The Tohoku earthquake of March 11, 2011, caused very huge tsunamis and widespread devastation. Various very highresolution
satellites quickly captured the details of affected areas, and were used for disaster management. In this study,
very high-resolution pre- and post-event Geoeye-1 satellite images were used to identify damages. Change detection
procedure was used to obtain estimation from the damages. However based on the selected zone and the number of
categories selected for the change detection some variability was detected in the results. This paper analyses the effects of
these parameters on the change detection results and discuss about the amount of errors and also the correlation between
the results for different zones selection. It was observed that the amount of changes vary based on the selections and there
is no linear relation between the quantitative results. This issue was investigated through various examples using 2011
Tohoku, Japan earthquake with very high resolution satellite images.
The outputs obtained from satellite image processing generally presents various information based on the interpretation technique, selected objects for object based processing, precision of processing, the number and time of images used for this process. This issue should be managed well during a disaster management process based on satellite images. Very high resolution (VHR) optical satellite data are potential sources to provide detailed information on damage and geological changes for a large area in a short time. In this paper, we studied tsunami triggered area, which was caused on 11 March 2011 by Tohoku earthquake, using VHR data from GeoEye-1satellite images. A set of pre and post-earthquake images were used to perform visual change analysis through comparison of these data. These images include the data of the same area before the disaster in normal condition and after the disaster which caused changes and also some modification imposed to that area. Upon occurrence of a disaster, the images are used to estimate the extent of the damage. Then based on disaster management criteria and the needs for recovery and reconstruction, the priorities for object based classification indexes are defined. In post-disaster management, they are used for reconstruction and sustainable development activities. Finally a classified characteristic definition has been proposed which can be used as sample indexes prioritization criteria for disaster management based on satellite image processing. This prioritization criteria are based on an object based processing technique and can be further developed for other image processing methods.
One of the main objectives of image processing is to optimize visualization of particular thematic dataset. The
processing methodology and strategy are very different from broadband image processing in many aspects. This strategy
highly depends on the application and its objectives. For natural disasters such as earthquakes and tsunamis which affect
a large area, the data obtained from satellite image processing can be utilized. The data can be used for disaster
management for rescue and relief plan during disaster and disaster preparedness for future disasters. In order to meet
objectives of disaster management, it is normally required to have a complete information system. The type of disaster
may also dictate the type of processing and interpretation technique of images. This paper reviews the methods of
satellite image processing and also the disaster management requirements. Based in these two issues the advantages and
limitations of image processing methods have been discussed considering important natural disasters.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.