9781526449368-1526449366-Geographical Data Science and Spatial Data Analysis: An Introduction in R (Spatial Analytics and GIS)

Geographical Data Science and Spatial Data Analysis: An Introduction in R (Spatial Analytics and GIS)

ISBN-13: 9781526449368
ISBN-10: 1526449366
Edition: 1
Author: Lex Comber, Chris Brunsdon
Publication date: 2021
Publisher: SAGE Publications Ltd
Format: Paperback 360 pages
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Book details

ISBN-13: 9781526449368
ISBN-10: 1526449366
Edition: 1
Author: Lex Comber, Chris Brunsdon
Publication date: 2021
Publisher: SAGE Publications Ltd
Format: Paperback 360 pages

Summary

Geographical Data Science and Spatial Data Analysis: An Introduction in R (Spatial Analytics and GIS) (ISBN-13: 9781526449368 and ISBN-10: 1526449366), written by authors Lex Comber, Chris Brunsdon, was published by SAGE Publications Ltd in 2021. With an overall rating of 4.2 stars, it's a notable title among other Human Geography (Social Sciences) books. You can easily purchase or rent Geographical Data Science and Spatial Data Analysis: An Introduction in R (Spatial Analytics and GIS) (Paperback) from BooksRun, along with many other new and used Human Geography books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $6.24.

Description

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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