인구 추정을 기반으로 한 인구집단별 폭염 취약지역 분포 예측에 관한 연구
A Study on Estimating Heat Vulnerable Areas by Demographic Group based on Population Estimates
0
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
본 연구는 다가올 미래 폭염의 영향을 최소화하기 위해 폭염 적응전략 수립에 선행하여 유아인구, 생산가능인구, 고령인구의 세 인구집단별 폭염 취약지역의 공간적 분포를 예측하였다. 이에 먼저 기계학습 모형과 설명가능한 기계학습 모형을 통해 인구집단별 미래 인구값을 추정하고, 추정값을 해석하였다. 인구 추정 결과, 세 인구집단 모두 2042년까지 지속적으로 감소할 것으로 전망되었다. 인구집단별 인구 추정값과 미래 폭염일수를 중첩하여 도출한 미래 폭염 취약지역은 세 인구집단 모두에 대해 주로 내륙지역에 위치할 것으로 예측되었다. 인구집단별 폭염 취약지역의 미래 공간적 분포를 예측한 결과, 국토의 동부보다는 서부가 취약하며, 유아인구에 대한 폭염 취약지역은 서울과 수도권 남부, 대도시 지역 등에서, 생산가능인구에 대한 폭염 취약지역은 서울, 수도권 남부, 충청권 등에 위치할 것으로 나타났다. 정확한 인구 추정 분석은 미래 폭염의 영향에 사전적·효과적으로 대처하는 데 필수적인 단계로서, 이를 통해 폭염의 잠재적 영향을 사전에 예측하고 정책의 우선순위를 설정하는 데 기여할 수 있다.
Abstract
In order to minimize the impact of future heat waves, this study predicts the spatial distribution of heat vulnerable areas by three demographic groups: young population, working-age population, and old population, prior to establishing heat wave adaptation strategies. First, the future population values of each demographic group were estimated through machine learning and explainable AI, and the estimates were interpreted. The population estimates showed that all three demographic groups are expected to continue to decline until 2042. The future heat wave vulnerable areas, derived by overlaying population estimates and future heat wave days by demographic group, were predicted to be mainly inland for all three demographic groups. The spatial distribution of future heat vulnerable areas by demographic group showed that the western part of the country is more vulnerable than the eastern part, and that the heat vulnerable areas for the young population will be located in Seoul, the southern part of the Seoul metropolitan area, and metropolitan areas, while the heat vulnerable areas for the working-age population will be located in Seoul, the southern part of the Seoul metropolitan area, and the Chungcheongbuk-do region. Accurate population estimation analysis is an essential step in proactively and effectively dealing with the effects of future heat waves, and the results of this study can be used as a basis for heat adaptation policies.
참고문헌 (45)
- Abate R, "Climate change and indigenous peoples: The search for legal remedies" (2013), Edward Elgar Publishing
- Ahn JH, "Explainable AI, Dissecting AI", ~ (2020)
- Bae MK, "Analysis on the spatial relationship between the residential area of the vulnerable groups and the hazardous area during the heat wave", Journal of Environmental Policy and Administration, 28(3), pp.243~280 (2020)
- Chakraborty TC, "Residential segregation and outdoor urban moist heat stress disparities in the United States", One Earth, 6(6), pp.738~750 (2023)
- Chan EYY, "A study of intracity variation of temperaturerelated mortality and socioeconomic status among the Chinese population in Hong Kong", J Epidemiol Community Health, 66(4), pp.322~327 (2012)
- Chi G., "Can knowledge improve population forecasts at subcounty levels?", Demography, 46(2), pp.405~427 (2009)
- Chi G, "Small-area population forecasting : Borrowing strength across space and time", Population, Space and Place, 17(5), pp.505~520 (2011)
- Chi G, "Population projection accuracy : The impacts of sociodemographics, accessibility, land use, and neighbour characteristics, Population", space and place, 24(5), pp.e2129~ (2018)
- Choi C, "Spatial-temporal patterns and recent changes of tropical night phenomenon in South Korea", Journal of the Korean Geographical Society, 40(6), pp.730~747 (2005)
- Choi KH, "A Study on Legislation and Policy for Support of Climate Change Vulnerable Class", Ewha Law Journal, 22(3), pp.227~252 (2018)
- Choi YS, "An analysis on the spatial patterns of heat wave vulnerable areas and adaptive capacity vulnerable areas in Seoul", Journal of Korea Planning Association, 53(7), pp.87~107 (2018)
- Climate change and economic growth: Evidence from the last half century, "Dell M", National Bureau of Economic Research, ~ (2008)
- Deschênes O, "Climate change, mortality, and adaptation : Evidence from annual fluctuations in weather in the US", American Economic Journal : Applied Economics, 3(4), pp.152~185 (2011)
- Díaz J, "Heat waves in Madrid 1986-1997 : effects on the health of the elderly", International archives of occupational and environmental health, 75, pp.163~170 (2002)
- Risks from climate change to indigenous communities in the tropical north of Australia, "Green D", ~ (2009)
