Spatial Analysis and Modeling in Geographical Transformation Process
Spatial Analysis and Modeling in Geographical Transformation Process

Author: Yuji Murayama

Publisher: Springer Science & Business Media

Published: 2011-02-26

Total Pages: 301

ISBN-13: 9400706715

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Currently, spatial analysis is becoming more important than ever because enormous volumes of spatial data are available from different sources, such as GPS, Remote Sensing, and others. This book deals with spatial analysis and modelling. It provides a comprehensive discussion of spatial analysis, methods, and approaches related to human settlements and associated environment. Key contributions with empirical case studies from Iran, Philippines, Vietnam, Thailand, Nepal, and Japan that apply spatial analysis including autocorrelation, fuzzy, voronoi, cellular automata, analytic hierarchy process, artificial neural network, spatial metrics, spatial statistics, regression, and remote sensing mapping techniques are compiled comprehensively. The core value of this book is a wide variety of results with state of the art discussion including empirical case studies. It provides a milestone reference to students, researchers, planners, and other practitioners dealing the spatial problems on urban and regional issues. We are pleased to announce that this book has been presented with the 2011 publishing award from the GIS Association of Japan. We would like to congratulate the authors!

Spatial Analysis and Modeling in Geographical Transformation Process
Spatial Analysis and Modeling in Geographical Transformation Process

Author: Yuji Murayama

Publisher: Springer

Published: 2011-03-07

Total Pages: 302

ISBN-13: 9789400706729

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Currently, spatial analysis is becoming more important than ever because enormous volumes of spatial data are available from different sources, such as GPS, Remote Sensing, and others. This book deals with spatial analysis and modelling. It provides a comprehensive discussion of spatial analysis, methods, and approaches related to human settlements and associated environment. Key contributions with empirical case studies from Iran, Philippines, Vietnam, Thailand, Nepal, and Japan that apply spatial analysis including autocorrelation, fuzzy, voronoi, cellular automata, analytic hierarchy process, artificial neural network, spatial metrics, spatial statistics, regression, and remote sensing mapping techniques are compiled comprehensively. The core value of this book is a wide variety of results with state of the art discussion including empirical case studies. It provides a milestone reference to students, researchers, planners, and other practitioners dealing the spatial problems on urban and regional issues. We are pleased to announce that this book has been presented with the 2011 publishing award from the GIS Association of Japan. We would like to congratulate the authors!

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

Publisher: Elsevier

Published: 2019-01-18

Total Pages: 800

ISBN-13: 0128156953

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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

Models in Spatial Analysis
Models in Spatial Analysis

Author: Lena Sanders

Publisher: Wiley-ISTE

Published: 2007-05-25

Total Pages: 360

ISBN-13:

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This title provides a broad overview of the different types of models used in advanced spatial analysis. The models concern spatial organization, location factors and spatial interaction patterns from both static and dynamic perspectives. Each chapter gives a broad overview of the subject, covering both theoretical developments and practical applications. The advantages of an interdisciplinary approach are illustrated in the way that the viewpoint of each of the individual disciplines are brought together when considering questions relevant to spatial analysis. The authors of the chapters come from a range of different disciplines (geography, economy, hydrology, ecology, etc.) and are specialists in their field. They use a range of methods and modeling tools developed in mathematics, statistics, artificial intelligence and physics.

Spatial Analysis Methods and Practice
Spatial Analysis Methods and Practice

Author: George Grekousis

Publisher: Cambridge University Press

Published: 2020-06-11

Total Pages: 535

ISBN-13: 1108498981

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An introductory overview of spatial analysis and statistics through GIS, including worked examples and critical analysis of results.

