Spatial Analysis and Modelling for Biodiversity and Ecosystem Processes

2 step course of 5 days

The course is going to be divided into two Parts to allow students with less experience in spatial data analysis to have a first introduction, necessary to participate in the second half of the course.

Part 1 - Introduction (2 days)

Part 1 consists of a general introduction to spatial analysis principles and tools including spatial data collection, manipulation and edition, projections and transformations, basic analysis tools, and the use of simple workflows in spatial analysis.

Part 2 - Spatial analysis and modelling (3 days)

The second part of the course require the students to have prior knowledge about spatial projections and spatial data handling, as well as, a good level of R, ArcGIS tools and programming. This part will concentrate in experimenting with spatial analysis tools and data handling exercises in biodiversity and ecosystem analysis routines. The exercises will be previously prepared and will be given to the students along with the course program. The exercises will include ecosystem modelling and regression analysis, data extraction and causality and spatial interpolation.

Here you can find the provisional course agenda.

Prior knowledge needed:

For part 1 of the course no prior knowledge is needed.

For part 2, participants need knowledge on spatial projections and spatial data handling (similar to the first 2 days of this course) and have proficiency in the use of databases and workflows in spatial analysis. Furthermore a good level of R and ArcGIS tools and programming language is indispensable. Python programming is a plus.