Python is used in a wide range of geoscientific applications, such as in processing images for remote sensing, in generating and processing digital elevation models, and in analyzing time series. This book introduces methods of data analysis in the geosciences using Python that include basic statistics for univariate, bivariate, and multivariate data sets, time series analysis, and signal processing; the analysis of spatial and directional data; and image analysis. The text includes numerous examples that demonstrate how Python can be used on data sets from the earth sciences. The supplementary electronic material (available online through Springer Link) contains the example data as well as recipes that include all the Python commands featured in the book.

Introduces methods of data analysis in geosciences using Python Contains a complete collection of computer codes and sample data, as well as an accompanying blog Written by an expert for geoscientific modeling programs

Autorentext

Martin H. Trauth studied geophysics and geology at the University of Karlsruhe. He obtained a doctoral degree from the University of Kiel in 1995 and was subsequently appointed a permanent member of the scientific staff at the University of Potsdam. He became a lecturer following his habilitation in 2003 and was granted a titular professorship at the University of Potsdam in 2011. Since 1990, he has worked on various aspects of past changes in the climates of eastern Africa and South America. Martin H. Trauth has taught a variety of courses on data analysis in the earth sciences with MATLAB for more than 30 years both at the University of Potsdam and at other universities around the world.

Inhalt
Data Analysis in the Earth Sciences.- Introduction to Python.- Univariate Statistics.- Bivariate Statistics.- Time Series Analysis.- Signal Processing.- Spatial Data.- Image Processing.- Multivariate Statistics.- Directional Data.