I am currently trying to edit the Corine Land Cover (CLC2018) raster map of Europe. I need to condense the landcover classes into a smaller number of different classes and then convert those classes into resistance data so that I can then use the map for Circuitscape analysis. Does anyone have any R code that could help me get started with this? I am stuck.
Also does anyone know of a shapefile of the balkans I could use to crop the CLC2018 map to a more manageable size?
Thanks!
Hi,
referring to your first question, there are basically two paths to victory:
1) Reclassify all the final landcover categories into reistance values, based on expert judgement. So landcover which is very unsuited for your species would be assigned a higher reistance, and good (suitable) land cover would then be assigned a low resistance.
2) Create an ecological niche model (ENM) and then invert this model into resistance values. There are lots of possibilities to create ENMs, and most are doable within R (MaxEnt for example).
If you dont manage it with R, consider using a GIS like ArcGIS of QGIS.
Hope this helps,
Florian
Dear Anthony,
I totally agree with Florian Kunz . In R, you can use function reclassify() from package 'raster' or simple raster algebra for reclassification and packages 'dismo', 'maxent' or 'biomod2' for modeling.
For the class-resistance conversion I recommend writing an own function and use it with raster::calc().
HTH,
Ákos
- Badges
- Science topic
- Similar topics
- Mathematics
- Statistics
- Statistical Software
- R