Spatial Modeling in GIS and R for Earth and Environmental Sciences

Spatial Modeling in GIS and R for Earth and Environmental Sciences
Author: Hamid Reza Pourghasemi,Candan Gokceoglu
Publsiher: Elsevier
Total Pages: 798
Release: 2019-01-18
ISBN 10: 0128156953
ISBN 13: 9780128156957
Language: EN, FR, DE, ES & NL

Spatial Modeling in GIS and R for Earth and Environmental Sciences Book Review:

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. Offers a clear, interdisciplinary guide to serve researchers in a variety of fields, including hazards, land surveying, remote sensing, cartography, geophysics, geology, natural resources, environment and geography Provides an overview, methods and case studies for each application Expresses concepts and methods at an appropriate level for both students and new users to learn by example

Spatial Data Analysis in the Social and Environmental Sciences

Spatial Data Analysis in the Social and Environmental Sciences
Author: Robert Haining
Publsiher: Cambridge University Press
Total Pages: 409
Release: 1993-08-26
ISBN 10: 9780521448666
ISBN 13: 0521448662
Language: EN, FR, DE, ES & NL

Spatial Data Analysis in the Social and Environmental Sciences Book Review:

A description of methods for the analysis of spatial data.

Soil and Groundwater Remediation Technologies

Soil and Groundwater Remediation Technologies
Author: Yong Sik Ok,Jörg Rinklebe,Deyi Hou,Daniel C.W. Tsang,Filip M.G. Tack
Publsiher: CRC Press
Total Pages: 338
Release: 2020-04-14
ISBN 10: 1000046966
ISBN 13: 9781000046960
Language: EN, FR, DE, ES & NL

Soil and Groundwater Remediation Technologies Book Review:

This book offers various soil and water treatment technologies due to increasing global soil and water pollution. In many countries, the management of contaminated land has matured, and it is developing in many others. Topics covered include chemical and ecological risk assessment of contaminated sites; phytomanagement of contaminants; arsenic removal; selection and technology diffusion; technologies and socio-environmental management; post-remediation long-term management; soil and groundwater laws and regulations; and trace element regulation limits in soil. Future prospects of soil and groundwater remediation are critically discussed in this book. Hence, readers will learn to understand the future prospects of soil and groundwater contaminants and remediation measures. Key Features: Discusses conventional and novel aspects of soil and groundwater remediation technologies Includes new monitoring/sensing technologies for soil and groundwater pollution Features a case study of remediation of contaminated sites in the old, industrial, Ruhr area in Germany Highlights soil washing, soil flushing, and stabilization/solidification Presents information on emerging contaminants that exhibit new challenges This book is designed for undergraduate and graduate courses and can be used as a handbook for researchers, policy makers, and local governmental institutes. Soil and Groundwater Remediation Technologies: A Practical Guide is written by a team of leading global experts in the field.

Quantitative Analysis and Modeling of Earth and Environmental Data

Quantitative Analysis and Modeling of Earth and Environmental Data
Author: Jiaping Wu,Junyu He,George Christakos
Publsiher: Elsevier
Total Pages: 420
Release: 2020-12-15
ISBN 10: 9780128163412
ISBN 13: 0128163410
Language: EN, FR, DE, ES & NL

Quantitative Analysis and Modeling of Earth and Environmental Data Book Review:

Quantitative Analysis and Modeling of Earth and Environmental Data: Applications for Spatial and Temporal Variation offers a systematic, quantitative analysis of multi-sourced data, including the spatial distribution and temporal dynamics of natural attributes. It covers data handling techniques that may vary by space and/or time, and aims to improve understanding of physical laws of change underlying available numerical datasets, while also considering in-situ uncertainties and relevant measurement errors (conceptual, technical, computational). Featuring real-world practical applications and practice exercises, this book is a comprehensive step-by-step tutorial of data-driven techniques that will help students and researchers master data analysis in earth and environmental sciences. The notions and methods presented in the book cover a wide range of data in various forms and sources, including hard measurements, soft observations, secondary information and auxiliary variables (ground-level measurements, satellite observations, scientific instruments and records, protocols and surveys, empirical models and charts). Addresses the analysis and processing data that varies spatially and/or temporally, which is the case with the majority of data in scientific and engineering disciplines Covers a wide range of data describing a variety of attributes characterizing physical phenomena and systems including earth, ocean and atmospheric variables, environmental and ecological parameters, population health states, disease indicators, and social and economic characteristics Includes case studies and practice exercises at the end of each chapter for both real-world applications and deeper understanding of the concepts presented

