#clear
rm(list=ls())
#contrl+L, clear workspace

require(sp)
require(gstat)
#Set your own working directory
setwd("C:\\ANAND SOOKUN\\A PhD Thesis 2015\\Analysis4R GIS\\Krigging")
carbon_seq <- read.csv("carbon seqnewAUG15.csv", header=TRUE)
ls()

str(carbon_seq)

carbon_seq$CO2SEQ2

carbon_seq$logcarbseq<-log10(carbon_seq$CO2SEQ2)
carbon_seq$logsolcarbseq<-log10(carbon_seq$SOIL_CARB)

hist(carbon_seq$logcarbseq, breaks = 16)
hist(carbon_seq$logsolcarbseq, breaks = 16)

str(carbon_seq)

coordinates(carbon_seq)<-c("Lat","Lon")
class(carbon_seq)
summary(carbon_seq)
#project the data frame
proj4string(carbon_seq) <- CRS("+proj=utm +zone=40 +south +datum=WGS84 +units=m +no_defs +ellps=WGS84 +towgs84=0,0,0")
carbon_seq@proj4string

plot(carbon_seq, asp = 1, pch = 1)
(v <- variogram(logcarbseq ~ 1, carbon_seq))
print(plot(v, plot.numbers = T))
dim(coordinates(carbon_seq))
coordinates(carbon_seq)[1, ]
coordinates(carbon_seq)[2, ]
(sep <- dist(coordinates(carbon_seq)[1:2, ]))
(gamma <- 0.5 * (carbon_seq$logcarbseq[1] - carbon_seq$logcarbseq[2])^2)

(v <- variogram(logcarbseq ~ 1, carbon_seq))
print(plot(v, plot.numbers = T))
print(show.vgms())
vm <- vgm(psill = 0.15, model = "Sph", range = 0.1,nugget = 0.08)
print(plot(v, pl = T, model = vm))
(vmf <- fit.variogram(v, vm))
print(plot(v, pl = T, model = vmf))
library(raster)
map<-raster("vca_raster")
k40 <- krige(logcarbseq ~ 1, locations = carbon_seq, newdata = map,model = vmf)
#Error in (function (classes, fdef, mtable)  : unable to find an inherited method for function 'gridded' for signature '"RasterLayer"
print(spplot(k40, "var1.pred", asp=1, col.regions=bpy.colors(64),main="OK prediction, carbon seq"))


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