Spatial Analysis Using Big Data

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Spatial Analysis Using Big Data

Author : Yoshiki Yamagata
Publisher : Academic Press
ISBN 13 : 9780128131275
Total Pages : 0 pages
Book Rating : 4.1/5 (312 download)

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Book Synopsis Spatial Analysis Using Big Data by : Yoshiki Yamagata

Download or read book Spatial Analysis Using Big Data written by Yoshiki Yamagata and published by Academic Press. This book was released on 2019-11-02 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spatial Analysis Using Big Data: Methods and Urban Applications helps readers understand the most powerful, state-of-the-art spatial econometric methods, focusing particularly on urban research problems. The methods represent a cluster of potentially transformational socio-economic modeling tools that allow researchers to capture real-time and high-resolution information to potentially reveal new socioeconomic dynamics within urban populations. Each method, written by leading exponents of the discipline, uses real-time urban big data to solve research problems in spatial science. Urban applications of these methods are provided in unsurpassed depth, with chapters on surface temperature mapping, view value analysis, community clustering and spatial-social networks, among many others.

Geographical Data Science and Spatial Data Analysis

Author : Lex Comber
Publisher : SAGE
ISBN 13 : 1526485435
Total Pages : 417 pages
Book Rating : 4.5/5 (264 download)

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Book Synopsis Geographical Data Science and Spatial Data Analysis by : Lex Comber

Download or read book Geographical Data Science and Spatial Data Analysis written by Lex Comber and published by SAGE. This book was released on 2020-12-02 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 (i.e. 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’ textbook, 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.

Spatial Big Data Science

Author : Zhe Jiang
Publisher : Springer
ISBN 13 : 3319601954
Total Pages : 138 pages
Book Rating : 4.3/5 (196 download)

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Book Synopsis Spatial Big Data Science by : Zhe Jiang

Download or read book Spatial Big Data Science written by Zhe Jiang and published by Springer. This book was released on 2017-07-13 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: Emerging Spatial Big Data (SBD) has transformative potential in solving many grand societal challenges such as water resource management, food security, disaster response, and transportation. However, significant computational challenges exist in analyzing SBD due to the unique spatial characteristics including spatial autocorrelation, anisotropy, heterogeneity, multiple scales and resolutions which is illustrated in this book. This book also discusses current techniques for, spatial big data science with a particular focus on classification techniques for earth observation imagery big data. Specifically, the authors introduce several recent spatial classification techniques, such as spatial decision trees and spatial ensemble learning. Several potential future research directions are also discussed. This book targets an interdisciplinary audience including computer scientists, practitioners and researchers working in the field of data mining, big data, as well as domain scientists working in earth science (e.g., hydrology, disaster), public safety and public health. Advanced level students in computer science will also find this book useful as a reference.

Big Data Computing for Geospatial Applications

Author : Zhenlong Li
Publisher : MDPI
ISBN 13 : 3039432443
Total Pages : 222 pages
Book Rating : 4.0/5 (394 download)

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Book Synopsis Big Data Computing for Geospatial Applications by : Zhenlong Li

Download or read book Big Data Computing for Geospatial Applications written by Zhenlong Li and published by MDPI. This book was released on 2020-11-23 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: The convergence of big data and geospatial computing has brought forth challenges and opportunities to Geographic Information Science with regard to geospatial data management, processing, analysis, modeling, and visualization. This book highlights recent advancements in integrating new computing approaches, spatial methods, and data management strategies to tackle geospatial big data challenges and meanwhile demonstrates opportunities for using big data for geospatial applications. Crucial to the advancements highlighted in this book is the integration of computational thinking and spatial thinking and the transformation of abstract ideas and models to concrete data structures and algorithms.

Spatial Analysis Using Big Data

Author : Yoshiki Yamagata
Publisher : Academic Press
ISBN 13 : 0128131322
Total Pages : 304 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Spatial Analysis Using Big Data by : Yoshiki Yamagata

Download or read book Spatial Analysis Using Big Data written by Yoshiki Yamagata and published by Academic Press. This book was released on 2019-11-03 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spatial Analysis Using Big Data: Methods and Urban Applications helps readers understand the most powerful, state-of-the-art spatial econometric methods, focusing particularly on urban research problems. The methods represent a cluster of potentially transformational socio-economic modeling tools that allow researchers to capture real-time and high-resolution information to potentially reveal new socioeconomic dynamics within urban populations. Each method, written by leading exponents of the discipline, uses real-time urban big data to solve research problems in spatial science. Urban applications of these methods are provided in unsurpassed depth, with chapters on surface temperature mapping, view value analysis, community clustering and spatial-social networks, among many others. - Reviews some of the most powerful and challenging modern methods to study big data problems in spatial science - Provides computer codes written in R, MATLAB and Python to help implement methods - Applies these methods to common problems observed in urban and regional economics

