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KCI등재후보 학술저널

도시 빅데이터

Urban Big Data: Social Costs Analysis for Urban Planning with Crowd-sourced Mobile Sensing Data

In this study, we developed a method to quantify urban social costs using mobile sensing data, providing a novel approach to urban planning. By collecting and analyzing extensive mobile data over time, we transformed travel patterns into measurable social costs. Our findings highlight the effectiveness of big data in urban planning, revealing key correlations between transportation modes and their associated social costs. This research not only advances the use of mobile data in urban planning but also suggests new directions for future studies to enhance data collection and analysis methods.

1. Introduction

2. Method 1: social costs estimation

3. Method

4. Discussion and Concluding

References

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