Resettlement Area Detection Model
Description
A Resettlement Area Detection (RAD) model is described to help local governments in depopulating regions evaluate candidate areas for post-disaster relocation. On this occasion, I have developed a method that sources annual population data for the past ten years and combined it with geographic features to compare population growth and population decline areas through a geographic lens to characterize population growth areas and enable the detection of urban structures likely to enable sustained population growth after resettlement. The method assumes that resettlement is a small part of a larger urban redevelopment and reconstruction scheme which together can generate sufficient movement of people into new relocation sites. In addition, the method proved that Tohoku-affected coastal areas with the potential for future population growth are: (1) In proximity to the regional city, (2) have accessible and conglomerate built-up areas closely connected to the main highway, and (3) are surrounded by farmlands which provide a large cohort of the population with sustained livelihood options. Data for the elaboration of this method can be found here.
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Steps to reproduce
First, annual population census data was collected from 20 municipal areas affected by the 2011 Great East Japan Earthquake; second, demographic trends were subsequently identified before (2000-2011) and after (2012-2021) the event; third, population growth areas before the disaster (group 1) and after (group 2) were compared against population decline areas before the disaster (group 3) and after the disaster (group 4); fifth, geographic features were integrated in the dataset to effectively explore population and geographic feature relationships aiming to find descriptive results which can then help to identify municipal sub-areas that are likely going to experience population growth after a large planned investment; sixth, I identified urban structures tied to geographic features and analyzed a municipal area that had experience extensive damage during the disaster event; seventh and last, I extracted urban structures in that area demonstrating how to identify these urban features and where to find them in other peri-urban municipal districts.