Название: Python Recipes for Earth Sciences, Second Edition
Автор: Martin H. Trauth
Издательство: Springer
Год: 2024
Страниц: 500
Язык: английский
Формат: pdf (true)
Размер: 20.1 MB
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. Codes are available online through GitHub. The book Python Recipes for Earth Sciences is designed to help undergraduate and postgraduate students, doctoral students, post-doctoral researchers, and professionals alike in finding quick solutions to common data analysis problems in the earth sciences. It provides a minimal amount of theoretical background and demonstrates the application of all described methods via examples. The present book contains Python scripts that can be used to solve typical problems in the earth sciences via simple statistics, time series analysis, geostatistics, and image processing. It also demonstrates the application of selected advanced techniques of data analysis, such as nonlinear time series analysis, adaptive filtering, bootstrapping, and terrain analysis. In order to derive the maximum benefit from this book, the reader will need to have access to the Python software and be able to execute the recipes while reading the book. The Python recipes yield various graphs on the screen that are not shown in the printed book. The tutorial-style book does, however, contain numerous figures, thereby making it possible to go through the text without actually running Python on a computer. I developed the recipes using Python 3.8.8, though most recipes will also work with earlier software releases, but not with Python 2.
