Enhanced Field Data Model with ML Metadata Support — validate_field_data

Provides comprehensive validation for field data structures following constitutional principles for spatial analysis excellence. Ensures CRS consistency, geometry integrity, and data quality standards. Enhanced with ML-specific metadata support for feature importance, uncertainty maps, and spatial weights.

Usage

validate_field_data_structure(field_data, strict_validation = TRUE)

Arguments

field_data: List containing boundary, covariates, and metadata
strict_validation: Logical, apply strict constitutional standards

Value

Validated field data list with standardized structure and ML metadata

Examples

if (FALSE) { # \dontrun{
# Create enhanced field data with ML metadata
field_data <- list(
  boundary = sf::st_read("boundary.shp"),
  covariates = terra::rast("covariates.tif"),
  crs = "EPSG:32633",
  ml_metadata = list(
    feature_importance = c(0.3, 0.2, 0.5),
    uncertainty_maps = terra::rast("uncertainty.tif"),
    spatial_weights = matrix(c(1, 0.5, 0.5, 1), nrow = 2)
  )
)

# Validate and standardize
validated_data <- validate_field_data_structure(field_data)
} # }