getCosts.RdA function that calculates the cost to travel between two sets of points. This can be between two circumscribed sets of points, or one circumscribed one ('nodes') and all other points on the landscape.
getCosts(
region,
from,
to = NULL,
id = "ID",
dir = tempdir(),
x = "x",
y = "y",
destination = "pairs",
polygons = "centroid",
costs = c("dt", "dW_l", "dE_l"),
direction = "both",
output = "object",
outname = deparse(substitute(from)),
overwrite = FALSE,
...
)A SpatVector, Spatial* or Raster* representing the area of maximum movement
One of data.frame, data.table, SpatVector, SpatialPointsDataFrame, or
SpatialPolygonsDataFrame representing the origin locations. If to = NULL
and destination = 'pairs', this will also be used as the to parameter.
If it is a polygon, the location will be controlled by the polygons parameter.
One of data.frame, data.table, SpatVector SpatialPointsDataFrame, or
SpatialPolygonsDataFrame representing the origin locations. Optional if
destination = 'pairs', ignored if destination = 'all'.
Character string representing the column containing the unique
IDs for for each location in the from (and to) objects.
A filepath to the directory being used as the workspace.
Default is tempdir() but unless the analyses will only be performed a few
times it is highly recommended to define a permanent workspace.
A character vector representing the column containing the 'x' coordinates.
Required if data is not Spatial*.
A character vector representing the column containing the 'y' coordinates.
Required if data is not Spatial*.
One of 'pairs' or 'all'. If 'pairs',
a distance matrix will be generated between every pair of locations in
from, or every pair of locations between from and to.
If 'all', rasters will be generated for each node representing the cost
to travel to every cell in the given world.
One of c('polygon','centroid','center'). Ignored unless
from and/or to are polygons. If polygons = 'centroid' (the default),
the destinations are calculated to the centroid of the polygon whether or not
it lies within the polygon itself. If polygons = 'center', distances
are calculated to the point within the polygon closest to the centroid. If
polygons = 'polygons', distances are calculated to any point within the
polygon---in essence, the polygon acts as a giant node permitting costless
movement within its bounds. This is generally not consistent with real-world
scenarios and for that reason is not the default.
A character vector containing any combination of the strings
of differential values present in the environment (see
calculateCosts function; default is
costs = c("dt","dW_l","dE_l") anticipating the use of
calculateCosts(costFUN = energyCosts).
A character vector containing one or both of c("in","out")
or the singular string 'both'. This determines whether costs to or from the nodes
are calculated. Ignored for destination = 'pairs'.
A character vector containing one or both of c("object","file").
If "object" is included, then a list of RasterStacks will be returned.
If "file" is included, then the appropriate cost rasters will be saved
to the workspace directory dir. Ignored if destination = 'pairs'.
A character vector describing the name of the set of input
nodes for raster analysis. Ignored unless 'file' %in% output, in
which case the files will be stored in a file named as such. Default is the
name of the from input, which can lead to files being
overwritten if vector sources are arbitrarily changed.
Should any output files with the same outname be overwritten?
Default is overwrite = FALSE.
Additional arguments to pass to importWorld.
A list, with entries for each combination of selected costs
and directions. The object class of the list entries depends on the
destination and output parameters:
(1) If destination = 'pairs', entries are distance matrices.
(2) If destination = 'all' and 'object' %in% output,
entries are RasterStacks with each Raster* representing the cost to/from
each node.
(3) If destination = 'all' and output == 'file', no list is output.
Moreover, if file %in% output, then the cost rasters are saved in the
workspace directory.
There are four possible workflows:
(1) If you simply desire the distance between two sets of points, provide
entries for from and to (or just from if the interest is
in all distances between locations in that object). Output is a distance matrix.
The computational time for this operation is comparable to generating a raster
for the distance to all cells in the world (unless all of the locations
in the object are close to each other). So unless the operation is to be done
multiple times, it is highly recommended to generate the rasters as below and extract
values
(2) If you wish to generate a RasterStack of costs from and/or to all nodes
in the from object, set the output = 'object' and
destination = 'all'.
(3) You may also save the rasters as a series of .tif files in the same workspace
directory as the transition .gz tensor files and the cropped/downloaded
DEMs. This allows us to use getCosts within a loop for large numbers of origin
nodes without running into random access memory limitations. Do this by
setting output = 'file' and destination = 'all'.
(4) You may perform (2) and (3) simultaneously by setting
output == c('file','object') and destination = 'all'.
