國立虎尾科技大學 |

Spatial Modeling Principles in Earth Sciences

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Spatial Modeling Principles in Earth Sciences/ by Zekai Sen.
Author:	Sen, Zekai.
Description:	XII, 413 p. 212 illus.online resource. :
Contained By:	Springer Nature eBook
Subject:	Geology—Statistical methods. -
Online resource:	https://doi.org/10.1007/978-3-319-41758-5
ISBN:	9783319417585

Spatial Modeling Principles in Earth Sciences
Sen, Zekai.

Spatial Modeling Principles in Earth Sciences[electronic resource] /by Zekai Sen. - 2nd ed. 2016. - XII, 413 p. 212 illus.online resource.

Introduction -- Sampling and Deterministic Modeling Methods -- Temporal and Point Uncertainty Modeling -- Classical Spatial Variation Models in Earth sciences -- Spatial Dependence Measures -- Spatial Modeling -- Spatial Simulation -- Index. .

This is a revised and updated second edition, including new chapters on temporal and point uncertainty model, as well as on sampling and deterministic modeling. It is a comprehensive presentation of spatial modeling techniques used in the earth sciences, outlining original techniques developed by the author. Data collection in the earth sciences is difficult and expensive, but simple, rational and logical approaches help the reader to appreciate the fundamentals of advanced methodologies. It requires special care to gather accurate geological, hydrogeological, meteorological and hydrological information all with risk assessments. Spatial simulation methodologies in the earth sciences are essential, then, if we want to understand the variability in features such as fracture frequencies, rock quality, and grain size distribution in rock and porous media. This book outlines in a detailed yet accessible way the main spatial modeling techniques, in particular the Kriging methodology. It also presents many unique physical approaches, field cases, and sample interpretations. Since Kriging’s origin in the 1960s it has been developed into a number of new methods such as cumulative SV (CSV), point CSV (PCSV), and spatial dependence function, which have been applied in different aspects of the earth sciences. Each one of these techniques is explained in this book, as well as how they are used to model earth science phenomena such as geology, earthquakes, meteorology, and hydrology. In addition to Kriging and its variants, several alternatives to Kriging methodology are presented and the necessary steps in their applications are clearly explained. Simple spatial variation prediction methodologies are also revised with up-to-date literature, and the ways in which they relate to more advanced spatial modeling methodologies are explained. The book is a valuable resource for students, researchers and professionals of a broad range of disciplines including geology, geography, hydrology, meteorology, environment, image processing, spatial modeling and related topics. Keywords »Data mining - Geo-statistics - Kriging - Regional uncertainty - Spatial dependence - Spatial modeling - geographic data - geoscience - hydrology - image processing .

ISBN: 9783319417585

Standard No.: 10.1007/978-3-319-41758-5doiSubjects--Topical Terms:

1254867
Geology—Statistical methods.

LC Class. No.: QE33.2.S82

Dewey Class. No.: 553

Spatial Modeling Principles in Earth Sciences
LDR:03844nam a22003975i 4500 001 974100
003 DE-He213
005 20200701163439.0
007 cr nn 008mamaa
008 201211s2016 gw | s |||| 0|eng d
020 $a 9783319417585 $9 978-3-319-41758-5
024 7 $a 10.1007/978-3-319-41758-5 $2 doi
035 $a 978-3-319-41758-5
050 4 $a QE33.2.S82
072 7 $a RBG $2 bicssc
072 7 $a SCI031000 $2 bisacsh
072 7 $a RBG $2 thema
082 0 4 $a 553 $2 23
100 1 $a Sen, Zekai. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 679510
245 1 0 $a Spatial Modeling Principles in Earth Sciences $h [electronic resource] / $c by Zekai Sen.
250 $a 2nd ed. 2016.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2016.
300 $a XII, 413 p. 212 illus. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
505 0 $a Introduction -- Sampling and Deterministic Modeling Methods -- Temporal and Point Uncertainty Modeling -- Classical Spatial Variation Models in Earth sciences -- Spatial Dependence Measures -- Spatial Modeling -- Spatial Simulation -- Index. .
520 $a This is a revised and updated second edition, including new chapters on temporal and point uncertainty model, as well as on sampling and deterministic modeling. It is a comprehensive presentation of spatial modeling techniques used in the earth sciences, outlining original techniques developed by the author. Data collection in the earth sciences is difficult and expensive, but simple, rational and logical approaches help the reader to appreciate the fundamentals of advanced methodologies. It requires special care to gather accurate geological, hydrogeological, meteorological and hydrological information all with risk assessments. Spatial simulation methodologies in the earth sciences are essential, then, if we want to understand the variability in features such as fracture frequencies, rock quality, and grain size distribution in rock and porous media. This book outlines in a detailed yet accessible way the main spatial modeling techniques, in particular the Kriging methodology. It also presents many unique physical approaches, field cases, and sample interpretations. Since Kriging’s origin in the 1960s it has been developed into a number of new methods such as cumulative SV (CSV), point CSV (PCSV), and spatial dependence function, which have been applied in different aspects of the earth sciences. Each one of these techniques is explained in this book, as well as how they are used to model earth science phenomena such as geology, earthquakes, meteorology, and hydrology. In addition to Kriging and its variants, several alternatives to Kriging methodology are presented and the necessary steps in their applications are clearly explained. Simple spatial variation prediction methodologies are also revised with up-to-date literature, and the ways in which they relate to more advanced spatial modeling methodologies are explained. The book is a valuable resource for students, researchers and professionals of a broad range of disciplines including geology, geography, hydrology, meteorology, environment, image processing, spatial modeling and related topics. Keywords »Data mining - Geo-statistics - Kriging - Regional uncertainty - Spatial dependence - Spatial modeling - geographic data - geoscience - hydrology - image processing .
650 0 $a Geology—Statistical methods. $3 1254867
650 0 $a Computer simulation. $3 560190
650 0 $a Geographical information systems. $3 1254121
650 1 4 $a Quantitative Geology. $3 682376
650 2 4 $a Simulation and Modeling. $3 669249
650 2 4 $a Geographical Information Systems/Cartography. $3 670563
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783319417561
776 0 8 $i Printed edition: $z 9783319417578
776 0 8 $i Printed edition: $z 9783319824215
856 4 0 $u https://doi.org/10.1007/978-3-319-41758-5
912 $a ZDB-2-EES
912 $a ZDB-2-SXEE
950 $a Earth and Environmental Science (SpringerNature-11646)
950 $a Earth and Environmental Science (R0) (SpringerNature-43711)