The second year EDENext Spatial Data and GIS residential workshop was hailed a great success and built apon the skills learnt in the first year of the course. The course took place in Antwerp, Belgium from the 4th-6th of December inclusive. The improved skill levels of the participants were obbvious from the first day and the EDENext DMT Team would like to congratulate the participants on their obvious application to the distance learning course throughout the previous year.
The focus of this years course was to introduce a number of tools and approaches that can be used on the spatial data that the students now have the skills to collect and mange within a GIS environment. The course utilised GIS software, modelling software and scripting platforms. What was very satisfying to see was that on the final day of the course students were using all three environments on their own datasets, moving datasets confidently from GIS for viewing and setting extents, R for batch processing clipping and some modelling and then into Vecmap for further modelling.
The distance learning part of the course will continue in the new year. Details of its content will be confirmed shortly.
Links to the software used during the workshop are given below:
Getting back into QGIS and GRASS - This topic recapitulates the basic and advanced functionalities of QGIS and GRASS. This is illustrated using the case study provided by the ROBO group. Els Ducheyne
Using R: Data import - How to import data for species distribution modelling. Els Ducheyne
Using R: Species distribution Modelling - Using the presence data collected during the MODIRISK project, this topic shows how ENFA can be applied in R. In the next step, the absence data are included in the data set for Random Forest Classication. In the final step, the accuracy of the output models is assessed. Els Ducheyne
Using R: Spatial Autocorrelation - An illustrated session on how to measure spatial autocorrelation and how to account for it into linear models using R. Marius Gilbert
VECMAP modelling - In this section, it is shown how VECMAP can be used for species distribution modelling. David Morley
Useful Scripts in R - In this topic we will post useful scripts in R. Els Ducheyne
This section links to the background reading and resources recommended for each of the topics of the workshop.
Getting back into QGIS and GRASS
The case study used in this module looked at creating a GIS layer of an index of the likely number of people to visit locations in forest covered areas in belgium. Details from the following paper were used for background information.
- Van Herzele & Wiedemann (2003); A monitoring tool for the provision of accessible and attractive urban green spaces; Landscape and Urban Planning; Vol 63, Issue 2, 15 April 2003, Pages 109–126; http://dx.doi.org/10.1016/S0169-2046(02)00192-5
Using R: Data Import
Using R: Species Distribution Modelling
- ENFA Modelling???
Elith et al (2006); Novel methods improve prediction of species’ distributions from occurrence data; Ecography Volume 29, Issue 2, pages 129–151, April 2006; DOI: 10.1111/j.2006.0906-7590.04596.x
Peters et al (2011); Absence reduction in entomological surveillance data to improve niche-based distribution models for Culicoides imicola; Prev Vet Med. 2011 Jun 1;100(1):15-28. doi: 10.1016/j.prevetmed.2011.03.004. Epub 2011 Apr 14.
Using R: Spatial Autocorrelation
- Spatial Autocorrelation presentation
- Bjornstad and Falck (2001); Nonparametric spatial covariance functions: Estimation and testing; Environmental and Ecological Statistics March 2001, Volume 8, Issue 1, pp 53-70;
- Crase et al (2012); A new method for dealing with residual spatial autocorrelation in species distribution models; Ecography Vol 35, Issue 10, pages 879–888, Oct 2012; DOI: 10.1111/j.1600-0587.2011.07138.x
- Dorman et al (2007); Methods to account for spatial autocorrelation in the analysis of species distributional data: a review; Ecography 30: 609628, 2007 doi: 10.1111/j.2007.0906-7590.05171.x
- VECMAP help file for Non Linear Discriminant Analysis
Useful Scripts in R
- How to crop images in R
- Hijmans (2012); Introduction to the 'raster' package
- www.spatialreference.org - This website contains the coordinate reference system definitions currently archived