Spatial Analysis Using Big Data

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Spatial Analysis Using Big Data

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Author : Yoshiki Yamagata
language : en
Publisher: Academic Press
Release Date : 2019-11-03

Spatial Analysis Using Big Data written by Yoshiki Yamagata and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-03 with Business & Economics categories.

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

Big Data Computing For Geospatial Applications

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Author : Zhenlong Li
language : en
Publisher:
Release Date : 2020

Big Data Computing For Geospatial Applications written by Zhenlong Li and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.

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.

Geographical Data Science And Spatial Data Analysis

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Author : Lex Comber
language : en
Publisher: SAGE
Release Date : 2020-12-02

Geographical Data Science And Spatial Data Analysis written by Lex Comber and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-02 with Science categories.

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 Analysis With R

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Author : Tonny J. Oyana
language : en
Publisher: CRC Press
Release Date : 2023-09-25

Spatial Analysis With R written by Tonny J. Oyana and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-25 with categories.

This 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. It includes the implementation of new tools for spatial analysis using R.

Spatial Econometrics And Spatial Statistics

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Author : A. Getis
language : en
Publisher: Palgrave Macmillan
Release Date : 2004-02-24

Spatial Econometrics And Spatial Statistics written by A. Getis and has been published by Palgrave Macmillan this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-02-24 with Education categories.

The field of spatial econometrics has come to include the methods and models that deal with estimation and testing problems encountered when attempting to implement regional economic models. Those problems are often characterized by the difficulties associated with assessing the importance of spatial dependence and spatial heterogeneity. This book includes contributions on spatial proximity, spatial patterning and in particular the spatial association (dependence) contained in local map patterns.

Big Data For Regional Science

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Author : Laurie A Schintler
language : en
Publisher: Routledge
Release Date : 2017-08-07

Big Data For Regional Science written by Laurie A Schintler and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-08-07 with Business & Economics categories.

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.

Hierarchical Modeling And Analysis For Spatial Data

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Author : Sudipto Banerjee
language : en
Publisher: CRC Press
Release Date : 2003-12-17

Hierarchical Modeling And Analysis For Spatial Data written by Sudipto Banerjee and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-12-17 with Mathematics categories.

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 Analysis

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Author : Tonny J. Oyana
language : en
Publisher: CRC Press
Release Date : 2015-07-28

Spatial Analysis written by Tonny J. Oyana and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07-28 with Mathematics categories.

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 p

Spatial Data Mining

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Author : Deren Li
language : en
Publisher: Springer
Release Date : 2016-03-23

Spatial Data Mining written by Deren Li and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-03-23 with Computers categories.

· 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’.

An Introduction To R For Spatial Analysis And Mapping

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Author : Chris Brunsdon
language : en
Publisher: SAGE
Release Date : 2014-04-30

An Introduction To R For Spatial Analysis And Mapping written by Chris Brunsdon and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-04-30 with Social Science categories.

"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.