Spatial Modeling in Forest Resources Management

Spatial Modeling in Forest Resources Management
Author: Pravat Kumar Shit,Hamid Reza Pourghasemi,Pulakesh Das,Gouri Sankar Bhunia
Publsiher: Springer Nature
Total Pages: 675
Release: 2020-10-08
ISBN 10: 3030565424
ISBN 13: 9783030565428
Language: EN, FR, DE, ES & NL

Spatial Modeling in Forest Resources Management Book Review:

This book demonstrates the measurement, monitoring, mapping, and modeling of forest resources. It explores state-of-the-art techniques based on open-source software & R statistical programming and modeling specifically, with a focus on the recent trends in data mining/machine learning techniques and robust modeling in forest resources. Discusses major topics such as forest health assessment, estimating forest biomass & carbon stock, land use forest cover (LUFC), dynamic vegetation modeling (DVM) approaches, forest-based rural livelihood, habitat suitability analysis, biodiversity and ecology, and biodiversity, the book presents novel advances and applications of RS-GIS and R in a precise and clear manner. By offering insights into various concepts and their importance for real-world applications, it equips researchers, professionals, and policy-makers with the knowledge and skills to tackle a wide range of issues related to geographic data, including those with scientific, societal, and environmental implications.

Spatial Data Modelling for 3D GIS

Spatial Data Modelling for 3D GIS
Author: Alias Abdul-Rahman,Morakot Pilouk
Publsiher: Springer Science & Business Media
Total Pages: 289
Release: 2007-09-23
ISBN 10: 3540741674
ISBN 13: 9783540741671
Language: EN, FR, DE, ES & NL

Spatial Data Modelling for 3D GIS Book Review:

This book covers fundamental aspects of spatial data modelling specifically on the aspect of three-dimensional (3D) modelling and structuring. Realisation of "true" 3D GIS spatial system needs a lot of effort, and the process is taking place in various research centres and universities in some countries. The development of spatial data modelling for 3D objects is the focus of this book.

Spatial Data Analysis

Spatial Data Analysis
Author: Robert P. Haining,Robert Haining
Publsiher: Cambridge University Press
Total Pages: 432
Release: 2003-04-17
ISBN 10: 9780521774376
ISBN 13: 0521774373
Language: EN, FR, DE, ES & NL

Spatial Data Analysis Book Review:

Table of contents

Geocomputation with R

Geocomputation with R
Author: Robin Lovelace,Jakub Nowosad,Jannes Muenchow
Publsiher: CRC Press
Total Pages: 335
Release: 2019-03-22
ISBN 10: 1351396900
ISBN 13: 9781351396905
Language: EN, FR, DE, ES & NL

Geocomputation with R Book Review:

