Spatial Analysis Using Big Data

Spatial Analysis Using Big Data
Author: Yoshiki Yamagata,Hajime Seya
Publsiher: Academic Press
Total Pages: 302
Release: 2019-11-03
ISBN 10: 0128131322
ISBN 13: 9780128131329
Language: EN, FR, DE, ES & NL

Spatial Analysis Using Big Data Book Review:

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

Spatial Analysis Using Big Data

Spatial Analysis Using Big Data
Author: Yoshiki Yamagata,Hajime Seya
Publsiher: Academic Press
Total Pages: 300
Release: 2019-10
ISBN 10: 9780128131275
ISBN 13: 0128131276
Language: EN, FR, DE, ES & NL

Spatial Analysis Using Big Data Book Review:

Spatial Analysis using Big Data: Econometrical Methods and 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

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.

Spatial Data Handling in Big Data Era

Spatial Data Handling in Big Data Era
Author: Chenghu Zhou,Fenzhen Su,Francis Harvey,Jun Xu
Publsiher: Springer
Total Pages: 237
Release: 2017-05-04
ISBN 10: 9811044244
ISBN 13: 9789811044243
Language: EN, FR, DE, ES & NL

Spatial Data Handling in Big Data Era Book Review:

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.

Spatial Big Data Science

Spatial Big Data Science
Author: Zhe Jiang,Shashi Shekhar
Publsiher: Springer
Total Pages: 131
Release: 2017-07-13
ISBN 10: 3319601954
ISBN 13: 9783319601953
Language: EN, FR, DE, ES & NL

Spatial Big Data Science Book Review:

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.

Spatial Planning in the Big Data Revolution

Spatial Planning in the Big Data Revolution
Author: Voghera, Angioletta,La Riccia, Luigi
Publsiher: IGI Global
Total Pages: 359
Release: 2019-03-15
ISBN 10: 1522579281
ISBN 13: 9781522579281
Language: EN, FR, DE, ES & NL

Spatial Planning in the Big Data Revolution Book Review:

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.

Spatial Analysis

Spatial Analysis
Author: Tonny J. Oyana,Florence Margai
Publsiher: CRC Press
Total Pages: 323
Release: 2015-07-28
ISBN 10: 1498707645
ISBN 13: 9781498707640
Language: EN, FR, DE, ES & NL

Spatial Analysis Book Review:

An introductory text for the next generation of geospatial analysts and data scientists, Spatial Analysis: Statistics, Visualization, and Computational Methods focuses on the fundamentals of spatial analysis using traditional, contemporary, and computational methods. Outlining both non-spatial and spatial statistical concepts, the authors present practical applications of geospatial data tools, techniques, and strategies in geographic studies. They offer a problem-based learning (PBL) approach to spatial analysis—containing hands-on problem-sets that can be worked out in MS Excel or ArcGIS—as well as detailed illustrations and numerous case studies. The book enables readers to: Identify types and characterize non-spatial and spatial data Demonstrate their competence to explore, visualize, summarize, analyze, optimize, and clearly present statistical data and results Construct testable hypotheses that require inferential statistical analysis Process spatial data, extract explanatory variables, conduct statistical tests, and explain results Understand and interpret spatial data summaries and statistical tests Spatial Analysis: Statistics, Visualization, and Computational Methods incorporates traditional statistical methods, spatial statistics, visualization, and computational methods and algorithms to provide a concept-based problem-solving learning approach to mastering practical spatial analysis. Topics covered include: spatial descriptive methods, hypothesis testing, spatial regression, hot spot analysis, geostatistics, spatial modeling, and data science.

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.

