Description Usage Arguments Examples
This function calculates the minimum distance to points raster.
1 2 | dist2point(grid, points, parallel = TRUE, nclus = 4,
dist.method = "Haversine", maxram = 4)
|
grid |
A raster object to match. |
points |
A two column data frame in the form (lon,lat) or (x,y) |
parallel |
TRUE or FALSE, should this code be executed in parallel. |
nclus |
IF parallel==TRUE then how many cores in the cluster. |
dist.method |
Which distance should we use? Haversine for lat/long projections,or Pythagorean for flat images and/or small areas. |
maxram |
Maximum theoretical RAM usage. Will be divided by nclus for parallel jobs. |
1 2 3 4 5 6 7 8 9 10 11 12 13 | require(raster)
grid = raster::raster(nrows=81, ncols=162, xmn=-180, xmx=180, ymn=-90, ymx=90, vals=NULL)
grid = raster::setValues(grid,values=(as.vector(seq(1:raster::ncell(grid)))))
points = cbind(
c(seq(xmin(grid), xmax(grid), length.out=1000),
seq(xmax(grid), xmin(grid), length.out=1000)),
c(seq(ymin(grid), ymax(grid), length.out=100),
seq(ymin(grid), ymax(grid), length.out=100))
)
plot(grid); points(points);
di = dist2point(grid, points, parallel=TRUE, maxram = 0.5, nclus = 4, dist.method='Haversine')
plot(di)
points(points)
|
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