From c218e1727e43acf157abf460cd500c4a0e2219cf Mon Sep 17 00:00:00 2001 From: SYOUNG9836 <78527477+SYOUNG9836@users.noreply.github.com> Date: Fri, 27 Sep 2024 06:44:55 +0000 Subject: [PATCH] =?UTF-8?q?Deploying=20to=20gh-pages=20from=20@=20SYOUNG98?= =?UTF-8?q?36/knfi@9c20d5274ab16ab67e4f4fe52bd0b5870bc6ee04=20=F0=9F=9A=80?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- index.html | 17 ++++++++--------- pkgdown.yml | 2 +- reference/biomass_nfi.html | 2 -- reference/cwd_biomass_nfi.html | 2 -- reference/diversity_nfi.html | 2 -- reference/iv_nfi.html | 2 -- reference/read_nfi.html | 8 ++++++-- reference/summary_nfi.html | 2 -- reference/switchcol_nfi.html | 2 -- reference/tsvis_nfi.html | 11 +++-------- search.json | 2 +- sitemap.xml | 2 -- 12 files changed, 19 insertions(+), 35 deletions(-) diff --git a/index.html b/index.html index 4bf235b..a227e0e 100644 --- a/index.html +++ b/index.html @@ -5,7 +5,7 @@ -Analysis of Korean National Forest Inventory DB • knfi +Analysis of Korean National Forest Inventory database • knfi @@ -16,9 +16,9 @@ - - - + + + @@ -56,8 +56,8 @@
-

- knfi: Analysis of Korean National Forest Inventory DB +

+ knfi: Analysis of Korean National Forest Inventory database

@@ -66,7 +66,7 @@

Overview

-

Understanding the current status of forest resources is essential for monitoring changes in the forest ecosystem and producing related statistics. In South Korea, the National Forest Inventory (NFI) surveys over 4,500 sample plots nationwide every five years and records 70 items, including forest surveys, forest resource surveys, and forest vegetation surveys. Many researchers are using NFI as primary data for research when estimating biomass or analyzing the importance value of each species in the time and space suitable for the research purpose. However, the accumulation of various forest survey data across the country limits the use of vast data. Therefore, this study developed an algorithm that efficiently processes vast amounts of NFI data in time and space using the statistical analysis software R. The developed algorithm first reconstructs NFI in time and space according to the researcher’s purpose and performs integrity verification to maintain data quality. Subsequently, summary statistics, biodiversity, importance value, and biomass are analyzed using the verified data. Finally, visualizing the analysis results allows spatio-temporal access to forest ecosystem changes.

+

Understanding the current status of forest resources is essential for monitoring changes in the forest ecosystem and producing related statistics. In South Korea, the National Forest Inventory (NFI) surveys over 4,500 sample plots nationwide every five years and records 70 items, including forest surveys, forest resource surveys, and forest vegetation surveys. Many researchers are using NFI as primary data for research when estimating biomass or analyzing the importance value of each species in the time and space suitable for the research purpose. However, the accumulation of various forest survey data across the country limits the use of vast data. Therefore, this study developed an algorithm that efficiently processes vast amounts of NFI data in time and space using the statistical analysis software R. The developed algorithm first reconstructs NFI in time and space according to the researcher’s purpose and performs integrity verification to maintain data quality. Subsequently, summary statistics, biodiversity, importance value, and biomass are analyzed using the verified data. Finally, visualizing the analysis results allows spatio-temporal access to forest ecosystem changes. This algorithmic approach significantly enhances the efficiency of processing and analyzing NFI data. It’s important to note that the raw NFI data is not included in the developed R package. Researchers interested in accessing the original NFI datasets should visit the Korea Forest Service Forestry Statistics Platform https://kfss.forest.go.kr/stat/ptl/article/articleList.do?curMenu=11694&bbsId=microdataboard to manually download the annual NFI file subsets as .zip files. This package is designed to process and analyze these downloaded datasets.

