Nothing
## ----setup, include=FALSE-----------------------------------------------------
knitr::opts_chunk$set(
echo = TRUE,
eval = isTRUE(try(local_NASIS_defined(), silent = TRUE)) ||
!as.logical(Sys.getenv("R_SOILDB_SKIP_LONG_EXAMPLES", unset = "TRUE")),
message = FALSE,
warning = FALSE,
fig.height = 7,
fig.width = 7
)
## -----------------------------------------------------------------------------
# library(soilDB)
#
# gpkg_dir <- tempdir()
#
# AREASYMBOLS <- c("KS129", "KS187")
#
# ssurgo_zip <- downloadSSURGO(
# areasymbol = AREASYMBOLS,
# destdir = gpkg_dir
# )
## ----warning=FALSE, message=FALSE---------------------------------------------
# # Create a local GeoPackage from the downloaded ZIP
# gpkg_path <- file.path(gpkg_dir, "ssurgo.gpkg")
#
# createSSURGO(
# gpkg_path,
# exdir = gpkg_dir
# )
## -----------------------------------------------------------------------------
# library(DBI)
# library(RSQLite)
#
# # Connect to the GeoPackage
# con <- dbConnect(SQLite(), gpkg_path)
#
# # List available tables
# dbListTables(con)
## -----------------------------------------------------------------------------
# dbListFields(con, "mapunit")
## -----------------------------------------------------------------------------
# dbGetQuery(con, "SELECT * FROM mapunit LIMIT 5")
## -----------------------------------------------------------------------------
# query <- "
# SELECT mu.musym, mu.muname, c.compname, c.comppct_r
# FROM mapunit mu
# JOIN component c ON mu.mukey = c.mukey
# LIMIT 10
# "
# dbGetQuery(con, query)
## -----------------------------------------------------------------------------
# library(sf)
#
# # Read spatial map units
# spatial_mu <- st_read(gpkg_path, layer = "mupolygon")
#
# spatial_mu
#
# # Plot the map units
# plot(st_geometry(spatial_mu))
## -----------------------------------------------------------------------------
# library(sf)
#
# # Read spatial map units
# spatial_mu <- sf::st_read(gpkg_path, layer = "mupolygon")
#
# # Read tabular data
# mapunit <- dbReadTable(con, "mapunit")
# component <- dbReadTable(con, "component")
#
# # Disconnect when done
# dbDisconnect(con)
## -----------------------------------------------------------------------------
# # Get dominant component per map unit
# dominant_comp <- aggregate(
# comppct_r ~ mukey,
# data = component,
# max
# )
#
# # Join with spatial data
# spatial_mu$comppct_r <- dominant_comp$comppct_r[match(spatial_mu$mukey, dominant_comp$mukey)]
#
# # Plot (small subset of extent)
# plot(
# spatial_mu["comppct_r"],
# main = "Dominant Component Percentage (comppct_r)",
# breaks = seq(0, 100, 10),
# key.pos = 4,
# border = NA,
# pal = hcl.colors(10)
# )
## -----------------------------------------------------------------------------
# # Get most common hydgrp per mukey
# hydgrp_tab <- aggregate(
# hydgrp ~ mukey,
# data = component,
# function(x) names(sort(table(x), decreasing = TRUE))[1]
# )
#
# # Convert to ordered factor
# hydgrp_tab[[2]] <- NASISChoiceList(hydgrp_tab)[[2]]
#
# # Join with spatial data
# spatial_mu$hydgrp <- hydgrp_tab$hydgrp[match(spatial_mu$mukey, hydgrp_tab$mukey)]
#
# spatial_mu
#
# # Plot
# plot(
# spatial_mu["hydgrp"],
# main = "Hydrologic Group (hydgrp)",
# key.pos = 4,
# border = NA,
# pal = rev(hcl.colors(7))
# )
## -----------------------------------------------------------------------------
# # Get most common drainage class per mukey
# drainage_tab <- aggregate(
# drainagecl ~ mukey,
# data = component,
# function(x) names(sort(table(x), decreasing = TRUE))[1]
# )
#
# # Convert to ordered factor
# drainage_tab[[2]] <- NASISChoiceList(drainage_tab)[[2]]
#
# # Join with spatial data
# spatial_mu$drainagecl <- drainage_tab$drainagecl[match(spatial_mu$mukey, drainage_tab$mukey)]
#
# # Plot
# plot(
# spatial_mu["drainagecl"],
# main = "Drainage Class (drainagecl)",
# border = NA,
# key.pos = 4,
# pal = rev(hcl.colors(8))
# )
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