Geocomputation with R is for people who want to analyze, visualize and model geographic data with open source software. It is based on R, a statistical programming language that has powerful data processing, visualization, and geospatial capabilities. The book equips you with the knowledge and skills to tackle a wide range of issues manifested in geographic data, including those with scientific, societal, and environmental implications. This book will interest people from many backgrounds, especially Geographic Information Systems (GIS) users interested in applying their domain-specific knowledge in a powerful open source language for data science, and R users interested in extending their skills to handle spatial data. The book is divided into three parts: (I) Foundations, aimed at getting you up-to-speed with geographic data in R, (II) extensions, which covers advanced techniques, and (III) applications to real-world problems. The chapters cover progressively more advanced topics, with early chapters providing strong foundations on which the later chapters build. Part I describes the nature of spatial datasets in R and methods for manipulating them. It also covers geographic data import/export and transforming coordinate reference systems. Part II represents methods that build on these foundations. It covers advanced map making (including web mapping), "bridges" to GIS, sharing reproducible code, and how to do cross-validation in the presence of spatial autocorrelation. Part III applies the knowledge gained to tackle real-world problems, including representing and modeling transport systems, finding optimal locations for stores or services, and ecological modeling. Exercises at the end of each chapter give you the skills needed to tackle a range of geospatial problems. Solutions for each chapter and supplementary materials providing extended examples are available at https://geocompr.github.io/geocompkg/articles/. Dr. Robin Lovelace is a University Academic Fellow at the University of Leeds, where he has taught R for geographic research over many years, with a focus on transport systems. Dr. Jakub Nowosad is an Assistant Professor in the Department of Geoinformation at the Adam Mickiewicz University in Poznan, where his focus is on the analysis of large datasets to understand environmental processes. Dr. Jannes Muenchow is a Postdoctoral Researcher in the GIScience Department at the University of Jena, where he develops and teaches a range of geographic methods, with a focus on ecological modeling, statistical geocomputing, and predictive mapping. All three are active developers and work on a number of R packages, including stplanr, sabre, and RQGIS.

Data Analysis and Statistics for Geography Environmental Science and Engineering

Data Analysis and Statistics for Geography  Environmental Science  and Engineering
Author: Miguel F. Acevedo
Publsiher: CRC Press
Total Pages: 557
Release: 2012-12-07
ISBN 10: 1466592214
ISBN 13: 9781466592216
Language: EN, FR, DE, ES & NL

Data Analysis and Statistics for Geography Environmental Science and Engineering Book Review:

Providing a solid foundation for twenty-first-century scientists and engineers, Data Analysis and Statistics for Geography, Environmental Science, and Engineering guides readers in learning quantitative methodology, including how to implement data analysis methods using open-source software. Given the importance of interdisciplinary work in sustain

ArcGIS for Environmental and Water Issues

ArcGIS for Environmental and Water Issues
Author: William Bajjali
Publsiher: Springer
Total Pages: 353
Release: 2017-11-24
ISBN 10: 3319611585
ISBN 13: 9783319611587
Language: EN, FR, DE, ES & NL

ArcGIS for Environmental and Water Issues Book Review:

This textbook is a step-by-step tutorial on the applications of Geographic Information Systems (GIS) in environmental and water resource issues. It provides information about GIS and its applications, specifically using the most advanced ESRI GIS technology and its extensions. Eighteen chapters cover GIS applications in the field of earth sciences and water resources in detail from the ground up. Author William Bajjali explains what a GIS is and what it is used for, the basics of map classification, data acquisition, coordinate systems and projections, vectorization, geodatabase and relational database, data editing, geoprocessing, suitability modeling, working with raster, watershed delineation, mathematical and statistical interpolation, and more advanced techniques, tools and extensions such as ArcScan, Topology, Geocoding, Hydrology, Geostatistical Analyst, Spatial Analyst, Network Analyst, 3-D Analyst. ArcPad, ESRI’s cutting-edge mobile GIS software, is covered in detail as well. Each chapter contains concrete case studies and exercises – many from the author’s own work in the United States and Middle East. This volume is targeted toward advanced undergraduates, but could also be useful for professionals and for anyone who utilizes GIS or practices spatial analysis in relation to geology, hydrology, ecology, and environmental sciences.

International GIS Sourcebook

International GIS Sourcebook
Author: Anonim
Publsiher: Unknown
Total Pages: 329
Release: 1993
ISBN 10:
ISBN 13: UOM:39015048294766
Language: EN, FR, DE, ES & NL

International GIS Sourcebook Book Review:

GIS and Geostatistical Techniques for Groundwater Science

GIS and Geostatistical Techniques for Groundwater Science
Author: Dr. Senapathi Venkatramanan,Dr. Prasanna Mohan Viswanathan,Sang Yong Chung
Publsiher: Elsevier
Total Pages: 389
Release: 2019-05-28
ISBN 10: 0128154144
ISBN 13: 9780128154144
Language: EN, FR, DE, ES & NL

GIS and Geostatistical Techniques for Groundwater Science Book Review:

