REMOTE SENSING TECHNOLOGIES IN POST-DISASTER DAMAGE ASSESSMENT

2007 ◽  
Vol 01 (03) ◽  
pp. 193-210 ◽  
Author(s):  
FUMIO YAMAZAKI ◽  
MASASHI MATSUOKA

This paper highlights the recent applications of remote sensing technologies in post-disaster damage assessment, especially in the 2004 Indian Ocean tsunami and the 2006 Central Java earthquake. After the 2004 Indian Ocean tsunami, satellite images which captured the affected areas before and after the event were fully employed in field investigations and in tsunami damage mapping. Since the affected areas are vast, moderate resolution satellite images were quite effective in change detection due to the tsunami. Using high-resolution optical satellite images acquired before and after the 2006 Central Java earthquake, the areas of building damage were extracted based on pixel-based and object-based land cover classifications and their accuracy was compared with visual inspection results. In the Central Java earthquake, ALOS/PALSAR captured a SAR image of the affected area one day after the event as well as pre-event times. Taking the difference of the pre-event correlation and the pre-and-post event correlation, the areas affected by the earthquake were also identified. From these examples, the use of proper satellite imagery is suggested considering the area to cover, sensor type, spatial resolution, satellite's retake time etc., in post-disaster damage assessment.

2010 ◽  
Vol 04 (02) ◽  
pp. 51-60 ◽  
Author(s):  
OSAMU MURAO ◽  
HIDEAKI NAKAZATO

On the 26th of December 2004, the Tsunami damaged to five provinces in Sri Lanka and more than 40,000 people were displaced, lost, or killed within a short time. After the tsunami, the Government provided three types of houses for the victims (temporary shelters, transitional houses, and permanent houses). The authors conducted several field surveys and interviews in the damaged area to investigate the recovery conditions, and obtained dataset, which had been collected for 13 months since December 2004 by Rebuilding and Development Agency. It shows the construction status of transitional house and permanent house in the damaged areas. This paper demonstrates recovery curves for the transitional houses and the permanent houses. With the aim of constructing post-earthquake recovery curves for Sri Lanka, the factors of time (months) and completion ratio of building construction are used. The obtained curves quantitatively clarify the regional differences in the completion dates and processes of construction. The proposed quantitative methodology will be used for other damaged countries due to the 2004 Indian Ocean Tsunami. It means that this kind of analysis is essential for investigating post-disaster recovery process because it enables comparative studies of urban/rural planning among different types of post-disaster recovery processes throughout the world.


Nature ◽  
2008 ◽  
Vol 455 (7217) ◽  
pp. 1228-1231 ◽  
Author(s):  
Kruawun Jankaew ◽  
Brian F. Atwater ◽  
Yuki Sawai ◽  
Montri Choowong ◽  
Thasinee Charoentitirat ◽  
...  

2006 ◽  
Vol 15 (1) ◽  
pp. 163-177 ◽  
Author(s):  
Havidan Rodriguez ◽  
Tricia Wachtendorf ◽  
James Kendra ◽  
Joseph Trainor

2011 ◽  
Vol 11 (1) ◽  
pp. 173-189 ◽  
Author(s):  
A. Suppasri ◽  
S. Koshimura ◽  
F. Imamura

Abstract. The 2004 Indian Ocean tsunami damaged and destroyed numerous buildings and houses in Thailand. Estimation of tsunami impact to buildings from this event and evaluation of the potential risks are important but still in progress. The tsunami fragility curve is a function used to estimate the structural fragility against tsunami hazards. This study was undertaken to develop fragility curves using visual inspection of high-resolution satellite images (IKONOS) taken before and after tsunami events to classify whether the buildings were destroyed or not based on the remaining roof. Then, a tsunami inundation model is created to reconstruct the tsunami features such as inundation depth, current velocity, and hydrodynamic force of the event. It is assumed that the fragility curves are expressed as normal or lognormal distribution functions and the estimation of the median and log-standard deviation is performed using least square fitting. From the results, the developed fragility curves for different types of building materials (mixed type, reinforced concrete and wood) show consistent performance in damage probability and when compared to the existing curves for other locations.


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