Plot 1

Distribution of National Forest Inventory sample plots (left) and sampling design of the National Forest Inventory (right) (Korea Forest Research Institute, 2011)

Plot 2

@@ -94,8 +94,7 @@

Links

License

diff --git a/pkgdown.yml b/pkgdown.yml index dd3f3e0..0c3b77f 100644 --- a/pkgdown.yml +++ b/pkgdown.yml @@ -3,7 +3,7 @@ pkgdown: 2.1.1 pkgdown_sha: ~ articles: knfi: knfi.html -last_built: 2024-09-26T03:39Z +last_built: 2024-09-27T06:44Z urls: reference: https://syoung9836.github.io/knfi/reference article: https://syoung9836.github.io/knfi/articles diff --git a/reference/biomass_nfi.html b/reference/biomass_nfi.html index 1643689..e201f88 100644 --- a/reference/biomass_nfi.html +++ b/reference/biomass_nfi.html @@ -137,14 +137,12 @@

Examples# Basic usage biomass <- biomass_nfi(nfi_donghae) -# \donttest{ # Calculate biomass by administrative district district_biomass <- biomass_nfi(nfi_donghae, plotgrp = "SGG") # Calculate biomass for each plot plot_biomass <- biomass_nfi(nfi_donghae, byplot = TRUE) #> Warning: param 'byplot' has priority over param 'strat' -# }

diff --git a/reference/cwd_biomass_nfi.html b/reference/cwd_biomass_nfi.html index 66e9eba..db4b5b3 100644 --- a/reference/cwd_biomass_nfi.html +++ b/reference/cwd_biomass_nfi.html @@ -119,14 +119,12 @@

Examples# Basic usage cwd <- cwd_biomass_nfi(nfi_donghae) -# \donttest{ # Calculate CWD biomass grouped by administrative district and decay class cwd_grp <- cwd_biomass_nfi(nfi_donghae, plotgrp = "SGG", treegrp = "DECAY") # Calculate CWD biomass for each plot plot_biomass <- cwd_biomass_nfi(nfi_donghae, byplot = TRUE) #> Warning: param 'byplot' has priority over param 'strat' -# }

diff --git a/reference/diversity_nfi.html b/reference/diversity_nfi.html index 373f1c4..be470e2 100644 --- a/reference/diversity_nfi.html +++ b/reference/diversity_nfi.html @@ -149,10 +149,8 @@

Examples# Calculate tree diversity indices using basal area tree_ba_diversity <- diversity_nfi(nfi_donghae, sp = "SP", table = "tree", basal = TRUE) -# \donttest{ # Calculate tree diversity indices using number of individuals tree_indi_diversity <- diversity_nfi(nfi_donghae, sp = "SP", table = "tree", basal = FALSE) -# } diff --git a/reference/iv_nfi.html b/reference/iv_nfi.html index 3f0ae75..42a9a62 100644 --- a/reference/iv_nfi.html +++ b/reference/iv_nfi.html @@ -131,10 +131,8 @@

Examples# Calculate importance values without frequency importance <- iv_nfi(nfi_donghae, sp = "SP", frequency = FALSE) -# \donttest{ # Calculate importance values using genus genus_importance <- iv_nfi(nfi_donghae, sp = "GENUS") -# } diff --git a/reference/read_nfi.html b/reference/read_nfi.html index b8dc427..6cfb031 100644 --- a/reference/read_nfi.html +++ b/reference/read_nfi.html @@ -96,6 +96,9 @@

Details

Note

To manually download subsets of the annual NFI file, visit the Korea Forest Service Forestry Statistics Platform (https://kfss.forest.go.kr/stat/), download .zip files, and extract them.

+

-The 5th National Forest Inventory file: https://kfss.forest.go.kr/stat/ptl/article/articleFileDown.do?fileSeq=2995&workSeq=2203 +-The 6th National Forest Inventory file: https://kfss.forest.go.kr/stat/ptl/article/articleFileDown.do?fileSeq=2996&workSeq=2204 +-The 7th National Forest Inventory file: https://kfss.forest.go.kr/stat/ptl/article/articleFileDown.do?fileSeq=2997&workSeq=2205

Use data("col_name") to view the Korean and English names of the column names.

While the National Forest Inventory undergoes rigorous quality control, including internal reviews and field inspections, errors may still exist due to the extensive nature of the survey (approximately 4,000 plots and over 70 items in the 7th phase). Please use the data cautiously and report any anomalies to help improve our algorithms.

