Spatial Data on the Web PDF Download

Author: Alberto Belussi
Publisher: Springer Science & Business Media
ISBN: 3540698787
Category : Computers
Languages : en
Pages : 316

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Book Description
This book focuses on the modeling and management of spatial data in distributed systems. The authors have structured the contributions from internationally renowned researchers into four parts. The book offers researchers an excellent overview of the state-of-the-art in modeling and management of spatial data in distributed environments, while it may also be the basis of specialized courses on Web-based geographical information systems.

Author: Michael John De Smith
Publisher: Troubador Publishing Ltd
ISBN: 1905886608
Category : Mathematics
Languages : en
Pages : 417

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Book Description
Addresses a range of analytical techniques that are provided within modern Geographic Information Systems and related geospatial software products. This guide covers: the principal concepts of geospatial analysis; core components of geospatial analysis; and, surface analysis, including surface form analysis, gridding and interpolation methods.

Author: Robin Lovelace
Publisher: CRC Press
ISBN: 1351396900
Category : Mathematics
Languages : en
Pages : 335

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Book Description
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.

Author: Roger S. Bivand
Publisher: Springer Science & Business Media
ISBN: 1461476186
Category : Medical
Languages : en
Pages : 414

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Book Description
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.

Author: Igor Ivan
Publisher: Springer
ISBN: 3319451235
Category : Science
Languages : en
Pages : 418

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Book Description
This edited volume gathers the proceedings of the Symposium GIS Ostrava 2016, the Rise of Big Spatial Data, held at the Technical University of Ostrava, Czech Republic, March 16–18, 2016. Combining theoretical papers and applications by authors from around the globe, it summarises the latest research findings in the area of big spatial data and key problems related to its utilisation. Welcome to dawn of the big data era: though it’s in sight, it isn’t quite here yet. Big spatial data is characterised by three main features: volume beyond the limit of usual geo-processing, velocity higher than that available using conventional processes, and variety, combining more diverse geodata sources than usual. The popular term denotes a situation in which one or more of these key properties reaches a point at which traditional methods for geodata collection, storage, processing, control, analysis, modelling, validation and visualisation fail to provide effective solutions. >Entering the era of big spatial data calls for finding solutions that address all “small data” issues that soon create “big data” troubles. Resilience for big spatial data means solving the heterogeneity of spatial data sources (in topics, purpose, completeness, guarantee, licensing, coverage etc.), large volumes (from gigabytes to terabytes and more), undue complexity of geo-applications and systems (i.e. combination of standalone applications with web services, mobile platforms and sensor networks), neglected automation of geodata preparation (i.e. harmonisation, fusion), insufficient control of geodata collection and distribution processes (i.e. scarcity and poor quality of metadata and metadata systems), limited analytical tool capacity (i.e. domination of traditional causal-driven analysis), low visual system performance, inefficient knowledge-discovery techniques (for transformation of vast amounts of information into tiny and essential outputs) and much more. These trends are accelerating as sensors become more ubiquitous around the world.

Author: Xiaofeng Meng
Publisher: Springer Nature
ISBN: 3030698734
Category : Computers
Languages : en
Pages : 296

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Book Description
This book constitutes the proceedings of the First International Conference on Spatial Data and Intelligence, SpatialDI 2020, which was held on May 8-9, 2020. The conference was planned to take place in Shenzhen, China, and changed to an online format due to the COVID-19 pandemic. The 21 full papers presented in this volume were carefully reviewed and selected from 50 submissions. They were organized in topical sections named: traffic management; data science; and visualization science.

Author: Zhao, Peisheng
Publisher: IGI Global
ISBN: 1609601947
Category : Computers
Languages : en
Pages : 552

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Book Description
As Web service technologies have matured in recent years, an increasing number of geospatial Web services designed to deal with spatial information over the network have emerged. Geospatial Web Services: Advances in Information Interoperability provides relevant theoretical frameworks and the latest empirical research findings and applications in the area. This book highlights the strategic role of geospatial Web services in a distributed heterogeneous environment and the life cycle of geospatial Web services for building interoperable geospatial applications.

Author: Brent Hall
Publisher: Springer Science & Business Media
ISBN: 3540748318
Category : Science
Languages : en
Pages : 285

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Book Description
The role open-source geospatial software plays in data handling within the spatial information technology industry is the overarching theme of the book. It also examines new tools and applications for those already using OS approaches to software development.

Author: Pinde Fu
Publisher: Esri Press
ISBN: 9781589487277
Category :
Languages : en
Pages : 0

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Book Description
Get the latest information about online GIS using ArcGIS(R) apps and functionality with Getting to Know Web GIS, fifth edition.

Author: Joseph J. Kerski
Publisher: ESRI Press
ISBN: 9781589482449
Category : Geospatial data
Languages : en
Pages : 0

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Book Description
Readers will understand how to find, evaluate, and analyze data to solve location-based problems. This guide covers practical issues such as copyrights, cloud computing, online data portals, volunteered geographic information, and international data with supplementary exercises.