#### Example 1:
n <- 5
dem <- expand.grid(list(x = 1:(n * 100),
y = 1:(n * 100))) / 100
dem <- as.data.table(dem)
dem[, z := 250 * exp(-(x - n/2)^2) +
250 * exp(-(y - n/2)^2)]
#> x y z
#> 1: 0.01 0.01 1.0146139
#> 2: 0.02 0.01 1.0404641
#> 3: 0.03 0.01 1.0675194
#> 4: 0.04 0.01 1.0958300
#> 5: 0.05 0.01 1.1254477
#> ---
#> 249996: 4.96 5.00 1.0711366
#> 249997: 4.97 5.00 1.0428260
#> 249998: 4.98 5.00 1.0157707
#> 249999: 4.99 5.00 0.9899205
#> 250000: 5.00 5.00 0.9652271
dem <- rast(dem)
ext(dem) <- c(10000, 20000, 30000, 40000)
crs(dem) <- "+proj=lcc +lat_1=48 +lat_2=33 +lon_0=-100 +datum=WGS84"
# Export it so it doesn't just exist on the memory
dir <- tempdir()
writeRaster(dem, paste0(dir,"/DEM.tif"),overwrite=TRUE)
# Import raster, get the grid
dem <- rast(paste0(dir,"/DEM.tif"))
grid <- makeGrid(dem = dem, nx = n, ny = n, sources = TRUE)
# Select all tiles that exist between x = (12000,16000) and y = (32000,36000)
tiles <- ext(c(12000,16000,32000,36000))
tiles <- as.polygons(tiles)
crs(tiles) <- crs(grid)
tiles <- whichTiles(region = tiles, polys = grid)
region <- grid[8,]
# Generate five random points that fall within the region
points <- data.table(ID = 1:5,
x = runif(5, ext(region)[1], ext(region)[2]),
y = runif(5, ext(region)[3], ext(region)[4]))
# Make a world but limit it to the DEM grid size
defineWorld(source = grid, cut_slope = 0.5,
res = res(dem), dir = dir, overwrite=TRUE)
# Get time and work costs between points
costMatrix <- getCosts(grid[8,], from = points, dir = dir,
costs = c('dt','dW_l'), costFUN = energyCosts,
m = 70, v_max = 1.5, BMR = 76, k = 3.5, s = 0.05, l_s = 1,
L = 0.8)
#> [1] "Cropping Tile SECTOR_01 (1 of 4)"
#> [1] "Cropping Tile SECTOR_02 (2 of 4)"
#> [1] "Cropping Tile SECTOR_06 (3 of 4)"
#> [1] "Cropping Tile SECTOR_07 (4 of 4)"
#> [1] "Cropping Tile SECTOR_03 (1 of 2)"
#> [1] "Cropping Tile SECTOR_08 (2 of 2)"
#> [1] "Cropping Tile SECTOR_11 (1 of 2)"
#> [1] "Cropping Tile SECTOR_12 (2 of 2)"
#> [1] "Cropping Tile SECTOR_13 (1 of 1)"
#> [1] "Cropping Tile SECTOR_16 (1 of 2)"
#> [1] "Cropping Tile SECTOR_17 (2 of 2)"
#> [1] "Cropping Tile SECTOR_18 (1 of 1)"
#> [1] "Cropping Tile SECTOR_09 (1 of 3)"
#> [1] "Cropping Tile SECTOR_14 (2 of 3)"
#> [1] "Cropping Tile SECTOR_19 (3 of 3)"
#> [1] "Cropping Tile SECTOR_21 (1 of 2)"
#> [1] "Cropping Tile SECTOR_22 (2 of 2)"
#> [1] "Cropping Tile SECTOR_23 (1 of 1)"
#> [1] "Cropping Tile SECTOR_24 (1 of 1)"
#> [1] "Cropping Tile SECTOR_04 (1 of 1)"
#> [1] "Cropping Tile SECTOR_05 (1 of 2)"
#> [1] "Cropping Tile SECTOR_10 (2 of 2)"
#> [1] "Cropping Tile SECTOR_15 (1 of 1)"
#> [1] "Cropping Tile SECTOR_20 (1 of 1)"
#> [1] "Cropping Tile SECTOR_25 (1 of 1)"
#> Imported 9 Sectors
#>
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#> Warning: C:\Users\andre\AppData\Local\Temp\RtmpU5cHvW\World\costFUN.gz already defined. Ignoring input parameters.
#> Imported 9 Sectors
#>
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#> Warning: C:\Users\andre\AppData\Local\Temp\RtmpU5cHvW\World\costFUN.gz already defined. Ignoring input parameters.
#> Imported 9 Sectors
#>
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#### Example 2:
# Calculate the cost rasters to travel to ad from the center of a polygon
costRasters <- getCosts(grid[8,], from = grid[8,], dir = dir, destination = 'all',
polygons = 'center',
costs = c('dt','dW_l'), costFUN = energyCosts,
m = 70, v_max = 1.5, BMR = 76, k = 3.5, s = 0.05, l_s = 1,
L = 0.8)
#> Warning: C:\Users\andre\AppData\Local\Temp\RtmpU5cHvW\World\costFUN.gz already defined. Ignoring input parameters.
#> Imported 9 Sectors
#>
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#> Warning: C:\Users\andre\AppData\Local\Temp\RtmpU5cHvW\World\costFUN.gz already defined. Ignoring input parameters.
#> Imported 9 Sectors
#>
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#> Warning: C:\Users\andre\AppData\Local\Temp\RtmpU5cHvW\World\costFUN.gz already defined. Ignoring input parameters.
#> Imported 9 Sectors
#>
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