# Load example data
data("occ_flagged", package = "RuHere")
# Mapping the density of records
r_density <- richness_here(occ_flagged, summary = "records", res = 0.5)
ggrid_here(r_density)
# We can also summarize key features:
# 1. Identifying problematic regions by summing error flags
# We create a variable to store the sum of logical flags (TRUE = 1, FALSE = 0)
total_flags <- occ_flagged$florabr_flag +
occ_flagged$wcvp_flag +
occ_flagged$iucn_flag +
occ_flagged$cultivated_flag +
occ_flagged$inaturalist_flag +
occ_flagged$duplicated_flag
names(total_flags) <- occ_flagged$record_id
# Using summary = "records" with to see the average accumulation of errors
# with fun = mean to see the average accumulation
r_flags <- richness_here(occ_flagged, summary = "records",
field = total_flags,
field_name = "Number of flags",
fun = mean, res = 0.5)
ggrid_here(r_flags)
# 2. Or we can summarize organisms traits spatially
# Simulating a trait (e.g., mass) for each unique record
spp <- unique(occ_flagged$record_id)
sim_mass <- setNames(runif(length(spp), 10, 50), spp)
r_trait <- richness_here(occ_flagged, summary = "records",
field = sim_mass, field_name = "Mass",
fun = mean, res = 0.5)
ggrid_here(r_trait)
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