运用决策树方法探索健康与福祉结果的影响因素：以伦敦地方行政单位为例

摘要

Urban health, including physical health and wellbeing, has gained global a ention as cities prioritize policies that promote healthier living. This study answers one central question: what are the health determinants resulting in diff erent health outcomes throughout a city? It seeks to identify critical determinants of underperforming health and wellbeing status from variables related to urban health. Using a case study based in London, this study applies a decision-tree model approach to identify determinants from three dimensions, i.e. environment, socioeconomics, and urban planning and design, to obtain the relative importance of these health and wellbeing determinants. This study bridges the gap between cutting-edge data science methods and urban health research, providing urban planners and decision-makers with data-driven evidence and a new tool to shape a healthier city.

牛海沣

副研究员

英国剑桥大学土地经济系副研究员，欧盟Horizon 2020资助项目Emotional Cities空间分析研究员。主要研究兴趣包括城市大数据挖掘、空间数据科学、地理可视化、城市感知和城市动态模拟，特别是关注如何通过结合机器学习、人工智能和城市大数据来更好地支持城市规划、政策制定和智能管理。