Long term transformation of building locations in 8 villages along the Sanriku coast, tsunami-prone area
DOI:
https://doi.org/10.7480/iphs.2024.1.7648Abstract
The Sanriku coastal region of Iwate Prefecture was severely damaged by the Great East Japan Earthquake of 2011. The area has been repeatedly hit by tsunamis since the 1896 Meiji Sanriku Tsunami, the 1933 Showa Sanriku Tsunami, and the 1960 Chile Earthquake Tsunami, and is therefore called a "tsunami prone area" in prior research. However, this discourse has not been verified. In this study, we quantitatively analysed spatial changes in representative 8 villages along the Sanriku coast from the 1960s to 2022. Firstly, we traced aerial photographs taken since the 1960s on GIS, and created data on infrastructure such as roads and the location of all buildings in the villages. Secondly, all residential areas in the villages were categorized into 10 types according to their formation process and whether or not they were inundated by the Great East Japan Earthquake, and the number of buildings, building density, distance to fishing ports, and elevation were calculated to reveal spatial transformations. As a result, it became clear the eight villages can be roughly classified into two groups: those absorbed the increase in the number of buildings in the district from the 60s to the 00s through gentle slope sprawl and planned residential development, and those suffered significant damage from the Great East Japan Earthquake as residential areas spread within past flooded areas. On the other hand, even within the latter, changes contributed to the reduction of damage were identified, such as the concentration around stations and along national roads, and the relocation to higher ground was planned after the Showa Sanriku tsunami. These results support the discourse tsunami prone areas have been learning from past tsunamis. The study also succeeded in extracting a desirable change, sprawl on gentle slopes during the inter-disaster period, which had not been clearly visualized previously.
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Copyright (c) 2024 Kento Tawada, Shin Aiba
This work is licensed under a Creative Commons Attribution 4.0 International License.