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PRIVATE COURSE – Adapting to the recent changes in R spatial packages (sf, terra, PROJ library) (PROJ01)
6 September 2021 - 10 September 2021
This is a ‘PRIVATE COURSE’ – this course is being delivered privately for an institute, if you would like to attend a public edition of this course please email email@example.com. Alternatively, if you would like any of our courses delivered privately for your institue, please, again please email firstname.lastname@example.org.
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 These packages, however, are being revised, updated, or even superseded to allow for better performance, simpler user interface, or expanded capabilities.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)?
- 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.
Venue – Delivered remotely
Time zone – NA
Availability – NA
Duration – 2 full days
Contact hours – Approx. 14 hours
ECT’s – Equal to 1 ECT
Language – English
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 email@example.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.
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
Attendees are expected to have a working version or R and RStudio installed.
R and RStudio are supported by both PC and MAC and can be downloaded for free by following these links
You will be sent a list of packages prior to the course. It is essential that you come with all necessary software and packages already installed.
UNSURE ABOUT SUITABLILITY THEN PLEASE ASK firstname.lastname@example.org
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
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