Spatial Analysis Using Big Data

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

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  • Author : Yoshiki Yamagata
  • Publisher : Academic Press
  • Pages : 302 pages
  • ISBN : 0128131322
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKSpatial Analysis Using Big Data

Spatial Analysis Using Big Data

Spatial Analysis Using Big Data
  • Author : Yoshiki Yamagata,Hajime Seya
  • Publisher : Academic Press
  • Release : 03 November 2019
GET THIS BOOKSpatial Analysis Using Big Data

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

Spatial Data Handling in Big Data Era

Spatial Data Handling in Big Data Era
  • Author : Chenghu Zhou,Fenzhen Su,Francis Harvey,Jun Xu
  • Publisher : Springer
  • Release : 04 May 2017
GET THIS BOOKSpatial Data Handling in Big Data Era

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

Big Data Applications in Geography and Planning

Big Data Applications in Geography and Planning
  • Author : Mark Birkin,Graham Clarke,Jonathan Corcoran,Robert Stimson
  • Publisher : Edward Elgar Publishing
  • Release : 28 May 2021
GET THIS BOOKBig Data Applications in Geography and Planning

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.

Applied Spatial Statistics and Econometrics

Applied Spatial Statistics and Econometrics
  • Author : Katarzyna Kopczewska
  • Publisher : Routledge
  • Release : 26 November 2020
GET THIS BOOKApplied Spatial Statistics and Econometrics

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

Spatial Planning in the Big Data Revolution

Spatial Planning in the Big Data Revolution
  • Author : Voghera, Angioletta,La Riccia, Luigi
  • Publisher : IGI Global
  • Release : 15 March 2019
GET THIS BOOKSpatial Planning in the Big Data Revolution

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

An Introduction to R for Spatial Analysis and Mapping

An Introduction to R for Spatial Analysis and Mapping
  • Author : Chris Brunsdon,Lex Comber
  • Publisher : SAGE
  • Release : 10 December 2018
GET THIS BOOKAn Introduction to R for Spatial Analysis and Mapping

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;

Spatial Big Data Science

Spatial Big Data Science
  • Author : Zhe Jiang,Shashi Shekhar
  • Publisher : Springer
  • Release : 13 July 2017
GET THIS BOOKSpatial Big Data Science

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

Geographical Data Science and Spatial Data Analytics in R

Geographical Data Science and Spatial Data Analytics in R
  • Author : Lex Comber,Chris Brunsdon
  • Publisher : Spatial Analytics and GIS
  • Release : 09 January 2021
GET THIS BOOKGeographical Data Science and Spatial Data Analytics in R

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

Spatial Analysis Using Big Data

Spatial Analysis Using Big Data
  • Author : Yoshiki Yamagata,Hajime Seya
  • Publisher : Academic Press
  • Release : 01 October 2019
GET THIS BOOKSpatial Analysis Using Big Data

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

Spatial Analysis with R

Spatial Analysis with R
  • Author : Tonny J. Oyana
  • Publisher : CRC Press
  • Release : 01 September 2020
GET THIS BOOKSpatial Analysis with R

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

Distributed and Parallel Architectures for Spatial Data

Distributed and Parallel Architectures for Spatial Data
  • Author : Alberto Belussi,Sara Migliorini
  • Publisher : MDPI
  • Release : 20 January 2021
GET THIS BOOKDistributed and Parallel Architectures for Spatial Data

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.

Hierarchical Modeling and Analysis for Spatial Data

Hierarchical Modeling and Analysis for Spatial Data
  • Author : Sudipto Banerjee
  • Publisher : CRC Press
  • Release : 17 December 2003
GET THIS BOOKHierarchical Modeling and Analysis for Spatial Data

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,

Public Policy Analytics

Public Policy Analytics
  • Author : Ken Steif
  • Publisher : CRC Press
  • Release : 19 August 2021
GET THIS BOOKPublic Policy Analytics

Public Policy Analytics: Code & Context for Data Science in Government teaches readers how to address complex public policy problems with data and analytics using reproducible methods in R. Each of the eight chapters provides a detailed case study, showing readers: how to develop exploratory indicators; understand ‘spatial process’ and develop spatial analytics; how to develop ‘useful’ predictive analytics; how to convey these outputs to non-technical decision-makers through the medium of data visualization; and why, ultimately, data science and ‘Planning’ are

The ArcGIS Book

The ArcGIS Book
  • Author : Christian Harder,Clint Brown
  • Publisher : ESRI Press
  • Release : 29 June 2022
GET THIS BOOKThe ArcGIS Book

This is a hands-on book about ArcGIS that you work with as much as read. By the end, using Learn ArcGIS lessons, you'll be able to say you made a story map, conducted geographic analysis, edited geographic data, worked in a 3D web scene, built a 3D model of Venice, and more.

Data-centric Regenerative Built Environment

Data-centric Regenerative Built Environment
  • Author : Saeed Banihashemi,Sepideh Zarepour Sohi
  • Publisher : Routledge
  • Release : 18 March 2022
GET THIS BOOKData-centric Regenerative Built Environment

This book examines the use of big data in regenerative urban environment and how data helps in functional planning and design solutions. This book is one of the first endeavors to present the data-driven methods for regenerative built environments and integrate it with the novel design solutions. It looks at four specific areas in which data is used – urban land use, transportation and traffic, environmental concerns and social issues – and draws on the theoretical literature concerning regenerative built environments to