Earticle

초록

영어

With the upcoming era of the 4th Industrial Revolution, big aata has been constructed in various field. Especially in transport sector, tremendous passenger and vehicle trips are collected as a navigation big data. Through navigation data, previous spotted traffic volume and speed data contribute to establish traffic volume and speed data in national level. Established transport raw data in national level lead to various processed data such as mobility data, carbon dioxide(CO2), air pollutants etc. This research utilize geographically weighted regression model in order to analyze correlation between area type (residential and business area) and air pollutants (CO2, CO, PM-10, NOX, VOCs) in the city of Seoul. The research outcome describes low correlation between environmental indicators corresponding to navigation data related to vehicle trip and area type (residential and business area). Therefore, a following study is required to analyze correlation between environmental indicators corresponding to transport navigation data and socio-economic indicators rather than spatial features. Moreover, a comparative study between general regression model and geographically weighted regression model is necessary for in-depth analysis.

목차

Abstract
1. 서론
1.1 연구의 배경 및 목적
1.2 연구의 범위 및 방법
1.3 선행연구검토
2. 본론
2.1 환경지표의 산출(Kim, Sohn & Kang, 2016)
2.2 분석방법론
2.3 분석결과
3. 결론
REFERENCES

저자

• 황기연 [ Hwang, Kee-Yeon | 홍익대학교 도시공학과 교수 ]
• 김관용 [ Kim, Kwan-Yong | 홍익대학교 도시계획과 박사수료, 한국교통연구원 국가교통빅데이터사업단 ] Corresponding Author

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