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MATLAB recipes for earth sciences
~
Trauth, Martin H.
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MATLAB recipes for earth sciences
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
MATLAB recipes for earth sciences/ by Martin H. Trauth.
作者:
Trauth, Martin H.
出版者:
Cham :Springer International Publishing : : 2021.,
面頁冊數:
xii, 517 p. :ill., digital ;24 cm.
內容註:
Data Analysis in Earth Sciences -- Introduction to MATLAB -- Univariate Statistics -- Bivariate Statistics -- Time-Series Analysis -- Signal Processing -- Spatial Data -- Image Processing -- Multivariate Statistics -- Statistics on Directional Data.
Contained By:
Springer Nature eBook
標題:
Earth sciences - Mathematics. -
電子資源:
https://doi.org/10.1007/978-3-030-38441-8
ISBN:
9783030384418
MATLAB recipes for earth sciences
Trauth, Martin H.
MATLAB recipes for earth sciences
[electronic resource] /by Martin H. Trauth. - Fifth edition - Cham :Springer International Publishing :2021. - xii, 517 p. :ill., digital ;24 cm. - Springer textbooks in earth sciences, geography and environment,2510-1307. - Springer textbooks in earth sciences, geography and environment..
Data Analysis in Earth Sciences -- Introduction to MATLAB -- Univariate Statistics -- Bivariate Statistics -- Time-Series Analysis -- Signal Processing -- Spatial Data -- Image Processing -- Multivariate Statistics -- Statistics on Directional Data.
MATLAB is used in a wide range of geoscientific applications, e.g. for image processing in remote sensing, for creating and processing digital elevation models, and for analyzing time series. This book introduces readers to MATLAB-based data analysis methods used in the geosciences, including basic statistics for univariate, bivariate and multivariate datasets, time-series analysis, signal processing, the analysis of spatial and directional data, and image analysis. The revised and updated Fifth Edition includes seven new sections, and the majority of the chapters have been rewritten and significantly expanded. New sections include error analysis, the problem of classical linear regression of log-transformed data, aligning stratigraphic sequences, the Normalized Difference Vegetation Index, Aitchison's log-ratio transformation, graphical representation of spherical data, and statistics of spherical data. The book also includes numerous examples demonstrating how MATLAB can be used on datasets from the earth sciences. The supplementary electronic material (available online through SpringerLink) contains recipes that include all the MATLAB commands featured in the book and the sample data.
ISBN: 9783030384418
Standard No.: 10.1007/978-3-030-38441-8doiSubjects--Uniform Titles:
MATLAB.
Subjects--Topical Terms:
551200
Earth sciences
--Mathematics.
LC Class. No.: QE33.2.M3
Dewey Class. No.: 550.151
MATLAB recipes for earth sciences
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Data Analysis in Earth Sciences -- Introduction to MATLAB -- Univariate Statistics -- Bivariate Statistics -- Time-Series Analysis -- Signal Processing -- Spatial Data -- Image Processing -- Multivariate Statistics -- Statistics on Directional Data.
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MATLAB is used in a wide range of geoscientific applications, e.g. for image processing in remote sensing, for creating and processing digital elevation models, and for analyzing time series. This book introduces readers to MATLAB-based data analysis methods used in the geosciences, including basic statistics for univariate, bivariate and multivariate datasets, time-series analysis, signal processing, the analysis of spatial and directional data, and image analysis. The revised and updated Fifth Edition includes seven new sections, and the majority of the chapters have been rewritten and significantly expanded. New sections include error analysis, the problem of classical linear regression of log-transformed data, aligning stratigraphic sequences, the Normalized Difference Vegetation Index, Aitchison's log-ratio transformation, graphical representation of spherical data, and statistics of spherical data. The book also includes numerous examples demonstrating how MATLAB can be used on datasets from the earth sciences. The supplementary electronic material (available online through SpringerLink) contains recipes that include all the MATLAB commands featured in the book and the sample data.
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