Urban Analytics

Author : Alex D. Singleton
Publisher : SAGE
ISBN 13 : 1526418592
Total Pages : 222 pages
Book Rating : 4.5/5 (264 download)

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Book Synopsis Urban Analytics by : Alex D. Singleton

Download or read book Urban Analytics written by Alex D. Singleton and published by SAGE. This book was released on 2017-11-27 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: The economic and political situation of cities has shifted in recent years in light of rapid growth amidst infrastructure decline, the suburbanization of poverty and inner city revitalization. At the same time, the way that data are used to understand urban systems has changed dramatically. Urban Analytics offers a field-defining look at the challenges and opportunities of using new and emerging data to study contemporary and future cities through methods including GIS, Remote Sensing, Big Data and Geodemographics. Written in an accessible style and packed with illustrations and interviews from key urban analysts, this is a groundbreaking new textbook for students of urban planning, urban design, geography, and the information sciences.

Spatial Data Handling in Big Data Era

Author : Chenghu Zhou
Publisher : Springer
ISBN 13 : 9811044244
Total Pages : 239 pages
Book Rating : 4.8/5 (11 download)

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Book Synopsis Spatial Data Handling in Big Data Era by : Chenghu Zhou

Download or read book Spatial Data Handling in Big Data Era written by Chenghu Zhou and published by Springer. This book was released on 2017-05-04 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: This proceedings volume introduces recent work on the storage, retrieval and visualization of spatial Big Data, data-intensive geospatial computing and related data quality issues. Further, it addresses traditional topics such as multi-scale spatial data representations, knowledge discovery, space-time modeling, and geological applications. Spatial analysis and data mining are increasingly facing the challenges of Big Data as more and more types of crowd sourcing spatial data are used in GIScience, such as movement trajectories, cellular phone calls, and social networks. In order to effectively manage these massive data collections, new methods and algorithms are called for. The book highlights state-of-the-art advances in the handling and application of spatial data, especially spatial Big Data, offering a cutting-edge reference guide for graduate students, researchers and practitioners in the field of GIScience.

The Rise of Big Spatial Data

Author : Igor Ivan
Publisher : Springer
ISBN 13 : 3319451235
Total Pages : 418 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis The Rise of Big Spatial Data by : Igor Ivan

Download or read book The Rise of Big Spatial Data written by Igor Ivan and published by Springer. This book was released on 2016-10-14 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Spatial Analysis with R

Author : Tonny J. Oyana
Publisher : CRC Press
ISBN 13 : 100017347X
Total Pages : 304 pages
Book Rating : 4.0/5 (1 download)

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Book Synopsis Spatial Analysis with R by : Tonny J. Oyana

Download or read book Spatial Analysis with R written by Tonny J. Oyana and published by CRC Press. This book was released on 2020-08-31 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the five years since the publication of the first edition of Spatial Analysis: Statistics, Visualization, and Computational Methods, many new developments have taken shape regarding the implementation of new tools and methods for spatial analysis with R. The use and growth of artificial intelligence, machine learning and deep learning algorithms with a spatial perspective, and the interdisciplinary use of spatial analysis are all covered in this second edition along with traditional statistical methods and algorithms to provide a concept-based problem-solving learning approach to mastering practical spatial analysis. Spatial Analysis with R: Statistics, Visualization, and Computational Methods, Second Edition provides a balance between concepts and practicums of spatial statistics with a comprehensive coverage of the most important approaches to understand spatial data, analyze spatial relationships and patterns, and predict spatial processes. New in the Second Edition: Includes new practical exercises and worked-out examples using R Presents a wide range of hands-on spatial analysis worktables and lab exercises All chapters are revised and include new illustrations of different concepts using data from environmental and social sciences Expanded material on spatiotemporal methods, visual analytics methods, data science, and computational methods Explains big data, data management, and data mining This second edition of an established textbook, with new datasets, insights, excellent illustrations, and numerous examples with R, is perfect for senior undergraduate and first-year graduate students in geography and the geosciences.