- Hajat S, "Mortality displacement of heat-related deaths : a comparison of Delhi, Sao Paulo, and London", Epidemiology, 16(5), pp.613~620 (2005)
- Hilario L, "Forecasting urban population distribution of Iloilo City using GIS and spatial autocorrelation models, The International Archives of the Photogrammetry", Remote Sensing and Spatial Information Sciences, 46, pp.185~192 (2021)
- Hyerim C, "Heat Wave Disaster Vulnerability Assessment and Identification of Vulnerable Area Characteristics Considering Medical Vulnerability", The Korea Spatial Planning Review, 110, pp.63~79 (2021)
- Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the IPCC, "IPCC", ~ (2007)
- Climate Change 2014: Synthesis Report, "IPCC", ~ (2014)
- Climate Change 2023: Synthesis Report, "IPCC", ~ (2023)
- Jesdale BM, "The racial", ethnic distribution of heat risk-related land cover in relation to residential segregation, 2013, pp.121(7), 811~817
- Jung J, "Study on the vulnerability regarding high temperature related mortality in Korea", Journal of the Korean geographical society, 49(2), pp.245~263 (2014)
- Kim DW, "Characteristics of heat wave mortality in Korea", Atmosphere, 24(2), pp.225~234 (2014)
- Kim K, "Assessment of heat wave vulnerability in busan using the IPCC climate change vulnerability assessment framework", The Korea Spatial Planning Review, 104, pp.23~38 (2020)
- Kim SH, "Environmental protection, social welfare, and climate resilience: Addressing heat illness mortality in elderly populations", Journal of Climate Change Research, 15(3), pp.355~371 (2024)
- Kim SJ, "Influencing Factors of Commuting Time by Income Class : A Machine Learning Approach", Journal of the Korea Planning Association, 58(6), pp.85~99 (2023)
- Kim SY., "Research the latest trends in small area estimation techniques", ~ (2019)
- Kim TH, "Analyzing the relationship between health damage caused by heat wave and socioeconomic factors", Crisisonomy, 12(5), pp.67~78 (2016)
- Koo YS, "Study on the improvement of adaptation ability by vulnerability analysis of heat wave-The case of Busan Metropolitan City", J. Korean Reg. Dev. Assoc, 27(5), pp.331~348 (2015)
- Lee JJ, "A study on the employee turnover prediction using XGBoost and SHAP", The Journal of Information Systems, 30(4), pp.21~42 (2021)
- Lee NY, "Effect of Climate Change on Mortality Rate Analysis of Vulnerable Populations", Health and Social Welfare Review, 34(1), pp.456~484 (2014)
- Lee S, "Economic Valuation of Statistical Life in Life Loss of Heat Waves Attributed to the Climate Change", Korean J. Health Econ. Policy, 22, pp.51~78 (2016)
- Climate change health impacts and adaptation measures, "Ministry of Environment", ~ (2005)
- Mitchell BC, "Exploring the relationship between residential segregation and thermal inequity in 20 US cities", Local Environment, 23(8), pp.796~813 (2018)
- Oh PR, "A study on the neighborhood unit theory and the actual condition analysis of the neighborhood unit plan : Focused on the neighborhood unit plan in urban master plans", Seoul Studies, 13(4), pp.1~20 (2012)
- Park J, "Analysis of heat-related illness and excess mortality by heat waves in South Korea in 2018", Journal of the Korean Geographical Society, 55(4), pp.391~408 (2020)
- A study of environmental welfare policy for climate and environmentsusceptible populations (I), "Park J", Korea Environ. Inst, 1398~1632 (2013)
- Park JE, "A study on human damage due to heat wave by region", Journal of the Korean Society of Hazard Mitigation, 16(1), pp.103~109 (2016)
- Perry CA, "The neighborhood unit formula", Urban Housing, 94~109 (1966)
- Raftery AE, "Probabilistic population forecasting : Short to very long-term", International Journal of Forecasting, 39(1), pp.73~97 (2023)
- A Projected Population Exposed to Future Hot Weather Events Considering the Korean Society with Low Birth Rate and Rapid Aging:For Supporting Regional Policy Measures, "Sim CS", ~ (2019)
- Wilson T, "Methods for small area population forecasts : State-of-the-art and research needs", Population Research and Policy Review, 41(3), pp.865~898 (2022)
- Woo KS, "High temperaturerelated mortality in Korea : a meta-analysis of the empirical evidence", Health and Social Welfare Review, 39(2), pp.10~36 (2019)
- Yoon KJ, "A Study on the Improvement of Heat Wave Adaptation through Questionnaire Survey on the Heat Wave Cognition in Busan", The Korea Spatial Planning Review, 107, pp.79~92 (2020)