Generate Age Population Raster

Creates age-stratified population raster layers from predictor data and gamma distribution parameters. Supports parallel processing and caching of results. The output is a multi-layer raster stack with each layer representing the population proportion for a specific age interval.

Usage

generate_age_pop_raster(
  predictor_data,
  scale_pred,
  shape_pred,
  age_range = c(0, 10),
  age_interval = 1,
  country_code,
  ignore_cache = FALSE,
  output_dir,
  n_cores = parallel::detectCores() - 2
)

Arguments

predictor_data

Data frame containing population and spatial data with columns: country, region, district, pop, web_x, web_y

scale_pred

Matrix of scale parameters for gamma distribution predictions

shape_pred

Matrix of shape parameters for gamma distribution predictions

age_range

Numeric vector of length 2 specifying min and max ages, default c(0,99)

age_interval

Numeric interval size between age groups in years, default 1

country_code

Character ISO3 country code

ignore_cache

Logical whether to ignore cached results, default FALSE

output_dir

Character path to output directory

n_cores

Integer number of cores for parallel processing, default detectCores()-2

Value

SpatRaster object (terra package) containing multiple layers, where each layer represents the population proportion for an age interval. Layer names indicate the age range (e.g., "Age 0 to 1 years"). The raster uses EPSG:3857 projection with 5000m resolution.

Details

The function processes age intervals sequentially, computing population proportions using parallel processing. Results are cached as a GeoTIFF file for future use. The output raster maintains spatial properties of the input data and is suitable for GIS analysis and visualization.

Examples

# \donttest{
predictor_data <- data.frame(
 country = rep("CountryX", 100),
 region = rep("RegionA", 100),
 district = rep("District1", 100),
 pop = sample(100:1000, 100, replace = TRUE),
 web_x = runif(100, -100, 100),
 web_y = runif(100, -50, 50)
)

scale_pred <- matrix(runif(100 * 10, 1, 5), nrow = 100, ncol = 10)
shape_pred <- matrix(runif(100 * 10, 1, 5), nrow = 100, ncol = 10)

res <- generate_age_pop_raster(predictor_data,
                       scale_pred,
                       shape_pred,
                       country_code = "COD",
                       output_dir = file.path(tempdir()),
                       n_cores = 1)
#> ℹ Processing interval 1/11...
#> ✔ Completed interval 1/11.
#> 
#> ℹ Processing interval 2/11...
#> ✔ Completed interval 2/11.
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#> ✔ Completed interval 3/11.
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#> ✔ Completed interval 4/11.
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#> ✔ Completed interval 5/11.
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#> ✔ Completed interval 6/11.
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#> ✔ Completed interval 7/11.
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#> ✔ Completed interval 9/11.
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#> ℹ Processing interval 10/11...
#> ✔ Completed interval 10/11.
#> 
#> ℹ Processing interval 11/11...
#> ✔ Completed interval 11/11.
#> 
#> ✔ Raster stack saved to /tmp/RtmpioKZmp/cod_age_pop_grid_0_10_yrs_by_1yrs.tif
# }