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ONLINE COURSE – Adapting to the recent changes in R spatial packages (sf, terra, PROJ library) (PROJ05) This course will be delivered live
22 May 2024 - 23 May 2024
£350.00
Event Date
Wednesday, May 22nd, 2024
COURSE FORMAT
This is a ‘LIVE COURSE’ – the instructor will be delivering lectures and coaching attendees through the accompanying computer practical’s via video link, a good internet connection is essential.
TIME ZONE
TIME ZONE – `Central European Standard Time – however all sessions will be recorded and made available allowing attendees from different time zones to follow.
Please email oliverhooker@prstatistics.com for full details or to discuss how we can accommodate you.
About This Course
R statistical software is becoming increasingly popular for spatial analysis and mapping. This is partially due to a large number of R packages devoted to applying various spatial methods. These packages, however, are being revised, updated, or even superseded to allow for better performance, simpler user interface, or expanded capabilities. Substantial recent changes in R spatial packages include developing the ‘sf’ package as a successor of ‘sp’, creation of `terra` as a successor of `raster`, and establishing the `stars` package. Additionally, all of these packages were affected by the recent major updates of the PROJ library. In this course, we will learn to use key packages for the analysis of spatial data, both vector (‘sf’) and raster (‘terra’), and see how they differ from their older counterparts, ‘sp’ and ‘raster’. Another important aspect of the course will be to understood spatial projections and coordinate systems, how the recent PROJ changes affect R users, and how to adjust to them.
By the end of the course, participants should:
- Understand the basic concepts behind spatial analysis ecosystem in R
- Know how packages such as sp/rgeos/rgdal/raster differ from their successors sf/terra/star
- Be able to switch from using packages such as sp/rgeos/rgdal/raster to sf/terra/stars
- Understood the basic concepts behind spatial projections, and how PROJ.7 differs from PROJ4
- Know how to deal with coordinate reference systems in R
- Have the confidence to switch from PROJ4 to PROJ7 (i.e., for instance, adjusting old scripts based on PROJ4)?
Intended Audiences
- Academics and post-graduate students working on projects related to spatial data
- Applied researchers and analysts in public, private or third-sector organizations who need the reproducibility, speed and flexibility of a command-line language such as R for spatial data analysis
- Current R users wanting to update your knowledge, including switch from using `sp` to `sf`, and from `raster` to `terra`
The course is designed for intermediate R users interested in understanding modern tools for spatial data analysis in R and R beginners who have prior experience with geographic data and other spatial software.
Course Details
Time zone – Central Europe Standard Time
Availability – TBC
Duration – 2 days
Contact hours – Approx. 15 hours
ECT’s – Equal to 1 ECT’s
Language – English
Teaching Format
The course will be a mixture of theoretical and practical. Each concept will be first described and explained, and next the attendees will exercise the topics using provided data sets.
Assumed quantitative knowledge
Understanding basic GIS concepts, such as spatial vector, spatial raster, coordinate reference systems would be beneficial, but is not necessary.
Assumed computer background
Attendees should already have experience with R and be able to read csv files, create simple plots, and manipulate data frames. The experience of using some basic R spatial packages, such as sp or raster would be beneficial.
However, if you do not have R experience but already use GIS software and have a strong understanding of geographic data types, and some programming experience, the course may also be appropriate for you.
Equipment and software requirements
A laptop computer with a working version of R or RStudio is required. R and RStudio are both available as free and open source software for PCs, Macs, and Linux computers.
Participants should be able to install additional software on their own computer during the course (please make sure you have administration rights to your computer).
A large monitor and a second screen, although not absolutely necessary, could improve the learning experience. Participants are also encouraged to keep their webcam active to increase the interaction with the instructor and other students.
UNSURE ABOUT SUITABLILITY THEN PLEASE ASK oliverhooker@prstatistics.com
PLEASE READ – CANCELLATION POLICY
Cancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered, contact oliverhooker@prstatistics.com. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees will be credited.
If you are unsure about course suitability, please get in touch by email to find out more oliverhooker@prstatistics.com
COURSE PROGRAMME
Wednesday 22nd
Classes from 09:00 to 17:00
Overview of spatial analysis ecosystem in R
• available R packages for spatial analysis in R
• how do R packages represent spatial objects, and how are they connected with each other
• importance of using the more recent R spatial packages, such as ‘sf’ or ‘terra’
• main concepts behind map projections (geoids, datums, geographic/projected coordinates, types of projections, etc.)
• implementation of these concepts in the PROJ library (used by most R spatial packages)
• differences between PROJ.4 and its newer versions (e.g. PROJ.7)
Spatial vector data analysis in R
• spatial vector data processing & analysis in R
• read/write/and visualize spatial vector data
• differences between ‘sp’/’rgdal’/’rgeos’ and ‘sf’
• moving from ‘sp’ to ‘sf’ for spatial vector data processing & analysis
• spherical geometry: how this concept was recently implemented in sf, and what is an impact of this implementation
Thursday 23rd
Classes from 09:00 to 17:00
Spatial raster data analysis in R
• spatial raster data processing & analysis in R
• read/write/and visualize spatial raster data
• differences between ‘raster’ and ‘stars’/’terra’
• moving from ‘raster’ to ‘terra’ for spatial raster data processing & analysis
• short overview of package ‘stars’
Coordinate reference systems
• how to switch from PROJ.4 to PROJ.7 in R
• open session: questions from the participants
Jakub Nowosad
Works at: Adam Mickiewicz University
Jakub Nowosad is a computational geographer working at the intersection between geocomputation and the environmental sciences. His research is focused on developing and applying spatial methods to broaden understanding of processes and patterns in the environment. A vital part of his work is to create, collaborate, and improve geocomputational software. He is an active member of the #rspatial community and a co-author of the Geocomputation with R book.
Teaches
- Introduction to spatial analysis of ecological data using R (ISPE)
- Making beautiful and effective maps in R (MAPR
- Adapting to the recent changes in R spatial packages (sf, terra, PROJ library) (PROJ
Teaches
- Introduction to spatial analysis of ecological data using R (ISPE)
- Making beautiful and effective maps in R (MAPR
- Adapting to the recent changes in R spatial packages (sf, terra, PROJ library) (PROJ