Learning R for Geospatial Analysis
By: Michael Dorman (author)Paperback
1 - 2 weeks availability
This book is intended for anyone who wants to learn how to efficiently analyze geospatial data with R, including GIS analysts, researchers, educators, and students who work with spatial data and who are interested in expanding their capabilities through programming. The book assumes familiarity with the basic geographic information concepts (such as spatial coordinates), but no prior experience with R and/or programming is required. By focusing on R exclusively, you will not need to depend on any external software a working installation of R is all that is necessary to begin.
Michael Dorman is currently a PhD candidate at the Department of Geography and Environmental Development, Ben-Gurion University of the Negev. His research explores the response of planted pine forests to changing climate through remote sensing and dendrochronology. He uses R extensively for time series and spatial statistical analyses and visualization. In spring 2013, he prepared and taught a course named Introduction to Programming for Spatial Data Analysis at the Ben-Gurion University of the Negev, introducing R as an environment for spatial data analysis to undergraduate Geography students. The course material served as a foundation for this book. Michael holds a Master's degree in Life Sciences from the Ben-Gurion University of the Negev and a Bachelor's degree in Plant Sciences in Agriculture from The Hebrew University of Jerusalem. He has authored or coauthored eight papers in scientific literature and actively participated in 18 scientific conferences.
Number Of Pages:
- ID: 9781783984367
- Saver Delivery: Yes
- 1st Class Delivery: Yes
- Courier Delivery: Yes
- Store Delivery: Yes
Prices are for internet purchases only. Prices and availability in WHSmith Stores may vary significantly
© Copyright 2013 - 2016 WHSmith and its suppliers.
WHSmith High Street Limited Greenbridge Road, Swindon, Wiltshire, United Kingdom, SN3 3LD, VAT GB238 5548 36