Discovering Available Layers • firex

This vignette shows how to inspect the Wildfire Resilience Index (WRI) catalog before downloading data. Users start by listing available layers, then narrow the catalog to the layer ID they need. Catalog browsing reads the local STAC index bundled with the package, so this step does not require a large data download.

Setup

Load firex. No other packages are needed for catalog browsing.

library(firex)

Browsing the Full Catalog

wri_overview() reads the local STAC index and prints a structured summary of all 82 available layers. Call it with no arguments to see all domains, dimensions, and data types at a glance:

wri_overview()

WRI DATA SUMMARY
-------------------
Read at:      2026-05-11 16:07:50

Layer ID Naming Convention: wri_domain + wri_dimension + data_type

Collections (1): wri_ignitR

Unique wri_domain values (11): air_quality, communities, iconic_places,
iconic_species, infrastructure, livelihoods, natural_habitats,
sense_of_place, species, unknown, water

Unique data_type values (3): aggregate, final_score, indicator

Unique wri_dimension values (5): domain_score, recovery, resilience,
resistance, status

Total layers available: 82

The object summarizes the 82 available layers grouped by domain, dimension, and data type.

Getting the Catalog as a Data Frame

wri_overview_df() returns the same information as a flat data frame, one row per layer. This is useful for filtering with standard R tools:

df <- wri_overview_df()
nrow(df)
#> [1] 82

# Filter to water-domain aggregate layers
subset(
  df,
  wri_domain == "water" & data_type == "aggregate",
  select = c(id, wri_dimension, data_type)
)
#>                    id wri_dimension data_type
#> 75 water_domain_score  domain_score aggregate
#> 76   water_resilience    resilience aggregate
#> 77   water_resistance    resistance aggregate
#> 80       water_status        status aggregate

The ten named WRI domains are air_quality, communities, iconic_places, iconic_species, infrastructure, livelihoods, natural_habitats, sense_of_place, species, and water. The unknown domain is used for the overall WRI_score layer. The five WRI dimension values are domain_score, recovery, resilience, resistance, and status.

Inspecting a Single Layer

Once you have identified a layer ID, layer_info() retrieves its full metadata record, including the hosted COG URL, geographic extent, CRS, and classification properties. Transposing with t() makes it easier to read:

t(layer_info("WRI_score"))
#>            WRI_score
#> id         WRI_score
#> collection wri_ignitR
#> asset_href https://knb.ecoinformatics.org/.../WRI_score.tif
#> proj_code  EPSG:5070
#> data_type  final_score
#> wri_domain unknown
#> is_hosted  TRUE
#> xmin       -146.2082
#> ymin        19.1074
#> xmax        173.7109
#> ymax         54.8056

The asset_href field is the direct URL to the hosted COG file on KNB. get_layer() uses this URL to open a virtual connection via GDAL; you do not need to use it directly. The xmin, ymin, xmax, and ymax fields give the layer’s geographic extent in WGS84 (EPSG:4326).

Advanced: Querying STAC Items Directly

For filtering on combinations of properties not easily expressed as data frame queries, query_stac_flexible() filters the underlying STAC item list by any property value:

catalog <- wri_overview()
items <- lapply(catalog$data$items, function(x) x$item)

# All resistance indicators in the water domain
water_resist <- query_stac_flexible(
  items,
  wri_domain = "water",
  wri_dimension = "resistance",
  data_type = "indicator"
)

vapply(water_resist, function(x) x$id, character(1))
#> [1] "water_resistance_drought_plans"
#> [2] "water_resistance_water_treatment"

Once users identify a layer ID, they can pass that ID to get_layer() or use an existing spatial object as the area of interest.