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Calculate the benefit of a hexagon from grts results.

Source: R/BASS_benefit.R
calculate_benefit.Rd

Calculate the benefit of a hexagon from grts results.

Usage

calculate_benefit(
  land_hex,
  samples,
  hex_id = hex_id,
  stratum_id = NULL,
  non_random_set = NULL,
  land_cover_weights = NULL,
  crs = 4326,
  coords = c("lon", "lat"),
  quiet = FALSE
)

Arguments

land_hex

(Spatial) Data frame. Land Cover data by hexagon. If non-spatial, will be converted to spatial sf data frame using the crs and coords arguments. Requires columns identifying the Hex ID as well as the Stratum ID (see hex_id and stratum_id respectively).

samples

(Spatial) Data frame. Results from draw_random_samples().

hex_id

Column. Identifies hexagon IDs (e.g., default hex_id).

stratum_id

Column. Identifies larger area (e.g., StudyAreaID or Province).

non_random_set

Character vector. hex_ids of hexagons to include as a non randomly selected set.

land_cover_weights

Data frame. Proportional weights (weights column) for specific types of landcover (lc column). lc should correspond to the same landcover column names as the hex data.

crs

Numeric, character, or sf/sfc. Coordinate reference system. Must be valid input to sf::st_crs().

coords

Character vector. Names of the columns containing X and Y coordinates (default c("lon", "lat")).

quiet

Logical. Whether to suppress progress messages.

Value

Spatial data frame with benefits per hex

Examples


# Using example data psu_hexagons and psu_samples

calculate_benefit(
  land_hex = psu_hexagons,
  samples = psu_samples,
  non_random_set = c("SA_09", "SA_22", "SA_47"))
#> ℹ Spatial object land_hex should be POINTs not POLYGONs
#> • Don't worry, I'll fix it!
#> • Assuming constant attributes and using centroids as points
#> Simple feature collection with 33 features and 2 fields
#> Geometry type: POINT
#> Dimension:     XY
#> Bounding box:  xmin: 25 ymin: 43.30127 xmax: 275 ymax: 259.8076
#> Projected CRS: NAD83 / Ontario MNR Lambert
#> First 10 features:
#>    hex_id     benefit             geometry
#> 1   SA_09 0.011928502  POINT (25 43.30127)
#> 2   SA_10 0.019759576  POINT (25 129.9038)
#> 3   SA_11 0.018844331  POINT (25 216.5064)
#> 4   SA_14 0.014763746  POINT (50 86.60254)
#> 5   SA_15 0.010130728  POINT (50 173.2051)
#> 6   SA_16 0.009821685  POINT (50 259.8076)
#> 7   SA_17 0.011240254  POINT (75 43.30127)
#> 8   SA_18 0.016422632  POINT (75 129.9038)
#> 9   SA_19 0.016226578  POINT (75 216.5064)
#> 10  SA_22 0.012322357 POINT (100 86.60254)

# Specify a non-random set

calculate_benefit(
 land_hex = psu_hexagons,
 samples = psu_samples,
 non_random_set = c("SA_09", "SA_22", "SA_47"))
#> ℹ Spatial object land_hex should be POINTs not POLYGONs
#> • Don't worry, I'll fix it!
#> • Assuming constant attributes and using centroids as points
#> Simple feature collection with 33 features and 2 fields
#> Geometry type: POINT
#> Dimension:     XY
#> Bounding box:  xmin: 25 ymin: 43.30127 xmax: 275 ymax: 259.8076
#> Projected CRS: NAD83 / Ontario MNR Lambert
#> First 10 features:
#>    hex_id     benefit             geometry
#> 1   SA_09 0.011928502  POINT (25 43.30127)
#> 2   SA_10 0.019759576  POINT (25 129.9038)
#> 3   SA_11 0.018844331  POINT (25 216.5064)
#> 4   SA_14 0.014763746  POINT (50 86.60254)
#> 5   SA_15 0.010130728  POINT (50 173.2051)
#> 6   SA_16 0.009821685  POINT (50 259.8076)
#> 7   SA_17 0.011240254  POINT (75 43.30127)
#> 8   SA_18 0.016422632  POINT (75 129.9038)
#> 9   SA_19 0.016226578  POINT (75 216.5064)
#> 10  SA_22 0.012322357 POINT (100 86.60254)

# Without GRTS

non_grts_samples <- draw_random_samples(
  land_hex = psu_hexagons,
  num_runs = 3,
  n_samples = 10,
  use_grts = FALSE)
#> ℹ Spatial object land_hex should be POINTs not POLYGONs
#> • Don't worry, I'll fix it!
#> • Assuming constant attributes and using centroids as points

calculate_benefit(
 land_hex = psu_hexagons,
 samples = non_grts_samples)
#> ℹ Spatial object land_hex should be POINTs not POLYGONs
#> • Don't worry, I'll fix it!
#> • Assuming constant attributes and using centroids as points
#> Simple feature collection with 33 features and 2 fields
#> Geometry type: POINT
#> Dimension:     XY
#> Bounding box:  xmin: 25 ymin: 43.30127 xmax: 275 ymax: 259.8076
#> Projected CRS: NAD83 / Ontario MNR Lambert
#> First 10 features:
#>    hex_id     benefit             geometry
#> 1   SA_09 0.008367774  POINT (25 43.30127)
#> 2   SA_10 0.010510586  POINT (25 129.9038)
#> 3   SA_11 0.007752895  POINT (25 216.5064)
#> 4   SA_14 0.006910977  POINT (50 86.60254)
#> 5   SA_15 0.001677754  POINT (50 173.2051)
#> 6   SA_16 0.004713814  POINT (50 259.8076)
#> 7   SA_17 0.005191574  POINT (75 43.30127)
#> 8   SA_18 0.012027388  POINT (75 129.9038)
#> 9   SA_19 0.006278050  POINT (75 216.5064)
#> 10  SA_22 0.010723963 POINT (100 86.60254)