Journal cover Journal topic
Proceedings of the ICA
Journal topic
Volume 2
Proc. Int. Cartogr. Assoc., 2, 47, 2019
https://doi.org/10.5194/ica-proc-2-47-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Proc. Int. Cartogr. Assoc., 2, 47, 2019
https://doi.org/10.5194/ica-proc-2-47-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  10 Jul 2019

10 Jul 2019

Spatial Analysis to Identify Factors Affecting Residential Land Prices in Disaster Areas

Keiko Inagaki and Satoru Sadohara Keiko Inagaki and Satoru Sadohara
  • Yokohama National University, Japan

Keywords: multivariate spatial analysis, land price, residential location choice, Great East Japan Earthquake, tsunami

Abstract. On March 11, 2011, a catastrophic earthquake struck Japan’s Tohoku area, which faces the Pacific Ocean. In this study, a multivariate spatial analysis was conducted to analyse the factors affecting residential land prices in the disaster-stricken area using the Hedonic Price Method. For the analysis, we first, collected spatial data, including land price maps, tsunami damage area map, flood hazard map, landslide hazard map, railway map, zoning map, and public building map of Miyagi prefecture. Second, we examined the extent to which the damage caused by the tsunami inundation can influence land prices, in order to clarify the relationship between natural disasters and land price fluctuations. The results of the multivariate analysis concluded that the tsunami inundation affected the price of land, particularly after the Great East Japan Earthquake (2011) in Miyagi prefecture. Furthermore, the degree of the tsunami inundation and the distance from public housing constructed after the disaster influenced land price fluctuations after the earthquake. In other words, the human settlements have been affected by disaster damage and reconstruction plan. Present studies have demonstrated the residents’ attitudes towards housing location choices before and after the earthquake disaster. By improving the precision of the multiple regression analysis in the future, we will be able to utilize the experiences of previous disasters as lessons learnt for safety and sustainability, particularly Sustainable Development Goal 11: Make cities and human settlements inclusive, safe, resilient and sustainable.

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