Volume III-8
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., III-8, 35-42, 2016
https://doi.org/10.5194/isprs-annals-III-8-35-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., III-8, 35-42, 2016
https://doi.org/10.5194/isprs-annals-III-8-35-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

  07 Jun 2016

07 Jun 2016

ESTIMATION OF DAMAGED AREAS DUE TO THE 2010 CHILE EARTHQUAKE AND TSUNAMI USING SAR IMAGERY OF ALOS/PALSAR

Pertiwi Jaya Ni Made, Fusanori Miura, and A. Besse Rimba Pertiwi Jaya Ni Made et al.
  • Yamaguchi University, Graduate School of Science and Engineering, Disaster Prevention System Engineering, Ube City, Yamaguchi Prefecture 755-0097, Japan

Keywords: Damaged Areas Estimation, SAR Imagery, ALOS/PALSAR, the 2010 Chile Earthquake and Tsunami

Abstract. A large-scale earthquake and tsunami affect thousands of people and cause serious damages worldwide every year. Quick observation of the disaster damage is extremely important for planning effective rescue operations. In the past, acquiring damage information was limited to only field surveys or using aerial photographs. In the last decade, space-borne images were used in many disaster researches, such as tsunami damage detection. In this study, SAR data of ALOS/PALSAR satellite images were used to estimate tsunami damage in the form of inundation areas in Talcahuano, the area near the epicentre of the 2010 Chile earthquake. The image processing consisted of three stages, i.e. pre-processing, analysis processing, and post-processing. It was conducted using multi-temporal images before and after the disaster. In the analysis processing, inundation areas were extracted through the masking processing. It consisted of water masking using a high-resolution optical image of ALOS/AVNIR-2 and elevation masking which built upon the inundation height using DEM image of ASTER-GDEM. The area result was 8.77 Km2. It showed a good result and corresponded to the inundation map of Talcahuano. Future study in another area is needed in order to strengthen the estimation processing method.