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Spatial Block Cross-Validation

Source: R/spatial_blocks.R
spatial_block_folds.Rd

Creates spatial cross-validation folds by dividing the study area into rectangular blocks and assigning observations to folds based on their block membership. This method ensures spatial separation between training and test sets.

Usage

spatial_block_folds(
  data,
  x = NULL,
  y = NULL,
  k = 5,
  block_size = NULL,
  n_blocks = NULL,
  assignment = "systematic",
  seed = NULL
)

Arguments

data

Spatial observations (data.frame or sf object)

x

Name of the x coordinate column (required for data.frame, ignored for sf)

y

Name of the y coordinate column (required for data.frame, ignored for sf)

k

Number of folds (default: 5)

block_size

Size of blocks as c(width, height) in coordinate units

n_blocks

Number of blocks in x and y directions as c(nx, ny)

assignment

Strategy for assigning blocks to folds: "systematic" or "random"

seed

Random seed for reproducibility (default: NULL)

Value

An object of class "spatial_folds" containing fold assignments

Details

The spatial block method divides the spatial extent into a grid of rectangular blocks. Two approaches are available:

  • Fixed block size: Specify block_size to control block dimensions

  • Fixed number of blocks: Specify n_blocks to control grid resolution

If neither is specified, the function attempts to create approximately sqrt(k) blocks in each direction.

Assignment strategies:

  • "systematic": Assigns blocks to folds in a systematic pattern

  • "random": Randomly assigns blocks to folds

See also

Other spatial cross-validation functions: spatial_buffer_folds(), spatial_cluster_folds(), spatial_folds(), spatial_split()

Examples

if (FALSE) { # \dontrun{
data(sample_spatial_data)
folds <- spatial_block_folds(
  data = sample_spatial_data,
  x = "longitude",
  y = "latitude",
  k = 5,
  block_size = c(200, 200)
)
} # }