Tsunami shelter location allocation by applying a heuristic algorithm to residential and floating population data

Junsu Bae, Hong Gyoo Sohn, Joon Heo, Sangkyun Kim, Mi Kyeong Kim

Research output: Contribution to conferencePaper

Abstract

Recently, the Korean Peninsula is no longer a safe area for tsunamis because of frequent earthquakes in neighboring countries. Tsunami can cause heavy casualties, and in order to reduce heavy casualties, seismic tsunami shelters must be selected in the right place. Various studies have been conducted on the location of tsunami shelters, but most studies have conducted the study based on the population data of residential areas. Therefore, in this study, the location of shelters was selected using floating population data and residential population data, and the results were compared and analysed. Resident population data is based on approximately 500 people, and the floating population data is based on by time average data of 50m grid on every month. The data of the floating population data was used at 6 pm in July, where the largest number of the floating population is located in the study area. Guideline for the resident evacuation plan of tsunami in Korea requires that the tsunami shelter preferably be located within 600m of the shoreline and above 10m above sea level, so this study conducted a study according to the guideline. Genetic algorithms have been used to allocate shelter location and genetic algorithms have already been applied to many shelter location- allocation studies. Genetic algorithm is algorithms based on the law of survival of the fittest. Parent generation generate the next generation with genes that are more suitable for achieving objective functions through selection, crossover and selection processes. The objective function of the genetic algorithm was selected as the number of evacuees, and the elitist preserving selection method and the roulette wheel selection method were used as selection operators and the onepoint crossover was used as the crossover operator. As a result, the results of using floating population data showed that shelters were also allocated around tourist sites that were not selected when using residential population data. However, in some areas, it was confirmed that the location of the shelter was not selected due to the area of 10m below sea level. Later studies will include buildings with seismic design, which will be used to select shelters at more appropriate locations.

Original languageEnglish
Publication statusPublished - 2020 Jan 1
Event40th Asian Conference on Remote Sensing: Progress of Remote Sensing Technology for Smart Future, ACRS 2019 - Daejeon, Korea, Republic of
Duration: 2019 Oct 142019 Oct 18

Conference

Conference40th Asian Conference on Remote Sensing: Progress of Remote Sensing Technology for Smart Future, ACRS 2019
CountryKorea, Republic of
CityDaejeon
Period19/10/1419/10/18

All Science Journal Classification (ASJC) codes

  • Information Systems

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    Bae, J., Sohn, H. G., Heo, J., Kim, S., & Kim, M. K. (2020). Tsunami shelter location allocation by applying a heuristic algorithm to residential and floating population data. Paper presented at 40th Asian Conference on Remote Sensing: Progress of Remote Sensing Technology for Smart Future, ACRS 2019, Daejeon, Korea, Republic of.