Time series evaluation of re-urbanization in disaster area of large-scale tsunami in Japan by high-resolution satellite remote sensing

Hideki Hashiba; Masashi Sonobe

doi:10.1117/12.2325309

9 October 2018 Time series evaluation of re-urbanization in disaster area of large-scale tsunami in Japan by high-resolution satellite remote sensing

Hideki Hashiba, Masashi Sonobe

Author Affiliations +

Proceedings Volume 10790, Earth Resources and Environmental Remote Sensing/GIS Applications IX; 107900O (2018) https://doi.org/10.1117/12.2325309
Event: SPIE Remote Sensing, 2018, Berlin, Germany

Abstract

The 2011 tsunami caused by the Tohoku Region Pacific Offshore Earthquake caused severe damage. In particular, the city of Rikuzentakata, Iwate Prefecture, a coastal city in the Tohoku district, sustained enormous damage, and long-term revitalization process is in progress. For this disaster, several satellite observations and remote disaster investigations by aerial photography were conducted, and various damage situations were reported. Although there are many interpretations of images, few continuously evaluate the recovery process after the disaster. Here, land cover was investigated using image information observed time-sequentially by high-resolution satellite remote sensing. In addition, the re-urbanization process of the disaster area was evaluated from evaluation index values obtained from several types of filtering analysis. The distribution of debris caused by the tsunami, the change in the characteristics of the bare ground due to debris removal, and the characteristics of the land cover shape were quantitatively evaluated from the regularity and identity of the land cover distribution. In addition, the early stages of re-urbanization, which is still in progress, were effectively evaluated.

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Hideki Hashiba and Masashi Sonobe "Time series evaluation of re-urbanization in disaster area of large-scale tsunami in Japan by high-resolution satellite remote sensing", Proc. SPIE 10790, Earth Resources and Environmental Remote Sensing/GIS Applications IX, 107900O (9 October 2018); https://doi.org/10.1117/12.2325309

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