Spatial Analysis, Modelling and Planning
Spatial Analysis, Modelling and Planning

Author: Jorge Rocha

Publisher: BoD – Books on Demand

Published: 2018-11-28

Total Pages: 270

ISBN-13: 1789842395

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New powerful technologies, such as geographic information systems (GIS), have been evolving and are quickly becoming part of a worldwide emergent digital infrastructure. Spatial analysis is becoming more important than ever because enormous volumes of spatial data are available from different sources, such as social media and mobile phones. When locational information is provided, spatial analysis researchers can use it to calculate statistical and mathematical relationships through time and space. This book aims to demonstrate how computer methods of spatial analysis and modeling, integrated in a GIS environment, can be used to better understand reality and give rise to more informed and, thus, improved planning. It provides a comprehensive discussion of spatial analysis, methods, and approaches related to planning.

Applied Spatial Data Analysis with R
Applied Spatial Data Analysis with R

Author: Roger S. Bivand

Publisher: Springer Science & Business Media

Published: 2013-06-21

Total Pages: 414

ISBN-13: 1461476186

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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.

Spatial Modeling and Assessment of Urban Form
Spatial Modeling and Assessment of Urban Form

Author: Biswajeet Pradhan

Publisher: Springer

Published: 2017-05-08

Total Pages: 337

ISBN-13: 3319542176

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This book discusses the application of Geospatial data, Geographic Information System (GIS) and Remote Sensing (RS) technologies in analysis and modeling of urban growth process, and its pattern, with special focus on sprawl and compact form of urban development. The book explains these two kinds of urban forms (sprawl and compact urban development) in detail regarding their advantages, disadvantages, indicators, assessment, modeling, implementation and their relationship with urban sustainability. It confirms that the proposed modeling approaches, geospatial data and GIS are very practical for identifying urban growth, land use change patterns and their general trends in future. The analyses and modeling approaches presented in this book can be employed to guide the identification and measurements of the changes and growth likely to happen in urban areas. In addition, this book can be helpful for town planning and development in order to design urban areas in a compact form and eventually sustainable manner.

Geographically Weighted Regression
Geographically Weighted Regression

Author: A. Stewart Fotheringham

Publisher: John Wiley & Sons

Published: 2003-02-21

Total Pages: 282

ISBN-13: 0470855258

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Geographical Weighted Regression (GWR) is a new local modelling technique for analysing spatial analysis. This technique allows local as opposed to global models of relationships to be measured and mapped. This is the first and only book on this technique, offering comprehensive coverage on this new 'hot' topic in spatial analysis. * Provides step-by-step examples of how to use the GWR model using data sets and examples on issues such as house price determinants, educational attainment levels and school performance statistics * Contains a broad discussion of and basic concepts on GWR through to ideas on statistical inference for GWR models * uniquely features accompanying author-written software that allows users to undertake sophisticated and complex forms of GWR within a user-friendly, Windows-based, front-end (see book for details).

Geospatial Analysis and Modelling of Urban Structure and Dynamics
Geospatial Analysis and Modelling of Urban Structure and Dynamics

Author: Bin Jiang

Publisher: Springer Science & Business Media

Published: 2010-06-16

Total Pages: 465

ISBN-13: 9048185726

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A Coming of Age: Geospatial Analysis and Modelling in the Early Twenty First Century Forty years ago when spatial analysis first emerged as a distinct theme within geography’s quantitative revolution, the focus was largely on consistent methods for measuring spatial correlation. The concept of spatial au- correlation took pride of place, mirroring concerns in time-series analysis about similar kinds of dependence known to distort the standard probability theory used to derive appropriate statistics. Early applications of spatial correlation tended to reflect geographical patterns expressed as points. The perspective taken on such analytical thinking was founded on induction, the search for pattern in data with a view to suggesting appropriate hypotheses which could subsequently be tested. In parallel but using very different techniques came the development of a more deductive style of analysis based on modelling and thence simulation. Here the focus was on translating prior theory into forms for generating testable predictions whose outcomes could be compared with observations about some system or phenomenon of interest. In the intervening years, spatial analysis has broadened to embrace both inductive and deductive approaches, often combining both in different mixes for the variety of problems to which it is now applied.