GIS and Geostatistical Techniques for Groundwater Science provides a detailed synthesis of the application of GIS and geostatistics in groundwater studies. As the book illustrates, GIS can be a powerful tool for developing solutions for water resource problems, assessing water quality, and managing water resources. Beginning with an introduction to the history of GIS and geostatistical techniques in groundwater studies, the book then describes various spatial techniques, including case studies for various applications, from quality assessment, to resource management. This book assembles the most up-to-date techniques in GIS and geostatistics as they relate to groundwater, one of our most important natural resources. Provides details on the application of GIS and statistics in groundwater studies Includes practical coverage of the use of spatial analysis techniques in groundwater science Bridges the gap between geostatistics and GIS as it relates to groundwater science and management Offers worldwide case studies to illustrate various techniques and applications in addressing groundwater issues

GIS and Environmental Modeling

GIS and Environmental Modeling
Author: Michael F. Goodchild,Louis T. Steyaert,Bradley O. Parks,Carol Johnston,David Maidment,Michael Crane,Sandi Glendinning
Publsiher: John Wiley & Sons
Total Pages: 504
Release: 1996-09-30
ISBN 10: 9780470236772
ISBN 13: 0470236779
Language: EN, FR, DE, ES & NL

GIS and Environmental Modeling Book Review:

GIS and Environmental Modeling: Progress and Research Issues Michael F. Goodchild, Louis T. Steyaert, Bradley O. Parks, Carol Johnston, David Maidment, Michael Crane, and Sandi Glendinning, Editors With growing pressure on natural resources and landscapes there is an increasing need to predict the consequences of any changes to the environment. Modelling plays an important role in this by helping our understanding of the environment and by forecasting likely impacts. In recent years moves have been made to link models to Geographical Information Systems to provide a means of analysing changes over an area as well as over time. GIS and Environmental Modeling explores the progress made to date in integrating these two software systems. Approaches to the subject are made from theoretical, technical as well as data stand points. The existing capabilities of current systems are described along with important issues of data availability, accuracy and error. Various case studies illustrate this and highlight the common concepts and issues that exist between researchers in different environmental fields. The future needs and prospects for integrating GIS and environmental models are also explored with developments in both data handling and modelling discussed. The book brings together the knowledge and experience of over 100 researchers from academic, commercial and government backgrounds who work in a wide range of disciplines. The themes followed in the text provide a fund of knowledge and guidance for those involved in environmental modelling and GIS. The book is easily accessible for readers with a basic GIS knowledge and the ideas and results of the research are clearly illustrated with both colour and black and white graphics.

Spatial Analysis of Coastal Environments

Spatial Analysis of Coastal Environments
Author: Sarah M. Hamylton
Publsiher: Cambridge University Press
Total Pages: 329
Release: 2017-04-13
ISBN 10: 1108158331
ISBN 13: 9781108158336
Language: EN, FR, DE, ES & NL

Spatial Analysis of Coastal Environments Book Review:

At the convergence of the land and sea, coastal environments are some of the most dynamic and populated places on Earth. This book explains how the many varied forms of spatial analysis, including mapping, monitoring and modelling, can be applied to a range of coastal environments such as estuaries, mangroves, seagrass beds and coral reefs. Presenting empirical geographical approaches to modelling, which draw on recent developments in remote sensing technology, geographical information science and spatial statistics, it provides the analytical tools to map, monitor and explain or predict coastal features. With detailed case studies and accompanying online practical exercises, it is an ideal resource for undergraduate courses in spatial science. Taking a broad view of spatial analysis and covering basic and advanced analytical areas such as spatial data and geostatistics, it is also a useful reference for ecologists, geomorphologists, geographers and modellers interested in understanding coastal environments.

