EVALUATION OF TSUNAMI DAMAGE IN THE EASTERN PART OF SRI LANKA DUE TO THE 2004 SUMATRA EARTHQUAKE USING REMOTE SENSING TECHNIQUE ABSTRACT

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1 EVALUATION OF TSUNAMI DAMAGE IN THE EASTERN PART OF SRI LANKA DUE TO THE 2004 SUMATRA EARTHQUAKE USING REMOTE SENSING TECHNIQUE H. Miura 1, A. C. Wijeyewickrema 2 and S. Inoue 3 ABSTRACT In order to develop a methodology to evaluate damage distribution for appropriate emergency management after natural disasters, the applicability of the remote sensing technique using high-resolution satellite images for the evaluation of tsunami damage due to the Indian tsunami generated by the Sumatra earthquake in December 26, 2004 is examined in Batticaloa, located in the eastern part of Sri Lanka. The damage levels of buildings are visually interpreted by comparing the IKONOS images observed before and after the earthquake. The damage level evaluated from the images is compared with the field survey observations for the validation of the inspection. The results for washed away or completely collapsed buildings show good agreement with the actual damage, while it is difficult to distinguish partially collapsed buildings from slightly damaged buildings. The relationship between the damage distribution and the inundation area measured in the field survey is discussed. Introduction In order to consider emergency response and rehabilitation planning after natural disasters, e.g. earthquakes or floods, it is important to find out the damage distribution as soon as possible. Remote sensing technologies have been utilized for the evaluation of disaster damage because satellite images can widely capture surface ground conditions. Recently, high-resolution satellite images, e.g. IKONOS or QuickBird with a ground resolution of 1m or less, have been available at a low cost. The resolutions of those images are much higher than the resolutions of the conventional satellite images, e.g. Landsat or SPOT. Hence, it has become possible to consider conducting surveys for individual buildings with high-resolution satellite images. While the usefulness and the accuracy of satellite images for evaluation of damage have been discussed in earthquake disasters, they have not been fully examined in other disasters. The Sumatra earthquake on 26th December 2004 caused great tsunami damage to the countries in the Indian Ocean. Sri Lanka is one of the countries that were severely damaged due 1 Postdoctoral Research Fellow, Center for Urban Earthquake Engineering, Tokyo Institute of Technology, Yokohama, Japan 2 Associate Professor, Dept. of Civil Engineering, Tokyo Institute of Technology, Tokyo, Japan 3 Research Associate, Dept. of Built Environment, Tokyo Institute of Technology, Yokohama, Japan

2 to the tsunami. In order to comprehend the tsunami damage, the distribution of the damaged buildings should be evaluated. Visual detection method of damaged buildings has been applied to high-resolution satellite images observed before and after recent large earthquakes (Chiroiu et al. 2002, Saito et al. 2004, and Kouchi et al. 2004). However, characteristics of the image in the area affected by tsunami disaster have not been examined in detail. In this study, visual detection of damaged buildings is carried out using high-resolution satellite IKONOS images observed before and after the tsunami disaster in the eastern part of Sri Lanka. The results of these inspections are compared with the field survey data and the accuracy and the limitation of the evaluation of the images are discussed. The 2004 Sumatra Earthquake and IKONOS images in Sri Lanka Figure 1 shows the area affected by the 2004 Sumatra earthquake. The star shows the location of the epicenter of the main shock. The circles show the locations of the aftershocks. The fault length and moment magnitude of the earthquake are estimated at about 1200km and 9.3, respectively (Bilham 2005). The great tsunami generated by the large earthquake hit the countries of the Indian Ocean. The number of the casualties in the countries compiled by WHO (2005) is shown in Figure 1. More than 100,000 people died in Indonesia, which is situated near the epicenter. Also in Sri Lanka, which is located 1,500km away from the source region, the deaths and missing people are more than 30,000 and 5,000, respectively. Most of them were killed by the tsunami. The travel time of the tsunami computed by Active Fault Research Center (2005) are also shown in Figure 1. According to the simulation, the tsunami reached Sri Lanka two to three hours after the occurrence of the earthquake. Figure 2(a) shows the locations of the major coastal cities in Sri Lanka. The tsunami damage in the cities compiled by National Disaster Management Center Sri Lanka (2005) is shown in Table 1. The eastern and southern provinces show more severe damage than the western province such as Colombo, the capital of Sri Lanka. Before and after the tsunami disaster, the high-resolution satellite IKONOS images whose resolution is 1m were captured in Batticaloa district that is one of the districts that were severely damaged. Figure 2(b) shows the pre- and post-event images in the central part of Batticaloa. The pre-event images were taken in 2000 and 2001 while the post-event image was taken one month after the earthquake. The area of the images is about 120km 2 and the image covers about 1/10 of the coastal area in the entire district. Total 148,724 (Death) 142,123 (Missing) Thailand 5,332 3,144 India 10,872 5,551 Sri Lanka 30,959 5,644 Epicenter(Mw9.3) 2004/12/26 Indonesia 101, ,749 Figure 1. Number of deaths and missing people compiled by WHO (2005). Contours show travel time (in hours) of tsunami computed by Active Fault Research Center (2005).

