Journal of the Korean Association of Geographic Information Studies (한국지리정보학회지)

The Korean Association of Geographic Information Studies (한국지리정보학회)
권호 표지
DOI QR코드

DOI QR Code

Changes in Floating Population Distribution in Jeju Island Tourist Destinations Before and After COVID-19 Using Spatial Big Data Analysis

공간 빅데이터 분석을 활용한 COVID-19 전후 제주도 관광지의 유동인구 분포 변화

  • Heonkyu Jeong (Dept. of Tourism Development, Jeju National University) ;
  • Yong-Bok Choi (Dept. of Tourism Development, Jeju National University)
  • 정헌규 (제주대학교 관광개발학과) ;
  • 최용복 (제주대학교 관광개발학과 )
  • Received : 2023.11.21
  • Accepted : 2024.01.26
  • Published : 2024.03.31
Download PDF
⟨ Previous Next ⟩

Abstract

This study aims to identify the trend of changes in tourist floating population before and after COVID-19 in major tourist destinations in Jeju Island through spatial analysis. Seongsan-eup and Andeok-myeon in Jeju Island were selected as the research area, and the research period was set at 1 year before and 2 years after the COVID-19 outbreak. For the analysis, mobile floating population data was refined and processed to calculate floating population distribution and floating population increase/decrease data. This was converted into spatial data and an overlay analysis was performed with location data of major tourist attractions. As a result of the analysis, it was confirmed that the floating population of indoor tourist attractions and small facilities decreased immediately after COVID-19, and that in open coastal areas or large facilities, the floating population decreased less or actually increased. In conclusion, in tourism development, it is necessary to identify changes in floating population according to the characteristics of tourist facilities, and it is necessary to develop tourism facilities and strategies that can respond to risk situations such as pandemics when developing tourist destinations.

본 연구는 제주도의 주요 관광지별 COVID-19 전후 관광객 유동인구 변화 추세를 공간분석을 통하여 확인하고, 이를 통하여 관광객 유동인구 패턴 변화에 대한 이해를 하고자 한다. 제주도의 성산읍과 안덕면을 연구지역으로 선정하였으며, 연구기간은 COVID-19 발생전 1년과 발생후 2년으로 설정하였다. 공간분석을 위하여 이동통신 유동인구 데이터를 정제 및 가공하여 유동인구 분포와 유동인구 증감 데이터를 산출하였으며, 이를 공간데이터화 하여 주요 관광지의 위치데이터와 중첩분석을 실시하였다. 분석결과 실내 관광지와 소규모 시설은 COVID-19 직후 유동인구가 감소하였으며, 개방된 해안지역 또는 대규모 시설의 경우 유동인구 감소가 적거나 오히려 유동인구가 증가한 것으로 확인되었다. 결론적으로 관광개발에서 관광시설 특성에 따른 유동인구의 변화를 파악할 필요가 있으며, 관광지 개발시 팬데믹과 같은 위험상황에 대응할 수 있는 관광시설 및 전략의 개발이 필요하다.

Keywords

Acknowledgement

본 연구는 2023년도 제주대학교 교원성과지원사업에 의하여 연구되었음.

