Understanding the social-ecological complexity of urban ecosystems with big data and spatial methods
Chair: Weiqi Zhou
Co-chair: Kirsten Schwarz
Cities are highly heterogeneous in space, both socially and ecologically. Quantifying such heterogeneity, especially the interactions between social and ecological complexity, remains a grand challenge. With recent advances in data acquisition and data mining, high spatial and temporal resolution remotely sensed imagery, social media big data, area of interest (AOI) and point of interest (POI) data, to name just a few, have been increasingly used to understand the social and ecological complexity of cities.
This session aims to bring together recent advances in data and methods that can be applied to understand the social and ecological complexity, and their interaction of cities. We welcome talks focus on new data, new methods, as well as their applications and case studies. The topics of the session include but are no limited to: (1) new types of data that can be used to quantify the fine-scale social and ecological complexity of cities and their dynamics; (2) methods and tools that can be used to analyze, visualize, and distribute these data; and (3) applications and case studies of big data on understanding the social-ecological complexity of urban ecosystems.