Springer Textbooks in Earth Sciences, Geography and Environment R Applications Sciences

The book provides insights to the various approaches to Earth-related data analysis, starting from data preparation and validation, exploratory data analysis, linear regression, and going through time series decomposition, modeling, and prediction. This textbook helps to understand the real Earth data with the practical application of many handy R tools and techniques. R language and thousands of R packages can be used to solve the most sophisticated scientific problems. The book provides insights to the various approaches to Earth-related data analysis, starting from data preparation and validation, exploratory data analysis, linear regression, and going through time series decomposition, modeling, and prediction. In addition, the book introduces machine learning techniques and their application to some real problems. Along with a profound explanation of the datasets and theoretical considerations of the methods, the book offers a way of solving practical problems lying at the frontline of modern data analysis in physical geography, soils, and climate science.