lab plan

Lab plan:

1. R (intro)

[Introduction to the R Software and the Free and Open Source philosophy: how to deal with R making your first code!]

2. Spatial R

[Introduction to the R Software and the Free and Open Source philosophy: how to deal with R making your first code!]

3. Multivariate analysis in R

[Population and community monitoring]

4. Remote sensing in R

[Remote sensing: performing amazing spatio-temporal monitoring with satellite data at global scales, i.g. copernicus saterlite]

[Geographical data and reference systems: how to deal with the spatial reference of geographical data]

5. Spatial statistics: let's analyse spatial data from the students' theses!

[Spatial statistics: deriving continuous maps from in-situ data, principles of autocorrelation and spatial interpolation]

6. Multitemporal analysis (e.g. NO2 before and after covid-19, indicators of global change - decrease in snow cover, deforestation)

[Multitemporal analysis: monitoring change in time]

7. Species Distribution Modelling

[Species distribution modelling: modelling the main drivers shaping species distributions]

install.packages ("sp")
install.packages ("GGally")
install.packages ("raster")
install.packages ("rgdal")
install.packages ("ggplot2")
install.packages ("spatstat")
install.packages ("rnaturalearth")
install.packages ("vegan")
install.packages ("RStoolbox")
install.packages ("rasterdiv")
install.packages ("rasterVis")

library("sp")
library ("GGally")
library ("raster")
library ("rgdal")
library("ggplot2")
library ("spatstat")
library("rnaturalearth")
library ("vegan")
library ("RStoolbox")
library ("rasterdiv")
library ("rasterVis")