81,69 €
Geographical Data Science and Spatial Data Analysis
Geographical Data Science and Spatial Data Analysis
  • Sold out
Geographical Data Science and Spatial Data Analysis
Geographical Data Science and Spatial Data Analysis
El. knyga:
81,69 €
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 i…

Geographical Data Science and Spatial Data Analysis (e-book) (used book) | bookbook.eu

Reviews

(5.00 Goodreads rating)

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.

81,69 €
Log in and for this item
you will receive
0,82 Book Euros! ?

Electronic book:
Delivery after ordering is instant! Intended for reading only on a computer, tablet or other electronic device.

Lowest price in 30 days: 80,99 €

Lowest price recorded: 2025-09-27 20:41:19


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.

Reviews

  • No reviews
0 customers have rated this item.
5
0%
4
0%
3
0%
2
0%
1
0%
(will not be displayed)