Converts environmental point data into multi-resolution H3 hexagonal bins
with aggregated statistics and geometries for mapping. Uses dbplyr lazy
evaluation to defer collection until after aggregation.
Usage
prep_env_hex(df_env, res_range, env_stat)
Arguments
- df_env
dbplyr lazy table with H3 index columns (hex_h3res*) and qty column
- res_range
Integer vector of H3 resolution levels to generate (e.g., 3:5)
- env_stat
Character string specifying aggregation function: "mean", "median", "min", "max", "sd"
Value
List of sf objects, one per resolution level, each with columns:
resolution - H3 resolution level
hexid - H3 hexagon identifier
env.value - aggregated environmental value
tooltip - rounded value for display
geometry - sf geometry (hexagon polygon)
Details
This function uses dbplyr lazy evaluation to efficiently aggregate data
across multiple H3 resolutions via union_all. Geometries are joined
from a pre-computed sf object (sf_hex).
Examples
if (FALSE) { # \dontrun{
df_env <- get_env("t_deg_c", qtr = 1:4, date_range = c("2000-01-01", "2020-12-31"), min_depth = 0, max_depth = 100)
env_hex <- prep_env_hex(df_env, res_range = 3:5, env_stat = "mean")
} # }
