• Contact

  • Newsletter

  • About us

  • Delivery options

  • News

  • 0
    MATLAB? Recipes for Earth Sciences
      • GET 8% OFF

      • The discount is only available for 'Alert of Favourite Topics' newsletter recipients.
      • Publisher's listprice EUR 128.39
      • The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.

        54 463 Ft (51 869 Ft + 5% VAT)
      • Discount 8% (cc. 4 357 Ft off)
      • Discounted price 50 105 Ft (47 719 Ft + 5% VAT)

    54 463 Ft

    db

    Availability

    Estimated delivery time: In stock at the publisher, but not at Prospero's office. Delivery time approx. 3-5 weeks.
    Not in stock at Prospero.

    Why don't you give exact delivery time?

    Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.

    Product details:

    • Edition number Sixth Edition 2025
    • Publisher Springer
    • Date of Publication 18 March 2025
    • Number of Volumes 1 pieces, Book

    • ISBN 9783031579486
    • Binding Hardback
    • No. of pages567 pages
    • Size 235x155 mm
    • Language English
    • Illustrations 12 Illustrations, black & white; 132 Illustrations, color
    • 696

    Categories

    Short description:

    MATLAB? 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 MATLAB, 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 MATLAB 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 MATLAB 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 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.

    More

    Long description:

    MATLAB? 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 MATLAB, 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 MATLAB 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 MATLAB commands featured in the book and example data.

    More

    Table of Contents:

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

    More