Adapting to the recent changes in R spatial packages (sf, terra, PROJ library) (PROJPR)
1st January 2030
£350.00
COURSE FORMAT
Pre-Recorded
About This Course
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
Duration – Approx. 15 hours
ECT’s – Equal to 1 ECT’s
Language – English
Teaching Format
Assumed quantitative knowledge
Assumed computer background
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. R may be downloaded by following the links here https://www.r-project.org/. RStudio may be downloaded by following the links here: https://www.rstudio.com/.
All the R packages that we will use in this course will be possible to download and install during the workshop itself as and when they are needed, and a full list of required packages will be made available to all attendees prior to the course.
A working webcam is desirable for enhanced interactivity during the live sessions, we encourage attendees to keep their cameras on during live zoom sessions.
Although not strictly required, using a large monitor or preferably even a second monitor will improve he learning experience
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
Day 1
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
Day 2
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
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