Martin H. Trauth
Python Recipes for Earth Sciences
Python Recipes for Earth Sciences
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Python is used in geoscientific applications such as remote sensing, digital elevation models, and time series analysis. This book introduces methods of data analysis in the geosciences, including statistics, time series analysis, signal processing, spatial and directional data analysis, and image analysis, with examples and recipes.
Format: Paperback / softback
Length: 453 pages
Publication date: 30 September 2023
Publisher: Springer International Publishing AG
Python is a versatile programming language that finds extensive application in the field of geoscience. Its utilization spans various aspects, including the processing of images for remote sensing, the generation and manipulation of digital elevation models, and the analysis of time series data. In this comprehensive book, we delve into the realm of data analysis in the geosciences, employing Python as our tool of choice. Our approach encompasses a wide range of techniques, encompassing basic statistics for univariate, bivariate, and multivariate data sets, time series analysis, signal processing, the analysis of spatial and directional data, and image analysis.
To facilitate a deeper understanding, we provide numerous examples that showcase the practical applications of Python in the context of earth science data. These examples serve as practical guides, demonstrating how Python can be employed to extract valuable insights and make informed conclusions from diverse datasets. Furthermore, the accompanying supplementary electronic material, accessible online through Springer Link, offers an invaluable resource. It includes example data sets and comprehensive recipes that encompass all the Python commands featured in the book, enabling readers to replicate and experiment with the techniques discussed in detail.
By leveraging the power of Python and the comprehensive coverage of data analysis techniques in this book, geoscientists and aspiring data scientists can unlock the full potential of their data and advance their understanding of the earth's natural systems. Whether you are a seasoned professional or a newcomer to the field, this book serves as a valuable guide for exploring the rich world of geoscience data analysis using Python.
Weight: 837g
Dimension: 235 x 155 (mm)
ISBN-13: 9783031077210
Edition number: 1st ed. 2022
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