[R-sig-Geo] issue with variogram plotting using autofitVariogram(automap)

[subash]

I am a newbie in R. I am using *autofitVariogram* to  daily rainfall data of
50 stations.The sample data is provided below.Some of stations have missing
values represented by "NaN" values. 

My question is regarding the variogramfit. The variogram covers only a
distance of 60,000m. Why are the points in bins beyond 60Km not plotted. I
had seen from spatial correlation plot maximum distance from lon-lat
information is >200Km.


The summary of* latitide and longitude* information is provided below.
summary(lonlat)
      lon             lat       
 Min.   :74.78   Min.   :15.77  
 1st Qu.:75.14   1st Qu.:16.04  
 Median :75.56   Median :16.33  
 Mean   :75.54   Mean   :16.37  
 3rd Qu.:75.94   3rd Qu.:16.66  
 Max.   :76.31   Max.   :17.23  

$ Sample data  given below:
dput(rain[140:145,])

structure(list(Col0 = c(0, 0, 1, 9, 6.5, 0), Col1 = c(1.5, 36, 
21, 44, 4, 0), Col2 = c(0, 0, 24.5, 21.5, 7.5, 1), Col3 = c(0, 
1, 45, 3, 0, 0), Col4 = c(2, 0, 5, 54.5, 13.5, 0), Col5 = c(0.5, 
2, 0, 3.5, 13.5, 0), Col6 = c(0.5, 0, 0, 59, 15.5, 0), Col7 = c(0, 
0, 2.5, 1, 0, 0), Col8 = c(0, 6, 24, 2, 5.5, 0), Col9 = c(0, 
3, 6, 1, 0, 7), Col10 = c(0.5, 1, 64, 20, 1, 0.5), Col11 = c(NaN, 
NaN, NaN, NaN, NaN, NaN), Col12 = c(0, 11, 75, 19, 15.5, 0), 
    Col13 = c(0, 4, 57.5, 50.5, 8.5, 0), Col14 = c(1.5, 0.5, 
    127, 33.5, 34.5, 0), Col15 = c(0, 7, 0.5, 13, 1, 0), Col16 = c(0, 
    0.5, 81.5, 15, 49, 0), Col17 = c(0, 0, 4.5, 17, 5.5, 1), 
    Col18 = c(0, 3, 2.5, 0.5, 0, 0), Col19 = c(NaN, NaN, NaN, 
    NaN, NaN, NaN), Col20 = c(0, 0, 0, 0, 7, 0), Col21 = c(0, 
    1, 0, 5, 3.5, 0), Col22 = c(0, 0, 11.5, 28, 3.5, 0), Col23 = c(0, 
    0, 48.5, 0, 24.5, 0), Col24 = c(0, 0, 0, 10, 0.5, 14), Col25 = c(NaN, 
    NaN, NaN, NaN, NaN, NaN), Col26 = c(0, 7.5, 16, 28.5, 20.5, 
    0), Col27 = c(1.5, 0.5, 38, 28.5, 50, 0), Col28 = c(NaN, 
    NaN, NaN, NaN, NaN, NaN), Col29 = c(NaN, NaN, NaN, NaN, NaN, 
    NaN), Col30 = c(2.5, 0, 0, 80.5, 28, 13.5), Col31 = c(1, 
    0, 17, 85.5, 3.5, 0), Col32 = c(0, 0.5, 8, 101, 20, 4), Col33 = c(NaN, 
    NaN, NaN, NaN, NaN, NaN), Col34 = c(4, 3, 17, 122, 2, 2), 
    Col35 = c(0, 15.5, 14.5, 20, 3.5, 0), Col36 = c(0, 6.5, 8.5, 
    21, 7, 0), Col37 = c(0, 0, 1.5, 14.5, 0, 1.5), Col38 = c(0, 
    28, 30, 4, 0, 73), Col39 = c(28.5, 0, 4.5, 9.5, 1, 0), Col40 = c(1.5, 
    11.5, 32.5, 55, 0, 1), Col41 = c(0, 14.5, 0, 19, 12.5, 47.5
    ), Col42 = c(0, 28, 29, 17, 0.5, 20.5), Col43 = c(NaN, NaN, 
    NaN, NaN, NaN, NaN), Col44 = c(0, 19, 3.5, 42, 0, 0), Col45 = c(0, 
    0, 85, 15.5, 1, 0), Col46 = c(0, 0.5, 8, 24, 0.5, 0), Col47 = c(0, 
    1.5, 7, 12, 8.5, 0), Col48 = c(0, 0, 0, 43.5, 0, 1.5), Col49 = c(0, 
    13.5, 1, 16, 1, 1)), .Names = c("Col0", "Col1", "Col2", "Col3", 
"Col4", "Col5", "Col6", "Col7", "Col8", "Col9", "Col10", "Col11", 
"Col12", "Col13", "Col14", "Col15", "Col16", "Col17", "Col18", 
"Col19", "Col20", "Col21", "Col22", "Col23", "Col24", "Col25", 
"Col26", "Col27", "Col28", "Col29", "Col30", "Col31", "Col32", 
"Col33", "Col34", "Col35", "Col36", "Col37", "Col38", "Col39", 
"Col40", "Col41", "Col42", "Col43", "Col44", "Col45", "Col46", 
"Col47", "Col48", "Col49"), row.names = 143:148, class = "data.frame")


# Import the required libraries
library(rgdal)
library(maptools)
library(gstat)
library(sp)
library(automap)
library(XLConnect) 

# Read the station data from xls file
rawdata = readWorksheetFromFile(path_fileName,"Sheet1", region = "D1:BA187",
header = FALSE)
N = nrow(rawdata)
rain = rawdata[4:N,]
lat = as.numeric(t(rawdata[2,]))
lon = as.numeric(t(rawdata[3,]))
lonlat = cbind(lon,lat)

#Transform from GCS to UTM protection
sp = SpatialPoints(lonlat,proj4string = CRS("+proj=longlat")) 
sp_utm = spTransform(sp, CRS("+proj=utm +zone=43N +datum=WGS84"))

krige_value = list() #prepare a list for storing the autokrige output
krige_stderr    = list()

nRows = nrow(rain)


for (i in 1:nRows) 
{   
  irain = rain[i,]
  indx = (irain == "NaN")
  irain = irain[!indx]
  irain = as.numeric(irain)

  isallzeros = max(irain) # To take care of the cases of dry day(irain =0)
at all stations
  irain = as.data.frame(irain)
  M = nrow(irain)
    
  if (M > 5) # To avoid cases of NaN across many stations
  {
    if (!(isallzeros == 0))
    {
      print(i)
      foo_utm = sp_utm[!indx]# Removing the locations with NaN values
      data = data.frame(foo_utm,irain)
      names(data) = c("Easting","Northing","rain")
      coordinates(data) = c("Easting","Northing") 
      
      variogram = autofitVariogram(rain~1,data,model =
"Sph",fix.values=c(0,NA,NA)) 
      p = plot(variogram, main="Semi-variogram (Spherical
Model)",xlab="Distance(m)",ylab="Semi-Variance(mm2)", sub=paste("Range:
",variogram$var_model$range[2], "Day",i))
      print(p)
    }
    else
    {
      krige_value[[i]] = list(rep(0, L))
      krige_stderr[[i]]   = list(rep(0, L))
    }
  }
}

Please let me know if I am missing something?

<http://r-sig-geo.2731867.n2.nabble.com/file/n7582331/141.png> 



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