Dear R-Sig-Geo,
I am trying to interpolate air pollution from air monitoring thanks to
ordinary kriging in order to assign the pollution exposure for a sample of
individual for the city of Phoenix, Arizona, using the Gstat package.
However, I have some trouble to understand how my data should be projected
in order to fit the variogram. My data are in longitude/latitude:
id co1h latitude longitude
1 390 33.49462 -112.1310
2 470 33.48385 -112.1426
3 170 33.41045 -111.8651
4 210 33.56033 -112.0663
5 210 33.56936 -112.1915
6 360 33.45793 -112.0460
7 200 33.47968 -111.9172
8 300 33.46093 -112.1175
9 370 33.40316 -112.0753
10 180 33.29898 -111.8843
11 240 33.41240 -111.9347
12 150 33.63713 -112.3418
13 70 33.37005 -112.6207
14 310 33.50318 -112.0956
In order to fit the variogram I use the following commands with:
co<-read.dta("co1h.dta")
coordinates(co) = ~longitude+latitude
v <- variogram(log(co1h) ~ 1, co)
plot(v)
vgm<-vgm(0.59638453, "Hol", 0.1490525,0.02910648, anis = c(90, 0.8))
v.fit<-fit.variogram(v, vgm)
v.fit
plot(v,fit.variogram(v, vgm))
Does anyone know if my projection is correct or whether I need to change
it? If it is necessary to change, do you know how can I do it and what
should be the correct projection?
Thank you very much for your help!
Kind regards,
Marguerit David
PhD in economics,
University Paris Dauphine, France
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