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ONLINE COURSE – Introduction to spatial analysis of ecological data using R (ISPE05) This course will delivered live

11 July 2022 - 14 July 2022

£450.00
ONLINE COURSE – Introduction to spatial analysis of ecological data using R (ISPE05) This course will delivered live

Event Date

Monday, July 11th, 2022

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.

Course Program

TIME ZONE – UTC+2 – however all sessions will be recorded and made available allowing attendees from different time zones to follow a day behind with an additional 1/2 days support after the official course finish date (please email oliverhooker@prstatistics.com for full details or to discuss how we can accommodate you).

About this course

The aim of the course is to introduce you to a spatial data processing, analysis, and visualization capabilities of the R programming language. It will teach a range of techniques using a mixture of lectures, computer exercises and case studies.

By the end of the course participants should:

  • Understand the basic concepts of spatial data analysis
  • Know R’s spatial capabilities
  • Understand how to import a range of spatial data sources into R
  • Be confident with using R’s command-line interface (CLI) for spatial data processing
  • Be able to perform a range of attribute operations (e.g. subsetting and joining), spatial operations (e.g. distance relations, topological relations), and geometry operations (e.g. clipping, aggregations)
  • Understand coordinate reference systems (CRSs), be able to decide which CRS to use, and how to reproject spatial data
  • Know how to visualize the results of a spatial analysis in the form of static and interactive maps
  • Have the confidence to apply spatial analysis skills to their own projects
Intended Audiences

Academics and post-graduate students working on projects related to spatial data and want access to a powerful (geo)statistical and visualization programming language.

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.

The course is designed for intermediate-to-advanced R users interested in spatial data analysis and R beginners who have prior experience with geographic data.

Venue

Delivered remotely

Course Details

Venue – Delivered remotely

Time zone – Poland local time (UTC+2)

Availability – 20 places

Duration – 4 days

Contact hours – Approx. 27 hours

ECT’s – Equal to 2 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 there will be a time to exercise the topics using provided data sets. Participants are also very welcome to bring their own data.

Assumed quantitative knowledge

The course is designed for intermediate-to-advanced R users interested in spatial data analysis and R beginners who have prior experience with geographic data.

Assumed computer background

Attendees should already have experience with R and be able to read csv files, create simple plots, and manipulate data frames.

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

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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

Monday 11th – Classes from 09:00 – 17:00
Introduction to the course
Key concepts related to spatial data
R’s spatial ecosystem
Reading data from spatial file formats
Understanding R’s spatial classes
Creating static and interactive maps:
Customizing maps
Making facet maps

Tuesday 12th – Classes from 09:00 – 17:00
Attribute data operations:
Vector attribute subsetting, aggregation and joining
Creating new vector attributes
Raster subsetting
Summarizing raster objects
Spatial data operations:
Spatial subsetting

Wednesday 13th – Classes from 09:00 – 17:00
Spatial data operations:
Topological relations
Spatial joining
Aggregation
Map algebra
Local, focal, and zonal raster operations
Geometry operations:
Geometric operations on vector data
Geometric operations on raster data

Thursday 14th – Classes from 09:00 – 17:00
Geometry operations:
Interactions between rasters and vectors
Understanding of the coordinate reference systems (CRSs)
Reprojecting geographic data
Modifying map projections
Retrieving open data from web sources
Using R packages for spatial data retrieval
Writing spatial data

Course Instructor

Dr 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)

Personal website

ResearchGate

GoogleScholar

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.

Details

Start:
11 July 2022
End:
14 July 2022
Cost:
£450.00
Event Categories:
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