Dear R-sig-geo'ers
I am currently running some interpolations using automap written by Paul
Hiemstra. So far my interpolations have been producing suitable results except
for one problem. From the code you will see that the boundaries of the spatial
grid are determined using the range of the X and Y coordinates creating a
square grid. My point data do not cover the entire grid and I would only like
to interpolate in areas where data exists otherwise I get a significant edge
effect. Is it possible to limit / mask my interpolation to only predict where
data exists?
The point data are lidar canopy returns for an irregular shaped timber
compartment and number around 10 000 irregular spaced points.
Any help on this matter would be greatly appreciated.
Kind regards,
Wesley
library(automap)
library(gstat)
a <- read.csv("AreaOne_4pts.csv", header=TRUE)
coordinates(a) <-~ x+y
x.range <- as.integer(range(a...@coords[,1]))
y.range <- as.integer(range(a...@coords[,2]))
grd <- expand.grid(x=seq(from=x.range[1], to=x.range[2], by=0.1),
y=seq(from=y.range[1], to=y.range[2], by=0.1))
coordinates(grd) <-~ x+y
gridded(grd) <- TRUE
height = autoKrige(H~1, a, grd, nmax=100)
writeGDAL(height$krige_output, fname="test.tiff", drivername ="GTiff", type =
"Float32")
intensity = autoKrige(I~1, a, grd, nmax=100)
writeGDAL(intensity$krige_output, fname="test.tiff", drivername ="GTiff", type
= "Float32")
Wesley Roberts MSc.
Researcher: Earth Observation (Ecosystems)
Natural Resources and the Environment
CSIR
Tel: +27 (21) 888-2490
Fax: +27 (21) 888-2693
"To know the road ahead, ask those coming back."
- Chinese proverb
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