Applied Spatial Data Analysis with R

Author : Roger S. Bivand
Publisher : Springer Science & Business Media
ISBN 13 : 1461476186
Total Pages : 414 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Applied Spatial Data Analysis with R by : Roger S. Bivand

Download or read book Applied Spatial Data Analysis with R written by Roger S. Bivand and published by Springer Science & Business Media. This book was released on 2013-06-21 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Geospatial Data Analytics and Urban Applications

Author : Sandeep Narayan Kundu
Publisher : Springer Nature
ISBN 13 : 9811676496
Total Pages : 197 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Geospatial Data Analytics and Urban Applications by : Sandeep Narayan Kundu

Download or read book Geospatial Data Analytics and Urban Applications written by Sandeep Narayan Kundu and published by Springer Nature. This book was released on 2022-01-03 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights advanced applications of geospatial data analytics to address real-world issues in urban society. With a connected world, we are generating spatial at unprecedented rates which can be harnessed for insightful analytics which define the way we analyze past events and define the future directions. This book is an anthology of applications of spatial data and analytics performed on them for gaining insights which can be used for problem solving in an urban setting. Each chapter is contributed by spatially aware data scientists in the making who present spatial perspectives drawn on spatial big data. The book shall benefit mature researchers and student alike to discourse a variety of urban applications which display the use of machine learning algorithms on spatial big data for real-world problem solving.

Big Data Applications in Geography and Planning

Author : Graham Clarke
Publisher : Edward Elgar Publishing
ISBN 13 : 9781789909784
Total Pages : 480 pages
Book Rating : 4.9/5 (97 download)

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Book Synopsis Big Data Applications in Geography and Planning by : Graham Clarke

Download or read book Big Data Applications in Geography and Planning written by Graham Clarke and published by Edward Elgar Publishing. This book was released on 2021-05-28 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique book demonstrates the utility of big data approaches in human geography and planning. Offering a carefully curated selection of case studies, it reveals how researchers are accessing big data, what this data looks like and how such data can offer new and important insights and knowledge. Contributions from key scholars working in the field bring together an international series of case studies on demography and migration, retail and consumer analytics, health care planning, urban planning and transport studies. Chapters also discuss how data sets leveraged from commercial and public agency sources can greatly improve the data traditionally worked with in academic geography, regional science and planning. While addressing the challenges and limitations of big data, the book also demonstrates the usefulness of data sets held by commercial agencies and explores data linkage between big data and traditional public domain data sources. Focusing on the applications of big data to investigate issues in a spatial context, this book will be an essential guide for scholars and students of planning, mobility and human geography, particularly those who specialise in economic and transport geography. Its use of key case studies to demonstrate the applications of big data analytics in planning will also be useful for planners in these fields.

Applied Spatial Statistics and Econometrics

Author : Katarzyna Kopczewska
Publisher : Routledge
ISBN 13 : 1000079783
Total Pages : 760 pages
Book Rating : 4.0/5 ( download)

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Book Synopsis Applied Spatial Statistics and Econometrics by : Katarzyna Kopczewska

Download or read book Applied Spatial Statistics and Econometrics written by Katarzyna Kopczewska and published by Routledge. This book was released on 2020-11-25 with total page 760 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook is a comprehensive introduction to applied spatial data analysis using R. Each chapter walks the reader through a different method, explaining how to interpret the results and what conclusions can be drawn. The author team showcases key topics, including unsupervised learning, causal inference, spatial weight matrices, spatial econometrics, heterogeneity and bootstrapping. It is accompanied by a suite of data and R code on Github to help readers practise techniques via replication and exercises. This text will be a valuable resource for advanced students of econometrics, spatial planning and regional science. It will also be suitable for researchers and data scientists working with spatial data.

Spatial Planning in the Big Data Revolution

Author : Voghera, Angioletta
Publisher : IGI Global
ISBN 13 : 1522579281
Total Pages : 394 pages
Book Rating : 4.5/5 (225 download)

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Book Synopsis Spatial Planning in the Big Data Revolution by : Voghera, Angioletta

Download or read book Spatial Planning in the Big Data Revolution written by Voghera, Angioletta and published by IGI Global. This book was released on 2019-03-15 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: Through interaction with other databases such as social media, geographic information systems have the ability to build and obtain not only statistics defined on the flows of people, things, and information but also on perceptions, impressions, and opinions about specific places, territories, and landscapes. It is thus necessary to systematize, integrate, and coordinate the various sources of data (especially open data) to allow more appropriate and complete analysis, descriptions, and elaborations. Spatial Planning in the Big Data Revolution is a critical scholarly resource that aims to bring together different methodologies that combine the potential of large data analysis with GIS applications in dedicated tools specifically for territorial, social, economic, environmental, transport, energy, real estate, and landscape evaluation. Additionally, the book addresses a number of fundamental objectives including the application of big data analysis in supporting territorial analysis, validating crowdsourcing and crowdmapping techniques, and disseminating information and community involvement. Urban planners, architects, researchers, academicians, professionals, and practitioners in such fields as computer science, data science, and business intelligence will benefit most from the research contained within this publication.

