Spatial Data Science and Applications (SCHI 2000)

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We live in a digital and data-intensive era, and geospatial technologies have penetrated every aspect of our lives, from digital maps and location services on our smartphones to managing city infrastructure, natural resources, and the environment. The principal purpose of Spatial Data Science (SDS) is to find patterns within massive spatial data and solve data-intensive and location-based problems facing people almost daily. This course primarily aims to familiarize students with the basic concepts of spatial thinking, geospatial technologies, AI and Machine Learning, and cloud-based platform used to create a Digital Earth. It is an introductory course that focuses on how geospatial data is visualized, explored, and analyzed in digital formats. This course is intended to equip students with the basic skills to locate, gather, and use spatial data for predictive analysis, pattern detection and clustering, decision-making with location-enabled data, etc. This course also provides several case studies for a deeper understanding of how spatial data can be used to monitor, assess, and predict climate change, food and energy security, water and air quality, and public health (e.g. the spread of COVID-19).

Spatial Data Science and Applications (SCHI 2000) is being offered in Spring 2023. For more information, please contact Profesor Susan Pan.