Natural Hazards GIS Based Spatial Modeling Using Data Mining Techniques

Natural Hazards GIS Based Spatial Modeling Using Data Mining Techniques
Author: Hamid Reza Pourghasemi,Mauro Rossi
Publsiher: Springer
Total Pages: 296
Release: 2018-12-13
ISBN 10: 3319733834
ISBN 13: 9783319733838
Language: EN, FR, DE, ES & NL

Natural Hazards GIS Based Spatial Modeling Using Data Mining Techniques Book Review:

This edited volume assesses capabilities of data mining algorithms for spatial modeling of natural hazards in different countries based on a collection of essays written by experts in the field. The book is organized on different hazards including landslides, flood, forest fire, land subsidence, earthquake, and gully erosion. Chapters were peer-reviewed by recognized scholars in the field of natural hazards research. Each chapter provides an overview on the topic, methods applied, and discusses examples used. The concepts and methods are explained at a level that allows undergraduates to understand and other readers learn through examples. This edited volume is shaped and structured to provide the reader with a comprehensive overview of all covered topics. It serves as a reference for researchers from different fields including land surveying, remote sensing, cartography, GIS, geophysics, geology, natural resources, and geography. It also serves as a guide for researchers, students, organizations, and decision makers active in land use planning and hazard management.

Remote Sensing of Ocean and Coastal Environments

Remote Sensing of Ocean and Coastal Environments
Author: Meenu Rani,Kaliraj Seenipandi,Sufia Rehman,Pavan Kumar,Haroon Sajjad
Publsiher: Elsevier
Total Pages: 426
Release: 2020-09-27
ISBN 10: 0128231602
ISBN 13: 9780128231609
Language: EN, FR, DE, ES & NL

Remote Sensing of Ocean and Coastal Environments Book Review:

Remote Sensing of Ocean and Coastal Environments advances the scientific understanding and application of technologies to address a variety of areas relating to sustainable development, including environmental systems analysis, environmental management, clean processes, green chemistry and green engineering. Through each contributed chapter, the book covers ocean remote sensing, ocean color monitoring, modeling biomass and the carbon of oceanic ecosystems, sea surface temperature (SST) and sea surface salinity, ocean monitoring for oil spills and pollutions, coastal erosion and accretion measurement. This book is aimed at those with a common interest in oceanography techniques, sustainable development and other diverse backgrounds within earth and ocean science fields. This book is ideal for academicians, scientists, environmentalists, meteorologists, environmental consultants and computing experts working in the areas of earth and ocean sciences. Provides a comprehensive assessment of various ocean processes and their relative phenomena Includes graphical abstract and photosets in each chapter Presents literature reviews, case studies and applications

An Introduction to R for Spatial Analysis and Mapping

An Introduction to R for Spatial Analysis and Mapping
Author: Chris Brunsdon,Lex Comber
Publsiher: SAGE
Total Pages: 336
Release: 2018-12-10
ISBN 10: 152645422X
ISBN 13: 9781526454225
Language: EN, FR, DE, ES & NL

An Introduction to R for Spatial Analysis and Mapping Book Review:

This is a new edition of the accessible and student-friendly 'how to' for anyone using R for the first time, for use in spatial statistical analysis, geocomputation and digital mapping. The authors, once again, take readers from ‘zero to hero’, updating the now standard text to further enable practical R applications in GIS, spatial analyses, spatial statistics, web-scraping and more. Revised and updated, each chapter includes: example data and commands to explore hands-on; scripts and coding to exemplify specific functionality; self-contained exercises for students to work through; embedded code within the descriptive text. The new edition includes detailed discussion of new and emerging packages within R like sf, ggplot, tmap, making it the go to introduction for all researchers collecting and using data with location attached. This is the introduction to the use of R for spatial statistical analysis, geocomputation, and GIS for all researchers - regardless of discipline - collecting and using data with location attached.

