Spatial modeling in GIS and R for earth and environmental sciences

"Spatial Modeling in GIS and R for Earth and Environmental Sciences offers an integrated approach to spatial modelling using both GIS and R. Given the importance of Geographical Information Systems and geostatistics across a variety of applications in Earth and Environmental Science, a clear li...

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Bibliographic Details
Other Authors: Pourghasemi, Hamid Reza, (Editor), Gokceoglu, Candan, (Editor)
Format: eBook
Language: English
Published: Amsterdam, Netherlands : Elsevier, [2019]
Subjects:
ISBN: 9780128156957
0128156953
9780128152263
0128152265
Physical Description: 1 online resource (xxviii, 770 pages) : illustrations (chiefly color), maps

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Table of contents

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035 |a (OCoLC)1083205446  |z (OCoLC)1083357236 
245 0 0 |a Spatial modeling in GIS and R for earth and environmental sciences /  |c edited by Hamid Reza Pourghasemi, Candan Goceoglu. 
246 3 |a Spatial modeling in geographic information system and R for earth and environmental sciences 
264 1 |a Amsterdam, Netherlands :  |b Elsevier,  |c [2019] 
300 |a 1 online resource (xxviii, 770 pages) :  |b illustrations (chiefly color), maps 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
504 |a Includes bibliographical references and index. 
506 |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty 
520 |a "Spatial Modeling in GIS and R for Earth and Environmental Sciences offers an integrated approach to spatial modelling using both GIS and R. Given the importance of Geographical Information Systems and geostatistics across a variety of applications in Earth and Environmental Science, a clear link between GIS and open source software is essential for the study of spatial objects or phenomena that occur in the real world and facilitate problem-solving. Organized into clear sections on applications and using case studies, the book helps researchers to more quickly understand GIS data and formulate more complex conclusions. The book is the first reference to provide methods and applications for combining the use of R and GIS in modeling spatial processes. It is an essential tool for students and researchers in earth and environmental science, especially those looking to better utilize GIS and spatial modeling."--Provided by publisher 
505 0 |a Front Cover; Spatial Modeling in GIS and R for Earth and Environmental Sciences; Copyright Page; Dedication; Contents; List of Contributors; 1 Spatial Analysis of Extreme Rainfall Values Based on Support Vector Machines Optimized by Genetic Algorithms: The Case of ... ; 1.1 Introduction; 1.2 The Study Area; 1.3 Methodology and Data; 1.4 Results; 1.5 Performance Criteria; 1.6 Discussion; 1.7 Conclusions; References; 2 Remotely Sensed Spatial and Temporal Variations of Vegetation Indices Subjected to Rainfall Amount and Distribution Prope ... ; 2.1 Introduction; 2.2 Materials and Methods 
505 8 |a 2.2.1 Study Area2.2.2 Data; 2.2.3 Vegetation Indices; 2.2.4 Rainfall Distribution Parameters; 2.3 Results and Discussion; 2.3.1 Vegetation Indices; 2.3.1.1 Normalized Difference Vegetation Index; 2.3.1.2 Spatial Variations of the Normalized Difference Vegetation Index; 2.3.1.3 Green Normalized Difference Vegetation Index; 2.3.1.4 Global Environmental Monitoring Index; 2.3.2 Spatial Normalized Differential Reflectance and Shortwave Crop Reflectance Index; 2.3.3 Rainfall Properties Versus Normalized Difference Vegetation Index, Green Normalized Difference Vegetation Index, Glob ... 
505 8 |a 2.3.3.1 Prespring Rainfall2.3.3.2 Cumulative Rainfall; 2.3.3.3 Rainfall Distribution; 2.4 Conclusion; References; Further Reading; 3 Numerical Recipes for Landslide Spatial Prediction Using R-INLA: A Step-by-Step Tutorial; 3.1 Introduction; 3.2 Dataset Description and Preparation; 3.2.1 Multiple Occurrence Regional Landslide Event, Messina, 2009; 3.2.2 Computing Slope Units in GIS; 3.3 Point Process Modeling and Estimation Using R-INLA; 3.3.1 Preprocessing; 3.3.2 Fitting a Cox Point Process Model Using R-INLA; 3.4 Results; 3.4.1 Estimated Fixed and Random Effects 
505 8 |a 3.4.2 Estimated Landslide Intensity at Various Spatial Resolutions3.4.3 Model Checking and Goodness-of-Fit Assessment; 3.4.4 Cross-Validation Study and Out-of-Sample Predictive Skill; 3.5 Discussion; 3.6 Conclusion; References; 4 Geospatial Multicriteria Decision Analysis in Forest Operational Planning; 4.1 Introduction; 4.1.1 Multicriteria Decision Elements; 4.1.1.1 Decision-Maker Analysis; 4.1.1.2 Hierarchical Structure; 4.1.1.3 Decision Elements; Criteria and Subcriteria; Decision Alternatives; 4.1.1.4 Interpretation Findings; 4.1.2 Classification of Spatial Decision Support System 
505 8 |a 4.1.2.1 Geostatistical Analysis With R packages4.1.2.2 Forest Management Hierarchy; Strategic Planning; Tactical Planning; Operational Planning; 4.1.3 A Perspective of Forest Resource Management in Iran; 4.1.3.1 General Information; 4.1.3.2 The Role of Decision Support Systems in Iranian Forestry; 4.2 Planning Problems; 4.3 Methods; 4.3.1 Multicriteria Decision Analysis; 4.3.2 Geostatistical Analysis; 4.3.3 Spatial Modeling Procedure; 4.3.4 Model Application; 4.4 Results; 4.4.1 The Current Conditions of the Terrain; 4.5 Discussion; 4.6 Conclusions; Acknowledgments; References; Further Reading 
590 |a Knovel  |b Knovel (All titles) 
650 0 |a Earth sciences  |x Remote sensing. 
650 0 |a Environmental monitoring  |x Remote sensing. 
650 0 |a Geographic information systems. 
650 0 |a R (Computer program language) 
650 0 |a Geospatial data  |x Computer processing. 
655 7 |a elektronické knihy  |7 fd186907  |2 czenas 
655 9 |a electronic books  |2 eczenas 
700 1 |a Pourghasemi, Hamid Reza,  |e editor. 
700 1 |a Gokceoglu, Candan,  |e editor. 
776 0 8 |i Print version:  |t Spatial modeling in GIS and R for earth and environmental sciences.  |d Amsterdam, Netherlands ; Cambridge, MA, United States : Elsevier, 2019  |z 0128152265  |z 9780128152263  |w (OCoLC)1084302116 
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