GISC4381 - Spatial Data Science

GISC 4381 Spatial Data Science (3 semester credit hours) Introduces data science for spatial problem solving. Course topics cover all five stages of the data science life cycle: capture, maintain, process, analyze, and communicate, with emphases on spatial data. Spatial data is critical to solving problems or developing applications for energy planning, emergency management, environmental sustainability, public health, smart city, public safety, business logistics, autonomous vehicles, ecological conservation, and many other problem domains. Besides an overview of cyberGIS and spatial semantics web, the course discusses the essential characteristics of spatial data, types of spatial problems, relevant spatial concepts, and key spatial data science methods. Computer lab exercises offer hands-on practices on spatial data analytics with both structured data from government statistics or systematic data collections as well as unstructured data from social media, location-aware mobile devices (such as smart phones), and/or web scrapping. This course aims to help students develop fundamental knowledge and basic skills to ask spatial questions, find, process, and analyze spatial data, solve spatial problems, and communicate their findings. (3-0) Y