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ONLINE COURSE – Spatio-Ecological Data Analysis using R and Rstudio (SEAR01) This course will be delivered live
22 April 2024 - 25 April 2024
£480.00
Event Date
Monday, April 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.
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).
Course Details
Spatial ecology is now recognised as one of the founding disciplines to link spatial patterns to ecological changes in space and time.
This course mainly focuses on the application of free and open source algorithms – which ensure high reproducibility and robustness of ecological analysis – to study ecological change in space and time, due to both human impact and global change. Particular emphasis will be given to: 1) population ecology: how organisms spread in space and how to study it by point pattern analysis, 2) community ecology: how communities are structured and how to study such structure by multivariate analysis; 3) monitoring species distributions and their change in space and time by species distribution modelling; 4) monitoring ecosystem change in space and time by remote sensing data.
The course is dramatically practical giving space to exercises and additional ecological issues provided by the professor and suggested by students. We will make use of R which is one of the main free and open source software for ecological modelling.
By the end of the course, participants will:
• be able to create their own projects on monitoring of spatial and temporal changes of species and ecosystems at different spatial scales
• be able to report in LaTeX and R Markdown the achieved results
Intended Audiences
This course is aimed at academics and post-graduate students working in spatial ecology
Venue
Delivered remotely
Course Information
Time zone – Central European Time
Availability – 20 places
Duration – 5 days
Contact hours – Approx. 28 hours
ECT’s – Equal to 3 ECT’s
Language – English
Teaching Format
Theoretical presentations will introduce coding sessions. The whole course is intended to be practical.
Assumed quantitative knowledge
No previous knowledge of R is needed.
Assumed computer background
A basic computer background is needed.
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.
Course packages:
– imageRy
– overlap
– spatstat
– terra
– vegan
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.
COURSE PROGRAMME
Monday 25th – Classes from 09:30 to 17:30
– R (intro)
[Introduction to the R Software and the Free and Open Source philosophy: how to deal with R making your first code!]
[Spatial R]
– Population Ecology
[Point Patterns Analysis – Spatial statistics: deriving continuous maps from in-situ data, principles of autocorrelation and spatial interpolation]
Tuesday 26th – Classes from 09:30 to 17:30
– Community ecology
[Multivariate analysis in R]
[Community niche overlap]
– Remote sensing in R
[Remotely sensed data visualisation]
Wednesday 27th – Classes from 09:30 to 17:30
– Remote sensing in R
[Spectral indices]
[Time series]
Thursday 28th – Classes from 09:30 to 17:30
– External remote sensing data
[Download and use remote sensing data from internet sources]
[Downloading and visualising Copernicus data]
– Image data processing
[Remotely sensed data classification: land cover maps]
[Ecosystem variability]
[Multivariate analysis on remotely sensed data]
Friday 29th – Classes from 09:30 to 17:30
– Reporting
[LaTeX for scientific reporting via articles]
[LaTeX/Beamer for scientific reporting via presentations]
[R Markdown for scientific reporting via internet pages]
Course Instructor
Dr. Duccio Rocchini
Coming soon…