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A01=Chris Brunsdon
A01=Lex Comber
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Author_Lex Comber
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Geographical Data Science and Spatial Data Analysis: An Introduction in R

English

By (author): Chris Brunsdon Lex Comber

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. See more
Current price €50.39
Original price €55.99
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A01=Chris BrunsdonA01=Lex ComberAge Group_UncategorizedAuthor_Chris BrunsdonAuthor_Lex Comberautomatic-updateCategory1=Non-FictionCategory=GPSCategory=RGCOP=United KingdomDelivery_Delivery within 10-20 working daysLanguage_EnglishPA=AvailablePrice_€50 to €100PS=Activesoftlaunch
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Product Details
  • Weight: 670g
  • Dimensions: 170 x 242mm
  • Publication Date: 25 Dec 2020
  • Publisher: Sage Publications Ltd
  • Publication City/Country: United Kingdom
  • Language: English
  • ISBN13: 9781526449368

About Chris BrunsdonLex Comber

Alexis Comber Lex is Professor of Spatial Data Analytics at Leeds Institute for Data Analytics (LIDA) the University of Leeds. He worked previously at the University of Leicester where he held a chair in Geographical Information Science. His first degree was in Plant and Crop Science at the University of Nottingham and he completed a PhD in Computer Science at the Macaulay Institute Aberdeen (now the James Hutton Institute) and the University of Aberdeen. This developed expert systems for land cover monitoring from satellite imagery and brought him into the world of spatial data spatial analysis and mapping. Lexs research interests span many different application areas including environment land cover / land use demographics public health agriculture bio-energy and accessibility all of which require multi-disciplinary approaches. His research draws from methods in geocomputation mathematics statistics and computer science and he has extended techniques in operations research / location-allocation (what to put where) graph theory (cluster detection in networks) heuristic searches (how to move intelligently through highly dimensional big data) remote sensing (novel approaches for classification) handling divergent data semantics (uncertainty handling ontologies text mining) and spatial statistics (quantifying spatial and temporal process heterogeneity). He has co-authored (with Chris Brunsdon) An Introduction to R for Spatial Analysis and Mapping the first how to book for spatial analyses and mapping in R the open source statistical software now in its second edition. Outside of academic work and in no particular order Lex enjoys his vegetable garden walking the dog and playing pinball (he is the proud owner of a 1981 Bally Eight Ball Deluxe).  Chris Brunsdon is Professor of Geocomputation and Director of the National Centre for Geocomputation at the National University of Ireland Maynooth having worked previously in the Universities of Newcastle Glamorgan Leicester and Liverpool variously in departments focusing on both geography and computing. He has interests that span both of these disciplines including spatial statistics geographical information science and exploratory spatial data analysis and in particular the application of these ideas to crime pattern analysis the modelling of house prices medical and health geography and the analysis of land use data. He was one of the originators of the technique of geographically weighted regression (GWR). He has extensive experience of programming in R going back to the late 1990s and has developed a number of R packages which are currently available on CRAN the Comprehensive R Archive Network. He is an advocate of free and open source software and in particular the use of reproducible research methods and has contributed to a large number of workshops on the use of R and of GWR in a number of countries including the UK Ireland Japan Canada the USA the Czech Republic and Australia. When not involved in academic work he enjoys running collecting clocks and watches and cooking the last of these probably cancelling out the benefits of the first.

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