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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