Abstract
Population recovery process after a disaster is influenced by many factors in different spatial scales. In this paper, to analyze affectors in various spatial scales in recovery process, we focused on a spatial-temporal statistical model, which combines a spatial regression model and a time series model, considering that socio-economic data sets are not available on the same spatial and temporal scales. We applied the model to the Nagata Ward, Kobe City after the Hanshin-Awaji Earthquake, of which population recovery is relatively delayed compared to those in other damaged areas. As a result, the influence of variables in both local and large spatial scales are quantitatively identified, and it is shown that recovery policies both in large and local spatial scales are required.
