note_27_05

last time we made presentation on biodiversity 
standard deviation could be a way to analyze the potential biodiversity 
5x5 pixel our moving window, we calculate the SD for the gride at time

second part of EBVs 
##############

## FOCAL ON Cladonia

library(raster)
clad <- brick("cladonia_stellaris_calaita.JPG)
)
")
clad <- brick("cladonia_stellaris_calaita.JPG")
window <- matrix(1, nrow = 3, ncol = 3)
window
sd_sntr <- focal(snt_r10$snt_r10.4, w=window, fun=sd)
sd_sntr <- focal(clad, w=window, fun=sd) 
clad
sd_sntr <- focal(clad[,1], w=window, fun=sd) 
sd_sntr <- focal(clad$cladonia_stellaris_calaita.1, w=window, fun=sd) 
plot(sd_sntr) 
cl <- colorRampPalette(c('red','orange','yellow'))(100) # 
plot(sd_sntr,col=cl) 
cl <- colorRampPalette(c('yellow','orange','violet'))(100) # 
plot(sd_sntr,col=cl) 
cl <- colorRampPalette(c('yellow','violet','black'))(100) # 
plot(sd_sntr,col=cl) 
clado <- stack(clad, sd_sntr)
plot(clado)
plot(clado,col=cl)
par(mfrow=c(1,2)) 
plotRGB(clad,3,2,1,stretch="lin")
plot(sd_sntr,col=cl) 
pdf("clad_enhancement.png")
par(mfrow=c(1,2)) 
plotRGB(clad,3,2,1,stretch="lin")
plot(sd_sntr,col=cl) 
dev.off()
q()

#####################

how you download images? 
one of the main thing that we can do to evaluete Climate change is the snow cover
if you mesure the multitemporal analysis you can understand the temporal ecosystem changes
https://land.copernicus.vgt.vito.be/PDF/portal/Application.html
here you can find vito project with all datasets
login and download cryosphere 1km spat resolution

we need raster function= raster  import 1 layer 
brick function import all the layer

for this we need library raster!
for the PCA we need RStoolbox library

So we can start with subscribe on copernucus