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Summarize Prediction Rasters into Consensus Outputs

Source: R/summarize_raster_outputs.R
summarize_raster_outputs.Rd

Post-processing function that synthesizes per-time-step fold-vote rasters (output from generate_spatiotemporal_predictions) into binary consensus predictions and a temporal frequency summary. Each input raster contains integer vote counts per pixel the number of cross-validation folds that classified that pixel as suitable. The consensus threshold controls how many folds must agree for a pixel to be classified as suitable in the output binary rasters.

Usage

summarize_raster_outputs(predictions_dir, output_dir = NULL,
                         consensus = 1, file_pattern = "Prediction_.*\\.tif$",
                         overwrite = FALSE, verbose = TRUE)

Arguments

predictions_dir

Character. Directory containing prediction raster files, typically the output_dir used in generate_spatiotemporal_predictions.

output_dir

Character. Directory for output files. Defaults to predictions_dir if NULL.

consensus

Integer. Minimum number of folds that must agree on suitability for a pixel to be classified as suitable in the binary output. For example, consensus = 1 marks any pixel suitable if at least one fold predicts it suitable; consensus = 4 requires at least four folds to agree. Must be between 1 and the maximum vote count in the rasters (number of folds). Default is 1.

file_pattern

Character. Regular expression to match prediction raster files. Default is "Prediction_.*\.tif$".

overwrite

Logical. If TRUE, overwrites existing output files. If FALSE (default), existing files are skipped.

verbose

Logical. If TRUE (default), prints progress messages during processing.

Value

Invisibly returns a list containing:

  • consensus_stack: SpatRaster stack of per-time-step binary consensus rasters (one layer per input file).

  • frequency_raster: SpatRaster showing the proportion of time steps during which each pixel met the consensus threshold. Values range from 0 (never suitable) to 1 (always suitable).

  • consensus: the consensus threshold used.

  • n_timesteps: number of time steps processed.

  • consensus_dir: path to the directory containing per-time-step binary consensus rasters.

  • frequency_file: path to the written frequency raster file.

Details

Input rasters are fold-vote-count rasters produced by generate_spatiotemporal_predictions, where each pixel value is the number of cross-validation fold models that predicted suitability at that location for that time step. The consensus threshold is applied as: binary = as.integer(vote_count >= consensus).

The frequency raster (proportion of time steps suitable under the chosen consensus) serves as input to analyze_temporal_patterns for identifying long-term trends in suitability.

See also

Upstream: generate_spatiotemporal_predictions

Downstream: analyze_temporal_patterns

Examples

pred_dir <- system.file("extdata/predictions",
                        package = "TemporalModelR")

summarize_raster_outputs(
  predictions_dir = pred_dir,
  output_dir      = tempdir(),
  consensus       = 3,
  overwrite       = TRUE,
  verbose         = FALSE
)