contour map of spatial-temporal K function

Question

I have latitude and longitude point data over time. I would like to plot (in R or Matlab) a contour map of spatial-temporal K function (much like the one below), but have no ide

Answer 1

Here's an outline of how you might start this in R. Note that this does not address the question of 'how to compute a spatial-temporal K function'.

First, get example data from plot raster with discrete colors using rasterVis

x=seq(-107,-106,.1)
y=seq(33,34,.1)
coords=expand.grid(x,y)
data1=data.frame(coords,depth=runif(nrow(coords),0,2))
names(data1)=c('x','y','value')

# get max and min values 
xmn=min(data1[,1]); xmx=max(data1[,1])
ymn=min(data1[,2]); ymx=max(data1[,2])

Now compute an interpolated raster from the raw data...

# compute interpolated raster. Note that this is not the 'spatial-temporal K function' requested in the question, as pointed out in a comment below, but a linear interpolation
library(akima)
akima.li <- interp(data1[,1], data1[,2], data1[,3], duplicate = "median",
                   xo=seq(xmn,xmx, length=100),
                   yo=seq(ymn,ymx, length=100))

Plot the raster...

# plot interpolated raster 
image(akima.li, col = rainbow(100, alpha = 1))

Plot the raster as a contour plot...

# plot interpolated contour 
contour(akima.li, nlevels = 3)

Now put the raster and contour together and this is close to the example image you posted...

# put the raster and contours together
image(akima.li, col = rainbow(100, alpha = 1))
contour(akima.li, nlevels = 3, add = TRUE)

And with a few minor tweaks, here is a very close match to the style of the example...

image(akima.li, col = gray.colors(10, start = 0, end = 0.9, gamma = 2.2, alpha = 1))
contour(akima.li, nlevels = 3, add = TRUE)

Finally, this is pretty much a match, with grey-scale contour fill, contour labels but no contour lines

image(akima.li, col = gray.colors(10, start = 0, end = 1, gamma = 1, alpha = 1))
contour(akima.li, nlevels = 3, add = TRUE, lty = 0)