Speaker Bio & Abstract

Weigang Yan Senior Data Scientist
Cambridge City Council
United Kingdom

BiographyWeigang Yan is the senior data scientist in Cambridge City Council, UK. She is leading the data science research to drive the data driven decision making and policy in the council. Yan has over 10 years of experience on knowledge research, especially in the field of environmental sciences. She has been developing research in data science on environmental sciences and sustainability and the concept of environmental datacosm for better decision making.AbstractWeigang Yan, Matthew Magrath | Cambridge City Council Trees in towns and cities provide pleasant, healthy and refreshing environment to live, work and play. Growing evidence shows urban forests not only provide regulating ecosystem services to remove pollutants, air condition urban land and alleviate storm water, but also have impacts on social economics, human health and wellbeing. Research has been done to explore the correlation between tree canopy size and various social economics factors and wellbeing, and environmental attributes. The correlation has strong implications on retaining or increasing canopy cover in urban planning. However, it is not clear what factors are key to be associated impact on tree canopy size and how aggregate of these multiple factors is related to tree canopy size. Identifying the key factors associated with tree canopy size can become the foundation of predictive models and new index system for policy making of tree preservation and urban planning. In this study, we investigate the relationship between tree canopy cover and aggregates of factors including Index of Multiple deprivation(IMD), Specific public health key performance index, house prices, life expectancy, educational achievement, air quality, surface water flooding, urban heat island at Cambridge city on the basis of wards, through spatial multiple regression modelling. The findings show positive relationship between the tree canopy size and social economic status. The metric selected can be used to implicate where trees can be planted in the city. Trees as an cost-effective intervention can enhance our life quality.