3 (a) (b) Jaffna Before After Jan.25, 2005 Trincomalee Batticaloa Ampara Oct.21, 2000 Colombo Galle Hambantota Matara Feb.11, km 0 5km Figure 2. Map of Sri Lanka and IKONOS satellite images in Batticaloa used in this study. Table 1. Tsunami damage complied by National Disaster Management Center (2005). Province District Deaths Missing Damaged Houses Completely Partially Northern Jaffna 2, ,084 1,114 Trincomalee 1, ,974 10,394 Eastern Batticaloa 2,840 1,033 15,939 5,665 Ampara 10, ,199 - Hambantota 4, ,303 1,744 Southern Matara 1, ,362 5,659 Galle 4, ,525 5,966 Western Colombo ,398 2,210 Visual Detection of Building Damage in Batticaloa The visual detection of the damaged buildings is carried out using the images shown in Figure 2(b) based on the classification in the European Macroseismic Scale (European Seismological Commission 1998). The classification of the damage to masonry buildings, shown in Figure 3, is used in this study because most of the buildings in the area are unreinforced masonry buildings infilled with brick. Using the pre- and post-event images, buildings washed away by the tsunami, totally collapsed buildings (Grade 5 (G5)), and partially collapsed buildings (Grade 4 (G4)) are identified. It is difficult to distinguish slightly damaged buildings

4 from undamaged buildings in the IKONOS image because the spatial resolution is not fine enough compared with aerial photographs. All the buildings for Grade 1, 2, and 3 damage levels are judged as G1-G3. Figure 4 shows the comparison of the images before and after the event. Figures 4(a-1) and (a-2) represent the buildings washed away by the tsunami. While the buildings indicated by the circle exist in the pre-event image, they are completely washed away with the surrounding vegetation in the post-event image. Figures 4(b-1) and (b-2) represent the totally collapsed buildings. In the post-event image, the colors of the buildings in the circle are now white. It indicates that the roof and most of the walls are completely destroyed and the basement of the building is exposed. Therefore, those buildings are judged as G5 damage level. Figures 4(c-1) and (c-2) represent the partially collapsed buildings. The colors of the buildings change little in the appearance. Because some part of the buildings has failed and the debris is clearly observed in the post-event image, the buildings are judged as G4. Figures 4(d-1) and (d-2) represent undamaged or slightly damaged buildings. Because a significant difference of the buildings is not identified between the images, the buildings are judged as G1-G3. A field survey was conducted to confirm the damage of the area in March Photographs shown in Figures 5(a), (b), and (c) correspond to the buildings in Figures 4(a-2), (b- 2), and (c-2), respectively. No buildings can be found in Figure 5(a) because they were completely washed away by the tsunami. The columns and walls of the building shown in Figure 5(b) were completely destroyed. The building was totally collapsed by the tsunami. Because some part of the roof of the building shown in Figure 5(c) was destroyed, it indicates that the building was partially collapsed. In these cases, the comparison shows that the result of the visual inspection shows good agreement with the damage level of the photographs. Photographs and videos of the damaged buildings were taken during the field survey. The damage levels of the buildings are classified based on the photos and the videos. Totally, the damage levels of 51 buildings and their locations are identified and geo-referenced to Classification of damage to masonry buildings Grade 1: Negligible to slight damage (no structural damage, slight non-structural damage) Hair-line cracks in very few walls. Fall of small pieces of plaster only. Fall of loose stones from upper parts of buildings in very few cases. Grade 2: Moderate damage (slight structural damage, moderate non-structural damage) Cracks in many walls.fall of fairly large pieces of plaster. Partial collapse of chimneys. Grade 3: Substantial to heavy damage (moderate structural damage, heavy non-structural damage) Large and extensive cracks in most walls. Roof tiles detach. Chimneys fracture at the roof line; failure of individual non-structural elements (partitions, gable walls). Grade 4: Very heavy damage (heavy structural damage, very heavy non-structural damage) Serious failure of walls; partial structural failure of roofs and floors. Grade 5: Destruction (very heavy structural damage) Total or near total collapse. Figure 3. Classification of damage to masonry buildings in EMS-98.

