19 September 2012, Hanoi, Vietnam 7 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 Asia Geospatial Forum, 17-19 September 2012, Hanoi, Vietnam 8 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 1 Qa Alluvium Gravel, sand, silt and clay from Smilir Formation and Nglanggran Formation Material 2 Qmi 3 Tmn 4 Tmse Young Volcanic Deposits of Merapi Volcano Nglanggran Formation Semilir Formation Area Ha % 267.94 11.24 1,086.68 45.62 Volcanic Breccia, Flow Breccia, agglomerate, lava and tuff 82.16 3.44 Interbedded tiff-breccia, pumice breccia, dacite tuff and andesite tuffs, tuffaceous claystone 945.03 39.68 Tuff, ash, breccia, agglomerat and leleran lava tak terpisahkan 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 Asia Geospatial Forum, 17-19 September 2012, Hanoi, Vietnam 9 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 Asia Geospatial Forum, 17-19 September 2012, Hanoi, Vietnam 10 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. Asia Geospatial Forum, 17-19 September 2012, Hanoi, Vietnam 11 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 Roof Types Building Shape 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 Asia Geospatial Forum, 17-19 September 2012, Hanoi, Vietnam 12 2,1 % 1,3 % 0,4 % Cement roof type Limasan Irregular Kampung Irregular Picture 4. Building Structure Presentation by their roof types Source: Primary data processing, 2011 Joglo Kampung (regular) Limasan (irregular) Limasan (regular) Cement roof type Kampung (irregular) Vulnerability Limit FEMA 154, 2002) Low Hazard Area Moderate Hazard Area High Hazard Area 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 Asia Geospatial Forum, 17-19 September 2012, Hanoi, Vietnam 13 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 Source: Primary data processing, 2011 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 subvillage, most of buildings are kampung (91.6%). The building density on this block is 40 – 80 units/ ha. Asia Geospatial Forum, 17-19 September 2012, Hanoi, Vietnam 14 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) Asia Geospatial Forum, 17-19 September 2012, Hanoi, Vietnam 15 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. Asia Geospatial Forum, 17-19 September 2012, Hanoi, Vietnam 16 APPENDIX 1. Earthquake vulnerability map of residential building in Pleret Sub-District Asia Geospatial Forum, 17-19 September 2012, Hanoi, Vietnam 17 PAPER INFORMATION Paper reference No Tittle Name of Presenter Authors Mailing Address Email Address Telephone Number Fax Number Brief Biography : PN-51 : EARTHQUAKE VULNERABILITY MAPPING OF RESIDENTIAL BUILDINGS BASED ON THE GEOLOGICAL AND BUILDING FOOTPRINT CHARACTERISTIC IN PLERET SUB-DISTRICT BANTUL REGENCY, 2012 : Aditya Saputra : Aditya Saputra, Priyono, Yuli Priyana, Agus Anggoro Sigit : Jl. A. Yani Kartasura Tromol Pos 1 Surakarta 57102 : [email protected] : +6285729870149 :: 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. Asia Geospatial Forum, 17-19 September 2012, Hanoi, Vietnam