An Introduction to R for Spatial Analysis and Mapping

Author : Chris Brunsdon
Publisher : SAGE
ISBN 13 : 1473911192
Total Pages : 386 pages
Book Rating : 4.4/5 (739 download)

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Book Synopsis An Introduction to R for Spatial Analysis and Mapping by : Chris Brunsdon

Download or read book An Introduction to R for Spatial Analysis and Mapping written by Chris Brunsdon and published by SAGE. This book was released on 2014-04-30 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: "In an age of big data, data journalism and with a wealth of quantitative information around us, it is not enough for students to be taught only 100 year old statistical methods using ′out of the box′ software. They need to have 21st-century analytical skills too. This is an excellent and student-friendly text from two of the world leaders in the teaching and development of spatial analysis. It shows clearly why the open source software R is not just an alternative to commercial GIS, it may actually be the better choice for mapping, analysis and for replicable research. Providing practical tips as well as fully working code, this is a practical ′how to′ guide ideal for undergraduates as well as those using R for the first time. It will be required reading on my own courses." - Richard Harris, Professor of Quantitative Social Science, University of Bristol R is a powerful open source computing tool that supports geographical analysis and mapping for the many geography and ‘non-geography’ students and researchers interested in spatial analysis and mapping. This book provides an introduction to the use of R for spatial statistical analysis, geocomputation and the analysis of geographical information for researchers collecting and using data with location attached, largely through increased GPS functionality. Brunsdon and Comber take readers from ‘zero to hero’ in spatial analysis and mapping through functions they have developed and compiled into R packages. This enables practical R applications in GIS, spatial analyses, spatial statistics, mapping, and web-scraping. Each chapter includes: Example data and commands for exploring it Scripts and coding to exemplify specific functionality Advice for developing greater understanding - through functions such as locator(), View(), and alternative coding to achieve the same ends Self-contained exercises for students to work through Embedded code within the descriptive text. This is a definitive ′how to′ that takes students - of any discipline - from coding to actual applications and uses of R.

Hierarchical Modeling and Analysis for Spatial Data

Author : Sudipto Banerjee
Publisher : CRC Press
ISBN 13 : 020348780X
Total Pages : 470 pages
Book Rating : 4.2/5 (34 download)

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Book Synopsis Hierarchical Modeling and Analysis for Spatial Data by : Sudipto Banerjee

Download or read book Hierarchical Modeling and Analysis for Spatial Data written by Sudipto Banerjee and published by CRC Press. This book was released on 2003-12-17 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: Among the many uses of hierarchical modeling, their application to the statistical analysis of spatial and spatio-temporal data from areas such as epidemiology And environmental science has proven particularly fruitful. Yet to date, the few books that address the subject have been either too narrowly focused on specific aspects of spatial analysis,

Spatial Data Mining

Author : Deren Li
Publisher : Springer
ISBN 13 : 3662485389
Total Pages : 329 pages
Book Rating : 4.6/5 (624 download)

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Book Synopsis Spatial Data Mining by : Deren Li

Download or read book Spatial Data Mining written by Deren Li and published by Springer. This book was released on 2016-03-23 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: · This book is an updated version of a well-received book previously published in Chinese by Science Press of China (the first edition in 2006 and the second in 2013). It offers a systematic and practical overview of spatial data mining, which combines computer science and geo-spatial information science, allowing each field to profit from the knowledge and techniques of the other. To address the spatiotemporal specialties of spatial data, the authors introduce the key concepts and algorithms of the data field, cloud model, mining view, and Deren Li methods. The data field method captures the interactions between spatial objects by diffusing the data contribution from a universe of samples to a universe of population, thereby bridging the gap between the data model and the recognition model. The cloud model is a qualitative method that utilizes quantitative numerical characters to bridge the gap between pure data and linguistic concepts. The mining view method discriminates the different requirements by using scale, hierarchy, and granularity in order to uncover the anisotropy of spatial data mining. The Deren Li method performs data preprocessing to prepare it for further knowledge discovery by selecting a weight for iteration in order to clean the observed spatial data as much as possible. In addition to the essential algorithms and techniques, the book provides application examples of spatial data mining in geographic information science and remote sensing. The practical projects include spatiotemporal video data mining for protecting public security, serial image mining on nighttime lights for assessing the severity of the Syrian Crisis, and the applications in the government project ‘the Belt and Road Initiatives’.