Disaggregates a wind rose to a finer grid with terra::disagg(), interpolating between cells,
and multiplies conductance by fact. Conductance is a rate per hop between neighboring cells,
and hops on the finer grid are fact times shorter, so this rescaling keeps flow (conductance
times the distance to each neighbor) unchanged: wind moves material at the same speed on the
downscaled grid as on the original. Downscaling adds no wind information. It smooths the wind
field between the original cell centers, but does not represent real fine-scale variation
within cells, such as that caused by terrain.
Arguments
- x
A
wind_rose.- fact
A single integer: the factor by which to increase resolution. Each cell becomes
factxfactcells.- method
Interpolation method, passed to
terra::disagg():"bilinear"(the default) interpolates between the original cell centers;"near"gives each new cell the value of the cell it came from.
Value
A wind_rose with fact times as many rows and columns as x, and the same trans
and n_steps. Memory use and run time for connectivity analyses grow with the number of
cells, roughly fact^2.
Details
How much downscaling changes results, and whether it improves them, depends on the connectivity model.
Least-cost analyses. pairwise_least_cost() places sites at their actual locations
within cells by default (snap = FALSE), so it handles nearby sites without downscaling, and
downscaling changes its results little: typically by a few percent, reflecting the smoother
interpolated wind field. Downscaling does reduce error for nearby sites when sites are
snapped to cell centers, as in pairwise_least_cost(snap = TRUE), least_cost(), and
least_cost_paths().
Random walk analyses. The random walk functions treat each site as its cell, so downscaling
separates nearby sites into distinct cells (see check_cell_distance()). But the spread of a
random walk is numerical diffusion that scales with cell size (see random_walk()), so
downscaling also narrows the dispersal kernel: in one test, downscaling by a factor of 4 reduced
the spread of a stream-mode walk by 30 to 50 percent. Downscaling therefore changes the model
as well as the grid. Results at different resolutions are not directly comparable, so choose one
resolution for an analysis and treat it as part of the model specification.
Examples
rose <- windscape_example("wind_rose")
fine <- downscale(rose, 2)
dim(rose)
#> [1] 64 96 8
dim(fine)
#> [1] 128 192 8