GEOG 331 - Environmental Data Science
Introduces fundamental concepts and tools central to the emerging field of Environmental Data Science. Satellites, environmental sensors, and citizen science networks collect a tremendous amount of geospatial data that offers unprecedented insight into the environment. The integration of computational tools, statistics, and an understanding of the earth system is essential for utilizing big data to understand environmental processes (e.g. climate change, food security). Topics covered include data provenance and reproducibility, data fusion, visualization, and statistical programing for environmental data. Students learn how to manipulate and analyze large climatic, ecological, and geospatial data sets using a statistical programing language. No prior programming experience is required.
Prerequisites: or None
Major/Minor Restrictions: None
Class Restriction: None
Area of Inquiry: Natural Sciences & Mathematics
Liberal Arts CORE: None
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