Introduction to environmental data science Introduction to Environmental Data Science focuses on data science methods in the R language applied to environmental research with sections on exploratory data analysis in R including data abstraction transformation and visualization; spatial data analysis in vector and raster models; statistics & modelling ranging from exploratory to modelling considering confirmatory statistics and extending to machine learning models; time series analysis focusing especially on carbon and micrometeorological flux; and communication. Introduction to Environmental Data Science. It is an ideal textbook to teach undergraduate to graduate level students in environmental science environmental studies geography earth science and biology but can also serve as a reference for environmental professionals working in consulting NGOs and government agencies at the local state federal and international levels