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Spatial Analysis Using Big Data

2019-11-02 Business & Economics
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Release : 2019-11-02
Genre : Business & Economics
Kind : eBook
Book Rating : 275/5 ( reviews)

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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. This book was released on 2019-11-02. 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.

Spatial Big Data Science

2017-07-13 Computers
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Release : 2017-07-13
Genre : Computers
Kind : eBook
Book Rating : 954/5 ( reviews)

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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. This book was released on 2017-07-13. 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

2020-11-23 Science
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Release : 2020-11-23
Genre : Science
Kind : eBook
Book Rating : 443/5 ( reviews)

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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. This book was released on 2020-11-23. 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

2019-11-03 Business & Economics
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Release : 2019-11-03
Genre : Business & Economics
Kind : eBook
Book Rating : 322/5 ( reviews)

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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. This book was released on 2019-11-03. 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

Geographical Data Science and Spatial Data Analysis

2020-12-02 Science
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Release : 2020-12-02
Genre : Science
Kind : eBook
Book Rating : 435/5 ( reviews)

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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. This book was released on 2020-12-02. 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.

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