[논문]택시 이동 데이터 기반 COVID-19 확진자 수와 교통량 간의 상관관계 및 공간분석

전승배; 김건; 정명훈

doi:10.7848/ksgpc.2021.39.6.609

택시 이동 데이터 기반 COVID-19 확진자 수와 교통량 간의 상관관계 및 공간분석
Correlation and Spatial Analysis between the number of Confirmed Cases of the COVID-19 and Traffic Volume based on Taxi Movement Data 원문보기

한국측량학회지 = Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, v.39 no.6, 2021년, pp.609 - 618

전승배 (Dept. of Civil Engineering, Chosun University) , 김건 (Dept. of Civil Engineering, Chosun University) , 정명훈 (Dept. of Civil Engineering, Chosun University)

초록
AI-Helper

COVID-19의 확산과 피해는 대한민국 정부를 포함한 전 세계에 큰 영향을 주고 있다. 대다수 국가는 시민들 간의 접촉을 최소화하기 위해 이동과 집합에 제약을 두고 있으며, 이러한 정책들은 사회적 패턴에 새로운 변화를 가지고 왔다. 본 연구는 COVID-19가 미치는 사회적 영향 중 택시 운행에 대한 영향을 분석하기 위해 COVID-19 3차 대유행 초기에 수집된 대구광역시 택시 이동 데이터를 이용하여 도로 네트워크 규모의 교통량 데이터를 생성하였다. 이후 대구광역시의 확진자 데이터와 상관성 분석을 수행하였으며, 공간적 특성이 가지는 영향을 분석하기 위해 Local Moran's I를 적용하였다. 결과적으로, 전체 도로 네트워크의 택시 운행량과 확진자 수는 음의 상관관계(-0.615)를 나타내었고 이는 확진자 수의 증가에 따른 시민들의 이동 불안감이 반영된 것을 확인하였다. 또한, 본 연구에서는 도로 네트워크의 링크 기반으로 분석을 수행한 결과 도심 중심부의 상업 및 산업 지역은 음의 상관관계와 Local Morna's I의 값이 low-low로 cold spot을 확인하였으며, 병원 같은 의료기관 주변 및 공동주거지와 같은 공간적 특성을 가진 지역의 도로 네트워크는 high-high로 hot spot인 것을 확인하였다. 향후 이러한 분석이 COVID-19에 따른 정책 결정자들의 예방 대책에 활용될 수 있을 것이다.

Abstract ▼ AI-Helper

The spread and damage of COVID-19 are putting significant pressure on the world, including Korea. Most countries place restrictions on movement and gathering to minimize contact between citizens and these policies have brought new changes to social patterns. This study generated traffic volume data on the scale of a road network using taxi movement data collected in the early stages of the COVID-19 third pandemic to analyze the impact of COVID-19 on movement patterns. After that, correlation analysis was performed with the data of confirmed cases in Daegu Metropolitan City and Local Moran's I was applied to analyze the effect of spatial characteristics. As a result, in terms of the overall road network, the number of confirmed cases showed a negative correlation with taxi driving and at least -0.615. It was confirmed that citizens' movement anxiety was reflected as the number of confirmed cases increased. The commercial and industrial areas in the center of the city confirmed the cold spot with a negative correlation and low-low local Mona's I. However, the road network around medical institutions such as hospitals and spaces with spatial characteristics such as residential complexes was high-high. In the future, this analysis could be used for preventive measures for policymakers due to COVID-19.

주제어

표/그림 (10)

그림 Fig. 1. COVID-19 cumulative confirmed cases in Daegu Metropolitan City
그림 Fig. 2. Road network of Daegu Metropolitan City
그림 Fig. 3. The number of taxis traffic volume by date during the research period
그림 Fig. 4. System architecture
그림 Fig. 5. Four types of space clusters
그림 Fig. 6. Comparison of the number of COVID-19 confirmed cases and road network taxi traffic volume
그림 Fig. 7. The histogram of PCC on the road network
그림 Fig. 8. The results of spatial autocorrelation analysis on the PCC between the number of COVID-19 confirmed cases and taxi traffic volume
그림 Fig. 9. The spatial characteristics of hot spots
표 Table 1. The number of hot spots, households, and medical facilities based on administrative regions

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표제어: PCR

동의어: Packet Collision Rate

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