Fuzzy Modeling with Spatial Information for Geographic Problems

Fuzzy Modeling with Spatial Information for Geographic Problems
Author: Frederick E. Petry,Vincent B. Robinson,Maria A. Cobb
Publsiher: Springer Science & Business Media
Total Pages: 338
Release: 2006-01-16
ISBN 10: 9783540268864
ISBN 13: 3540268863
Language: EN, FR, DE, ES & NL

Fuzzy Modeling with Spatial Information for Geographic Problems Book Review:

The capabilities of modern technology are rapidly increasing, spurred on to a large extent by the tremendous advances in communications and computing. Automated vehicles and global wireless connections are some examples of these advances. In order to take advantage of such enhanced capabilities, our need to model and manipulate our knowledge of the geophysical world, using compatible representations, is also rapidly increasing. In response to this one fundamental issue of great concern in modern geographical research is how to most effectively capture the physical world around us in systems like geographical information systems (GIS). Making this task even more challenging is the fact that uncertainty plays a pervasive role in the representation, analysis and use of geospatial information. The types of uncertainty that appear in geospatial information systems are not the just simple randomness of observation, as in weather data, but are manifested in many other forms including imprecision, incompleteness and granularization. Describing the uncertainty of the boundaries of deserts and mountains clearly require different tools than those provided by probability theory. The multiplicity of modalities of uncertainty appearing in GIS requires a variety of formalisms to model these uncertainties. In light of this it is natural that fuzzy set theory has become a topic of intensive interest in many areas of geographical research and applications This volume, Fuzzy Modeling with Spatial Information for Geographic Problems, provides many stimulating examples of advances in geographical research based on approaches using fuzzy sets and related technologies.

Geographical Data Science and Spatial Data Analysis

Geographical Data Science and Spatial Data Analysis
Author: Lex Comber,Chris Brunsdon
Publsiher: SAGE
Total Pages: 360
Release: 2020-12-02
ISBN 10: 1526485435
ISBN 13: 9781526485434
Language: EN, FR, DE, ES & NL

Geographical Data Science and Spatial Data Analysis Book Review:

We are in an age of big data where all of our everyday interactions and transactions generate data. Much of this data is spatial – it is collected some-where – and identifying analytical insight from trends and patterns in these increasing rich digital footprints presents a number of challenges. Whilst other books describe different flavours of Data Analytics in R and other programming languages, there are none that consider Spatial Data (ie the location attached to data), or that consider issues of inference, linking Big Data, Geography, GIS, Mapping and Spatial Analytics. This is a ‘learning by doing’ text book, building on the previous book by the same authors, An Introduction to R for Spatial Analysis and Mapping. It details the theoretical issues in analyses of Big Spatial Data and developing practical skills in the reader for addressing these with confidence.

Applied Spatial Data Analysis with R

Applied Spatial Data Analysis with R
Author: Roger S. Bivand,Edzer Pebesma,Virgilio Gómez-Rubio
Publsiher: Springer Science & Business Media
Total Pages: 405
Release: 2013-06-21
ISBN 10: 1461476186
ISBN 13: 9781461476184
Language: EN, FR, DE, ES & NL

Applied Spatial Data Analysis with R Book Review:

Applied Spatial Data Analysis with R, second edition, is divided into two basic parts, the first presenting R packages, functions, classes and methods for handling spatial data. This part is of interest to users who need to access and visualise spatial data. Data import and export for many file formats for spatial data are covered in detail, as is the interface between R and the open source GRASS GIS and the handling of spatio-temporal data. The second part showcases more specialised kinds of spatial data analysis, including spatial point pattern analysis, interpolation and geostatistics, areal data analysis and disease mapping. The coverage of methods of spatial data analysis ranges from standard techniques to new developments, and the examples used are largely taken from the spatial statistics literature. All the examples can be run using R contributed packages available from the CRAN website, with code and additional data sets from the book's own website. Compared to the first edition, the second edition covers the more systematic approach towards handling spatial data in R, as well as a number of important and widely used CRAN packages that have appeared since the first edition. This book will be of interest to researchers who intend to use R to handle, visualise, and analyse spatial data. It will also be of interest to spatial data analysts who do not use R, but who are interested in practical aspects of implementing software for spatial data analysis. It is a suitable companion book for introductory spatial statistics courses and for applied methods courses in a wide range of subjects using spatial data, including human and physical geography, geographical information science and geoinformatics, the environmental sciences, ecology, public health and disease control, economics, public administration and political science. The book has a website where complete code examples, data sets, and other support material may be found: http://www.asdar-book.org. The authors have taken part in writing and maintaining software for spatial data handling and analysis with R in concert since 2003.