Spatial Big Data BIM and advanced GIS for Smart Transformation

Spatial Big Data  BIM and advanced GIS for Smart Transformation
Author: Sara Shirowzhan,Willie Tan,Samad M. E. Sepasgozar
Publsiher: MDPI
Total Pages: 166
Release: 2020-12-02
ISBN 10: 3039360302
ISBN 13: 9783039360307
Language: EN, FR, DE, ES & NL

Spatial Big Data BIM and advanced GIS for Smart Transformation Book Review:

This book covers a range of topics including selective technologies and algorithms that can potentially contribute to developing an intelligent environment and smarter cities. While the connectivity and efficiency of smart cities is important, the analysis of the impact of construction development and large projects in the city is crucial to decision and policy makers, before the project is approved. This book also presents an agenda for future investigations to address the need for advanced tools such as mobile scanners, Geospatial Artificial Intelligence, Unmanned Aerial Vehicles, Geospatial Augmented Reality apps, Light Detection, and Ranging in smart cities. Some of selected specific tools presented in this book are as a simulator for improving the smart parking practices by modelling drivers with activity plans, a bike optimization algorithm to increase the efficiency of bike stations, an agent-based model simulation of human mobility with the use of mobile phone datasets. In addition, this book describes the use of numerical methods to match the network demand and supply of bicycles, investigate the distribution of railways using different indicators, presents a novel algorithm of direction-aware continuous moving K-nearest neighbor queries in road networks, and presents an efficient staged evacuation planning algorithm for multi-exit buildings.

Applied Spatial Statistics and Econometrics

Applied Spatial Statistics and Econometrics
Author: Katarzyna Kopczewska
Publsiher: Routledge
Total Pages: 594
Release: 2020-11-26
ISBN 10: 1000079783
ISBN 13: 9781000079784
Language: EN, FR, DE, ES & NL

Applied Spatial Statistics and Econometrics Book Review:

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.

Modern Technologies for Big Data Classification and Clustering

Modern Technologies for Big Data Classification and Clustering
Author: Seetha, Hari,Murty, M. Narasimha,Tripathy, B. K.
Publsiher: IGI Global
Total Pages: 360
Release: 2017-07-12
ISBN 10: 1522528067
ISBN 13: 9781522528067
Language: EN, FR, DE, ES & NL

Modern Technologies for Big Data Classification and Clustering Book Review:

Data has increased due to the growing use of web applications and communication devices. It is necessary to develop new techniques of managing data in order to ensure adequate usage. Modern Technologies for Big Data Classification and Clustering is an essential reference source for the latest scholarly research on handling large data sets with conventional data mining and provide information about the new technologies developed for the management of large data. Featuring coverage on a broad range of topics such as text and web data analytics, risk analysis, and opinion mining, this publication is ideally designed for professionals, researchers, and students seeking current research on various concepts of big data analytics.

Spatial Analysis with R

Spatial Analysis with R
Author: Tonny J. Oyana
Publsiher: CRC Press
Total Pages: 334
Release: 2020-09-01
ISBN 10: 100017347X
ISBN 13: 9781000173475
Language: EN, FR, DE, ES & NL

Spatial Analysis with R Book Review:

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.

Hierarchical Modeling and Analysis for Spatial Data

Hierarchical Modeling and Analysis for Spatial Data
Author: Sudipto Banerjee
Publsiher: CRC Press
Total Pages: 472
Release: 2003-12-17
ISBN 10: 020348780X
ISBN 13: 9780203487808
Language: EN, FR, DE, ES & NL

Hierarchical Modeling and Analysis for Spatial Data Book Review:

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,

Big Data for Regional Science

Big Data for Regional Science
Author: Laurie A Schintler,Zhenhua Chen
Publsiher: Routledge
Total Pages: 350
Release: 2017-08-07
ISBN 10: 1351983253
ISBN 13: 9781351983259
Language: EN, FR, DE, ES & NL

Big Data for Regional Science Book Review:

