WFS (Web Feature Service) and WMS (Web Map Service) are standardized protocols for serving georeferenced map data over the internet:
When you use Argentum to import WFS layers, you’re getting actual vector data that you can analyze and manipulate in R:
library(Argentum)
library(sf)
# Get organization data
org <- argentum_select_organization(search = "Buenos Aires")
# List available layers
layers <- argentum_list_layers(org$Name)
# Import a specific layer
sf_layer <- argentum_import_wfs_layer(org$WFS_URL, layers$Name[1])
# Now you can work with the data using sf functions
st_crs(sf_layer)  # Check the coordinate reference system
plot(sf_layer)    # Basic plot of the geometryBefore importing data, you can check what capabilities a service offers:
Always implement proper error handling:
When working with WFS services:
After importing WFS data:
library(sf)
library(dplyr)
# Check the data structure
str(sf_layer)
# Basic statistics
summary(sf_layer)
# Spatial operations
sf_layer_transformed <- st_transform(sf_layer, 4326)
# Calculate areas if working with polygons
if (all(st_geometry_type(sf_layer) %in% c("POLYGON", "MULTIPOLYGON"))) {
  sf_layer$area <- st_area(sf_layer)
}While Argentum provides high-level functions, you can also work with WFS services directly:
Common issues and solutions:
argentum_list_layers() to get exact layer
namesPlanned features for future versions:
sessionInfo()
#> R version 4.3.1 (2023-06-16 ucrt)
#> Platform: x86_64-w64-mingw32/x64 (64-bit)
#> Running under: Windows 10 x64 (build 19045)
#> 
#> Matrix products: default
#> 
#> 
#> locale:
#> [1] LC_COLLATE=C                       LC_CTYPE=Spanish_Argentina.utf8   
#> [3] LC_MONETARY=Spanish_Argentina.utf8 LC_NUMERIC=C                      
#> [5] LC_TIME=Spanish_Argentina.utf8    
#> 
#> time zone: America/Buenos_Aires
#> tzcode source: internal
#> 
#> attached base packages:
#> [1] stats     graphics  grDevices utils     datasets  methods   base     
#> 
#> loaded via a namespace (and not attached):
#>  [1] digest_0.6.37     R6_2.5.1          fastmap_1.2.0     xfun_0.50        
#>  [5] cachem_1.1.0      knitr_1.49        htmltools_0.5.8.1 rmarkdown_2.29   
#>  [9] lifecycle_1.0.4   cli_3.6.1         sass_0.4.9        jquerylib_0.1.4  
#> [13] compiler_4.3.1    rstudioapi_0.17.1 tools_4.3.1       evaluate_1.0.3   
#> [17] bslib_0.8.0       yaml_2.3.10       rlang_1.1.1       jsonlite_1.8.9