---
title: "knfi"
output: rmarkdown::html_vignette
vignette: >
%\VignetteIndexEntry{knfi}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
---
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
```
```{r loaddata, eval = dir.exists("D:/NFI/NFI5/")}
library(knfi)
# Load tree and CWD data for all districts
nfi5_data <- read_nfi("D:/NFI/NFI5", district = NULL, tables = c("tree", "cwd"), recursive = TRUE)
# Applying hierarchical filtering to select only privately owned forest subplots.
# Ensures all child tables' subplots match the filtered plot table's subplots.
nfi5_data <- filter_nfi(nfi5_data, c("plot$OWN_CD == '5'"), hier = TRUE)
# Switch column names from English to original Korean names
nfi5_data_kor <- switchcol_nfi(nfi5_data)
```
```{r calculate}
library(knfi)
# The Korean and English names of the column names
data("nfi_col")
# National Forest Inventory data for Donghae-si, Gangwon-do, Republic of Korea for testing the function
data("nfi_donghae")
# calculates comprehensive descriptive statistics for study area
summary_stats <- summary_nfi(nfi_donghae, continuousplot = T)
# Calculate importance values using genus
importance_genus <- iv_nfi(nfi_donghae, sp = "GENUS", continuousplot = T)
# Calculate tree diversity indices using basal area
diversity_tree_ba <- diversity_nfi(nfi_donghae, sp = "SP", table = "tree", basal = TRUE, continuousplot = T)
# Calculate biomass by administrative district
biomass_district <- biomass_nfi(nfi_donghae, plotgrp = "SGG", continuousplot = T)
# Calculate CWD biomass grouped by administrative district and decay class
cwd_grpby <- cwd_biomass_nfi(nfi_donghae, plotgrp = "SGG", treegrp = "DECAY", continuousplot = T)
# Create a bar plot of importance values at 5-year intervals
tsvis_iv_bar <- tsvis_nfi(nfi_donghae, y = "iv", output = "bar", isannual = FALSE, continuousplot = T)
# Generate a line plot of carbon biomass over time
tsvis_bm_line <- tsvis_nfi(nfi_donghae, y = "biomass", continuousplot = T,
bm_type = "carbon", output = "line")
# # Create a map of volume at the sido level
# remotes::install_github("SYOUNG9836/kadmin")
# tsvis_bm_map <- tsvis_nfi(nfi_donghae, admin = "sido", continuousplot = T,
# y = "biomass", bm_type = "volume", output = "map")
```