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Python Recipes for Earth Sciences de Martin H. Trauth

Python Recipes for Earth Sciences

Autor Martin H. Trauth
en Limba Engleză Hardback – 8 oct 2024
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.
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Specificații

ISBN-13: 9783031569050
ISBN-10: 3031569059
Pagini: 504
Ilustrații: Approx. 500 p. 50 illus.
Dimensiuni: 160 x 241 x 33 mm
Greutate: 0.91 kg
Ediția:Second Edition 2024
Editura: Springer
Locul publicării:Cham, Switzerland

Cuprins

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.

Notă biografică

Martin H. Trauth studierte Geophysik und Geologie an der Universität Karlsruhe. Er promovierte 1995 an der Universität Kiel und wurde anschließend ständiger wissenschaftlicher Mitarbeiter an der Universität Potsdam. Nach seiner Habilitation im Jahr 2003 wurde er Privatdozent, 2011 erhielt er eine außerplanmäßige Professur an der Universität Potsdam. Seit 1990 beschäftigt sich Martin H. Trauth mit verschiedenen Aspekten vergangener Klimaveränderungen im östlichen Afrika und in Südamerika. Seine Projekte zielten auf ein besseres Verständnis (1) der Rolle der Tropen bei der Beendigung von Eiszeiten, (2) der Beziehung zwischen klimatischen Veränderungen und der menschlichen Evolution und (3) des Einflusses von Klimaanomalien auf Massenbewegungen in den zentralen Anden. In jedem dieser Projekte wurden numerische und statistische Methoden (z.B. Zeitreihenanalyse und Signalverarbeitung) mit Paläoklima-Zeitreihen, Seebilanzmodellierung, stochastische Modellierung von Bioturbation, Alterstiefenmodellierung von Sedimentabfolgen oder Satelliten- und mikroskopische Bildverarbeitung eingesetzt. Martin H. Trauth lehrt seit mehr als 25 Jahren an der Universität Potsdam und an anderen Universitäten weltweit eine Vielzahl von Kursen zur Datenanalyse in den Geowissenschaften.

Textul de pe ultima copertă

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

Caracteristici

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