Essential tools to remove biases in spatial data using R

In this workshop we will cover common challenges that arise with any kind of spatial coordinate data in biology. Knowledge of the tools introduced in this workshop is essential when presenting spatial biological data (e.g. a map of sampling sites) in presentations or publications.

More specifically we will discuss strategies to deal with the non-independence of spatial data points also known as spatial autocorrelation. Further we will address challenges arising in global analyses from the simple fact that the earth is round. We will also touch upon some of the globally available environmental predictors often applied in spatial analyses and their potential challenges.

Participants are required to have basic knowledge of the R programming language and we assume that the participants are familiar with basic spatial operation in R. In case of doubt, we encourage participants to review the tutorial of our previous workshop ”Handling spatial data in R” here.


Course teachers: Søren Faurby, Tobias Andermann, Matthias Obst

Recommended background: Basic R knowledge required

Course level: PhD level (motivated Master's students welcome)

Food: Lunch will be provided for all course participants

Application: Send a short motivation (5 lines stating goals and expectations) to matthias.obst@marine.gu.se latest by 14th May 2019.

Contact: Søren Faurby (soren.faurby@bioenv.gu.se), Tobias Andermann (tobias.andermann@bioenv.gu.se), Matthias Obst (matthias.obst@marine.gu.se)

Tid: 2019-05-21 12:00 - 17:00
Ort: Gothenburg
Sista anmälningsdag: 14 maj 2019

Sidansvarig: ulrika.sehlberg.samuelsson@slu.se