Over the Christmas break I undoubtably watched numerous documentaries surrounding the Boxing Day Tsunami in 2004, this Boxing Day marked the 10th anniversary of this catastrophic event. I noticed throughout documentaries they used aerial images and satellite data to illustrate the changes to the locations and also show the magnitude and location of destruction. I decided to research how remote sensing was directly used in this event and found an amazing article by Matsuoka and Yamazaki (2006). Their paper highlighted the use of remote sensing technologies in disaster management, and was published as part of the Asia Conference on Earthquake Engineering in 2006. Urban classification and vegetation were monitored. Terra- ASTER and NDVI images were used to identify tsunami inundation areas comparing the pre-event and post- event images.
In recent years Asia has experienced several large scale earthquakes, damaging its infrastructure, which is most coastal areas (the ones affected by tsunamis) are weak. The Boxing Day tsunami was caused by an earthquake of the western cost of Sumatra measuring a magnitude of 9.0, (Matsuoka and Yamazaki, 2006). Over 280,000 people were killed according to governments and the UN (Relief Web, 2005). See Figure 1 for aerial image of devastation.
According to Matsuoka and Yamazaki, (2006) ground surveys were conducted in Thailand to assess the damage to urban structures, these ground observations were used to validate the damage characteristics identified by the satellite imagery. The combination of observed and satellite images was named ‘Panoramic-VIEWS’, the data was then shared and analysed. The availability of ground truth data means that the satellite images are separated into classes under Supervised Classification, to illustrate the urban areas (Campbell and Wynne, 2011). The urban areas were then located on the satellite image and the rehabilitation of the area was monitored. Thematic maps of NDVI (vegetation), NDSI (soil) and NDWI (water) showed the destruction to the area using infra-red and can be seen in Figure 2 below. The higher the value according to the equation in Figure 3, the more likely it is covered with the respective vegetation, soil or water (Matsuoka and Yamazaki, 2006).
Also, quite fittingly the earthquake in Haiti occurred 5 years TODAY, so I have included images from the USGS (2015) showing comparisons of Haiti just before the earthquake and now 5 years on in Figure 4 below. There are very few differences between the two images, showing how quickly the area has recovered. They are both true colour composite images. so they detail what we can naturally see, the images have high spatial resolution. Figure 5, also shows a more focussed image, of before and after, and again, there is very little difference, however the 2015 image is clearer and could be said to have a high spatial resolution as more details can be depicted from the image (Campbell and Wynne, 2011).
BBC. (2015) Boxing Day Tsunami: A Survivor’s Story. [Online] Available at: http://www.bbc.co.uk/news/uk-30537152 (Accessed: 5 January 2015)
Campbell, J. B. and Wynne, R. H. (2011) Introduction to Remote Sensing. 5th edn. New York: The Guilford Press.
Relief Web. (2015). South Asia: Earthquake and Tsunami – Dec 2004 [Online] Available at: http://reliefweb.int/disaster/ts-2004-000147-idn (Accessed: 5 January 2015)
USGS. (2015). Port au Prince before and after. [Online] Available from: http://gallery.usgs.gov/photos/06_10_2010_vaq1TGf66N_06_10_2010_1#.VLeSqVpqa8q (Accessed: 12 January 2015)
Yamazaki, F., & Matsuoka, M. 2006. Remote sensing technologies for earthquake and tsunami disaster management. In Proceedings of the second Asia Conference on Earthquake Engineering, Manila, Philippines. pp. 1-20.