5 (a-1) Before (a-2) After Washed away (b-1) (b-2) G5 (c-1) (c-2) G4 (d-1) (d-2) G1-G3 Figure 4. Comparison of images observed before and after the tsunami disaster. (a) Washed away buildings, (b) Totally collapsed buildings (G5), (c) Partially collapsed buildings (G4), (d) Undamaged or slightly damaged buildings (G1-G3).

6 the satellite image. The damage levels based on the photos and the videos are compared with the results of the visual inspection of the IKONOS images. Table 2 shows the comparison of theclassified damage level. In the field survey, it is possible to identify slightly damaged buildings such as Grade 1 or Grade 2. In Table 2, the cells surrounded by thick lines indicate that the damage level of the visual interpretation agree with the classification in the field survey. The results of the visual interpretation for G5 and Washed away buildings almost agree with the actual damage. However, some of the G4 or G1-G3 buildings are misjudged in the visual inspection. For the buildings judged as G4 in the visual inspection, two and one buildings are classified into G2 and G3 in the field survey, respectively. The damage levels for the buildings are overestimated because some debris is observed around the buildings and the textures of the roofs seem to be rough in the post-event image. On the contrary, for the buildings classified into G4 in the field survey, the damage level of seven buildings is underestimated in the visual inspection while the result for five buildings corresponds with the actual damage. This is because the walls of the underestimated buildings are seriously damaged while the roofs are negligibly damaged. It is difficult to identify the damage of the walls from the satellite because the satellite image can observe only the roofs of the buildings. These results suggest that the actual damage level of the buildings judged as G4 in the visual interpretation is at least more than G2, although the accuracy of the interpretation for G4 buildings is not so high. (a) (b) (c) Figure 5. Photographs of (a) Washed away building, (b) Totally collapsed buildings, and (c) Partially collapsed building. Table 2. Comparison of visual interpretation of IKONOS images with field survey. IKONOS image Field survey G1-G3 G4 G5 Washed away Sum G G G G G Washed away Sum

7 The Distribution of Building Damage with Inundation Area Visual detection of building damage is applied to the entire area of the image. Figure 6(a) shows the distribution of the classified buildings in Batticaloa. A total of about 20,000 buildings are detected in the area. More than 90% of the buildings are judged as G1-G3 while about 10% of the buildings are identified as severely damaged buildings. The damaged buildings are concentrated in the eastern coastal line while G1-G3 buildings are distributed in the western area. The severely damaged buildings are distributed in the inland area within 1,000m from the coastal line. Especially, more than 90% of the buildings are severely damaged in the northern part of the area indicated by red circle. The area is located in the edge of sandspit extending into the ocean and the width of the land is only 500 to 1,500m. According to the evidence of the local inhabitants, the tsunami crossed over into the western lagoon in the area. In the field survey, the inundation area due to the tsunami and the tsunami height were investigated using GPS based on the evidence of the local inhabitants. Figure 6(b) shows the results of the survey with the digital elevation model of SRTM-3 (NASA 2005) whose resolution is approximately 90m. Solid circles indicate the location of GPS survey point for the boundary of the inundation area. The elevation of the point was also measured in the survey. Solid (a) (b) A B Figure 6. (a) Distribution of classified buildings, (b) Survey points for inundation boundary and tsunami height with Digital Elevation Model (SRTM-3 data).