References

  1. Baek, G.H. and J. Lee. 2016. Analysis of activity patterns of tourists in Jeju using big data: Using smart cell data. The Bank of Korea 121-245.
  2. Cho, H.W., D.S. Kim and S.S. Lee. 2022. Examining the characteristics of floating population distribution in the urbanized area of Daegu Metropolitan City before and after COVID-19 : An application of hotspot analysis. Journal of Korea Planning Association 57(2):5-17.
  3. Choi, K.E. 2021. International tourism trends and future challenges before and after COVID-19. Korea Tourism Policy 86:10-20.
  4. Choi, S.W. 2020. Tourism development and future prospects in the post-corona era. Korea Tourism Organization 2:1-13.
  5. Jang, Y.H., Y.J. Lee and J.H. Park. 2020. Records of COVID-19 examined through big data (1) - Focusing on news articles and floating population data -. KRIHS Issue Report 16:1-16.
  6. Jeju Tourism Organization. 2023. The market trends and statistics. https://ijto.or.kr/korean/Bd/list.php?btable=pds&lcate=1. (Accessed November 6, 2023).
  7. Jeon, S.E. and D.B. Shin. 2018. A study on the agent based infection prediction model using space big data -focusing on MERS-CoV incident in Seoul-. Journal of the Korean Association of Geographic Information Studies 21(2):94-106.
  8. Kang, H.J. 2008. Hot spot analysis: Basis of spatial analysis, utilization and understanding of local Moran's I and nearest neighbor analysis. Planning and Policy 324:116-121.
  9. Kim, B.R. and Y.S. Nam. 2023. A Study on the effect of tourism facilities' locations on tourists' visits : Using domestic floating population data. Journal of Tourism Enhancement 11(2):173-191.
  10. Kim, J.W. and B.K. Yoon. 2013. Theoretical background and domestic and international research trend of GIS in tourism. Journal of Tourism Sciences 37(10):137-162.
  11. Kim, M. and H.K. Kim. 2023. The effects of COVID-19 on public transportation demand: The case of Busan Metropolitan City. Journal of the Korean Association of Geographic Information Studies 26(3):1-11.
  12. Kim, Y.S. and H.J. Jin. 2021. Analysis for economic impacts of the tourism/culture and whole industry due to reduced inbound visitors after the COVID-19 outbreak. Journal of Tourism Sciences 45(3):33-53.
  13. Korea Culture and Tourism Institute. 2021. Impact of COVID-19 on the tourism industry and response measures. Korea Culture and Tourism Institute 1-299.
  14. Kwak, H.C., Song, J.Y., Eom, J.K. and K.T. Kim. 2018. A study on factors influencing floating population using mobile phone data in urban area. Journal of the Korean Society for Urban Railway 6(4):373-381.
  15. Kwon, T.I. and C.H. Lee. 2017. Empirical analysis study on big data utilization system in tourism field. Korea Culture and Tourism Institute 1-187.
  16. Lee, H. 2020. COVID-19 pandemic, changes and prospects for tourism travel. Future Horizon 48:16-23.
  17. Lim, H.J. and S.H. Park. 2020. Analysis of mobile spatial big data at Tama New Town. Journal of the Korean Cadastre Information Association 22(1):95-107.
  18. Min, K. and H. Lim. 2021. Tourism policy establishment plan using geographic information system and big data analysis system -Focusing on major tourist attractions in Incheon Metropolitan City-. Journal of the Korea Convergence Society 12(8):13-21.
  19. Ministry of Culture, Sports and Tourism. 2021. 2020 National Travel Survey. Ministry of Culture, Sports and Tourism 1-289.
  20. Oh, J.G., Heo, H.Y., Sim, G.W., Kim, T.G. and J.Y. Choi. 2017. Research on the actual status of national park visitors and analysis of usage patterns using telecommunication big data. Korea National Park Service 1-125.
  21. Park, Y.R. and Y. Kang. 2019. Estimation of flow population of Seoul walking tour courses using telecommunications data. Journal of Cadastre & Land Informatix 49(1):181-195.
  22. Shim, W.S., Choi, S.M. and C.S. Shim. 2018. Identifying major issues of tourism analysis using big data : Focused on mobile and credit card data. Journal of Tourism Studies 30(3):3-22.
  23. Son, H.J., Byun, S.H., Park, K.W., Kim, J.E. and T.W. Kim. 2023. Analysis of Drought Hotspot Areas Using Local Indicators of Spatial Association in the Nakdong River Basin. KSCE Journal of Civil and Environmental Engineering Research 43(2):175-185.
  24. Yoo, M.S. and D.J. Choi. 2019. An empirical study on the spatial effect of distribution patterns between small business and social-environmental factors. Journal of the Korean Association of Geographic Information Studies 22(1):1-18.