knfi

library(knfi)

# Load tree and CWD data for all districts
nfi5_data <- read_nfi("D:/NFI/NFI5", district = NULL, tables = c("tree", "cwd"))

# Applying hierarchical filtering to select only privately owned forest subplots.
# Ensures all child tables' subplots match the filtered plot table's subplots.
nfi5_data <- filter_nfi(nfi5_data, c("plot$OWN_CD == '5'"), hier = TRUE)

# Switch column names from English to original Korean names
nfi5_data_kor <- switchcol_nfi(nfi5_data)

library(knfi)

data("nfi_donghae")

# calculates comprehensive descriptive statistics for study area
summary_stats <- summary_nfi(nfi_donghae)

# Calculate importance values using genus
importance_genus <- iv_nfi(nfi_donghae, sp = "GENUS")

# Calculate tree diversity indices using basal area
diversity_tree_ba <- diversity_nfi(nfi_donghae, sp = "SP", table = "tree", basal = TRUE)

# Calculate biomass by administrative district
biomass_district <- biomass_nfi(nfi_donghae, plotgrp = "SGG")

# Calculate CWD biomass grouped by administrative district and decay class
cwd_grpby <- cwd_biomass_nfi(nfi_donghae, plotgrp = "SGG", treegrp = "DECAY")

# Create a bar plot of importance values at 5-year intervals
tsvis_iv_bar <- tsvis_nfi(nfi_donghae, y = "iv", output = "bar", isannual = FALSE)

# Generate a line plot of carbon biomass over time
tsvis_bm_line <- tsvis_nfi(nfi_donghae, y = "biomass", 
                            bm_type = "carbon", output = "line")

# # Create a map of volume at the sido level
# tsvis_bm_map <- tsvis_nfi(nfi_donghae, admin = "sido", 
#                            y = "biomass", bm_type = "volume", output = "map")