8 triangles and open triangles represent the survey point for the tsunami height investigated in this study and measured by Tanioka and Nishimura (2005), respectively. The dashed line shows the estimated boundary of the inundation area by connecting the survey points with a straight line. The results show that the area 800m to 1500m from the eastern coastal line was inundated and the tsunami with height more than 9m hit this region. As shown in Figures 6(a) and (b), the severely damaged buildings detected by the visual inspection are distributed within the inundation area. Figure 7 shows the cross section of line A-B indicated in the Figure 6(a). The bottom figure shows the distribution of the damaged buildings along the line while the upper figure shows the tsunami height observed on the coastal line and the elevation of the inundation boundary. In the area, the tsunami inundated more than 800m distances from the coastal line. The damaged buildings judged as more than G4 are distributed in about 500m distances area. In the area that the distance from the coastal line is 500m to 800m, severely damaged buildings are not observed because the tsunami depth is estimated to be shallow. Inundation area Damaged area Elevation (m) Inundation boundary Tsunami height Washed away G5 G4 G1-G B 500 Distance (m) Coastal line 0 A Figure 7. Cross section of elevation for inundation boundary with tsunami height and the distribution of damaged buildings along line A-B shown in Figure 6(a). Conclusions Using high-resolution satellite IKONOS images of Batticaloa, Sri Lanka acquired before and after the 2004 Sumatra earthquake, visual interpretation of building damage is conducted. The results of the interpretation are compared with the actual damage based on the field survey. The comparison shows that buildings washed away by the tsunami and totally collapsed buildings are well identified, while it is difficult to distinguish partially collapsed buildings from slightly damaged buildings. Applying the method to all the images reveals that the severely damaged buildings are concentrated along the eastern coastal line. About 10% of the buildings

9 are classified as severely damaged buildings. The damage distribution is compared with the inundation area investigated in the field survey. The result shows that the damaged buildings are distributed in the inundation area. Acknowledgments The authors are grateful to Dr. Hiroyuki Matsumoto (Japan Agency for Marine-Earth Science and Technology), Dr. Priyantha Gunaratna (University of Moratuwa), and Mr. Manoj Madurapperuma (University of Moratuwa) for helping the field survey. The authors also thank Prof. Saburoh Midorikawa (Tokyo Institute of Technology) for helpful comments to this manuscript. References Active Fault Research Center, National Institute of Advanced Industrial Science and Technology, December 26 Tsunami in Indian Ocean, Bilham, R., A flying start, then a slow slip, Science, 308(5725), Chiroiu, L., G. Andre, R. Guillande, and F. Bahoken, Earthquake damage assessment using high resolution satellite imagery, Proc. of 7th National Conference on Earthquake Engineering, Paper No (CD-ROM). European Seismological Commission, European Macroseismic Scale Kouchi, K., F. Yamazaki, F. Kohiyama, M. Matsuoka, and N. Muraoka, Damage detection from QuickBird high-resolution satellite images for the 2003 Boumerdes, Algeria earthquake, Proc. of Asia Conference on Earthquake Engineering, 2, National Aeronautics and Space Administration (NASA), Shuttle Radar Topology Mission, srtm/. National Disaster Management Center Sri Lanka, Sri Lanka Tsunami Disaster Statistics, Tsunami statistics.htm. Saito, K., R. J. S. Spence, C. Going, and M. Markus, Using high-resolution satellite images for post-earthquake building damage assessment: a study following the 26 January 2001 Gujarat earthquake, Earthquake Spectra, 20 (1), Tanioka, Y. and Y. Nishimura, Field Survey Result in Sri Lanka, The December 26, 2004 Earthquake Tsunami Disaster of Indian Ocean, sumatra/srilanka2/ (in Japanese). World Health Organization (WHO), South Asia tsunami situation reports 32 (1st February, 2005),