Recent technological advancements and other related factors and trends are contributing to the production of an astoundingly large and rapidly accelerating collection of data, or ‘Big Data’. This data now allows us to examine urban and regional phenomena in ways that were previously not possible. Despite the tremendous potential of big data for regional science, its use and application in this context is fraught with issues and challenges. This book brings together leading contributors to present an interdisciplinary, agenda-setting and action-oriented platform for research and practice in the urban and regional community. This book provides a comprehensive, multidisciplinary and cutting-edge perspective on big data for regional science. Chapters contain a collection of research notes contributed by experts from all over the world with a wide array of disciplinary backgrounds. The content is organized along four themes: sources of big data; integration, processing and management of big data; analytics for big data; and, higher level policy and programmatic considerations. As well as concisely and comprehensively synthesising work done to date, the book also considers future challenges and prospects for the use of big data in regional science. Big Data for Regional Science provides a seminal contribution to the field of regional science and will appeal to a broad audience, including those at all levels of academia, industry, and government.

Urban Analytics

Urban Analytics
Author: Alex D. Singleton,Seth Spielman,David Folch
Publsiher: SAGE
Total Pages: 200
Release: 2017-11-27
ISBN 10: 1526418592
ISBN 13: 9781526418593
Language: EN, FR, DE, ES & NL

Urban Analytics Book Review:

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.

Distributed and Parallel Architectures for Spatial Data

Distributed and Parallel Architectures for Spatial Data
Author: Alberto Belussi,Sara Migliorini
Publsiher: MDPI
Total Pages: 170
Release: 2021-01-20
ISBN 10: 3039367501
ISBN 13: 9783039367504
Language: EN, FR, DE, ES & NL

Distributed and Parallel Architectures for Spatial Data Book Review:

This book aims at promoting new and innovative studies, proposing new architectures or innovative evolutions of existing ones, and illustrating experiments on current technologies in order to improve the efficiency and effectiveness of distributed and cluster systems when they deal with spatiotemporal data.

Spatial Analysis Modelling and Planning

Spatial Analysis  Modelling and Planning
Author: Jorge Rocha,José António Tenedório
Publsiher: BoD – Books on Demand
Total Pages: 268
Release: 2018-11-28
ISBN 10: 1789842395
ISBN 13: 9781789842395
Language: EN, FR, DE, ES & NL

Spatial Analysis Modelling and Planning Book Review:

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.

Archaeological Spatial Analysis

Archaeological Spatial Analysis
Author: Mark Gillings,Piraye Hacıgüzeller,Gary Lock
Publsiher: Routledge
Total Pages: 484
Release: 2020-01-16
ISBN 10: 1351243845
ISBN 13: 9781351243841
Language: EN, FR, DE, ES & NL

Archaeological Spatial Analysis Book Review:

Effective spatial analysis is an essential element of archaeological research; this book is a unique guide to choosing the appropriate technique, applying it correctly and understanding its implications both theoretically and practically. Focusing upon the key techniques used in archaeological spatial analysis, this book provides the authoritative, yet accessible, methodological guide to the subject which has thus far been missing from the corpus. Each chapter tackles a specific technique or application area and follows a clear and coherent structure. First is a richly referenced introduction to the particular technique, followed by a detailed description of the methodology, then an archaeological case study to illustrate the application of the technique, and conclusions that point to the implications and potential of the technique within archaeology. The book is designed to function as the main textbook for archaeological spatial analysis courses at undergraduate and post-graduate level, while its user-friendly structure makes it also suitable for self-learning by archaeology students as well as researchers and professionals.

Spatial Analysis Modelling and Planning

Spatial Analysis  Modelling and Planning
Author: Jorge Rocha,José António Tenedório
Publsiher: BoD – Books on Demand
Total Pages: 268
Release: 2018-11-28
ISBN 10: 1789842395
ISBN 13: 9781789842395
Language: EN, FR, DE, ES & NL

Spatial Analysis Modelling and Planning Book Review:

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.

The Rise of Big Spatial Data

The Rise of Big Spatial Data
Author: Igor Ivan,Alex Singleton,Jiří Horák,Tomáš Inspektor
Publsiher: Springer
Total Pages: 408
Release: 2016-10-14
ISBN 10: 3319451235
ISBN 13: 9783319451237
Language: EN, FR, DE, ES & NL

The Rise of Big Spatial Data Book Review:

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.