Environmental Analytics

Catalog description

Environmental analytics concerns the quantitative analysis of environmental data in its non-spatial, spatial, and temporal dimensions, along with the assessment of quality indicators such as information redundancy, the accuracy and precision of models, and data uncertainty. Methods and techniques for environmental analytics are typically based on probability, stochastic modelling, and statistics as well as information science (inclusive of Geographic Information Systems and machine learning), though they take a more practical approach to the analysis and modeling of environmental processes. Applications include biophysical domains (e.g., agriculture, natural resources, ecology, air quality) as well as socioeconomic domains (e.g., epidemiology, health care, food systems, environmental planning). In this introductory course, students will work on case studies in both domains to illustrate the different facets of environmental problem solving. Co-convenes with ENSC 474 . Level: Graduate