@@ -109,10 +112,11 @@

Note

Examples

- 
if (FALSE) { # \dontrun{
+    
# \donttest{
  # Load tree and CWD data for all districts
  nfi5_data <- read_nfi("D:/NFI/NFI5", district = NULL, tables = c("tree", "cwd"))
-} # }
+#> Error in read_nfi("D:/NFI/NFI5", district = NULL, tables = c("tree", "cwd")): Directory  D:/NFI/NFI5/  does not exist.
+# }
diff --git a/reference/summary_nfi.html b/reference/summary_nfi.html index 4c2afd3..17ebc88 100644 --- a/reference/summary_nfi.html +++ b/reference/summary_nfi.html @@ -125,13 +125,11 @@

Examples# Basic usage summary_stats <- summary_nfi(nfi_donghae) -# \donttest{ # Summarize by the group, including all land types grouped_stats <- summary_nfi(nfi_donghae, plotgrp = "OWN_CD", stockedland = FALSE) # Summarize by individual plots, including both trees and shrubs plot_summaries <- summary_nfi(nfi_donghae, byplot = TRUE, talltree = FALSE) -# }

diff --git a/reference/switchcol_nfi.html b/reference/switchcol_nfi.html index 1e0e58d..3aa8e29 100644 --- a/reference/switchcol_nfi.html +++ b/reference/switchcol_nfi.html @@ -71,10 +71,8 @@

Examples#Switch column names from English to original Korean names nfi_donghae_kor <- switchcol_nfi(nfi_donghae) -# \donttest{ # Switch column names from original Korean to English names nfi_donghae_eng <- switchcol_nfi(nfi_donghae_kor) -# } diff --git a/reference/tsvis_nfi.html b/reference/tsvis_nfi.html index e7ca990..b18ac55 100644 --- a/reference/tsvis_nfi.html +++ b/reference/tsvis_nfi.html @@ -149,9 +149,6 @@

Examples

 data("nfi_donghae")
 
-
-# \donttest{
-
 # Visualize importance values as a table
 tsvis_iv <- tsvis_nfi(nfi_donghae, y = "iv", output = "table")
 
@@ -161,14 +158,12 @@ 
Examples# Generate a line plot of carbon biomass over time, grouped by age class
 tsvis_bm_line <- tsvis_nfi(nfi_donghae, y = "biomass", 
                             bm_type = "carbon", output = "line", plotgrp = "AGE_CLS")
-
-# }
-
-if (FALSE) { # \dontrun{
+                            
+# \donttest{
 # 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")
-} # }
+# }
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EXCEPT OTHERWISE STATED WRITING COPYRIGHT HOLDERS /PARTIES PROVIDE PROGRAM “” WITHOUT WARRANTY KIND, EITHER EXPRESSED IMPLIED, INCLUDING, LIMITED , IMPLIED WARRANTIES MERCHANTABILITY FITNESS PARTICULAR PURPOSE. ENTIRE RISK QUALITY PERFORMANCE PROGRAM . PROGRAM PROVE DEFECTIVE, ASSUME COST NECESSARY SERVICING, REPAIR CORRECTION.","code":""},{"path":"https://syoung9836.github.io/knfi/LICENSE.html","id":"id_16-limitation-of-liability","dir":"","previous_headings":"TERMS AND CONDITIONS","what":"16. Limitation of Liability","title":"GNU General Public License","text":"EVENT UNLESS REQUIRED APPLICABLE LAW AGREED WRITING COPYRIGHT HOLDER, PARTY MODIFIES /CONVEYS PROGRAM PERMITTED , LIABLE DAMAGES, INCLUDING GENERAL, SPECIAL, INCIDENTAL CONSEQUENTIAL DAMAGES ARISING USE INABILITY USE PROGRAM (INCLUDING LIMITED LOSS DATA DATA RENDERED INACCURATE LOSSES SUSTAINED THIRD PARTIES FAILURE PROGRAM OPERATE PROGRAMS), EVEN HOLDER PARTY ADVISED POSSIBILITY DAMAGES.","code":""},{"path":"https://syoung9836.github.io/knfi/LICENSE.html","id":"id_17-interpretation-of-sections-15-and-16","dir":"","previous_headings":"TERMS AND CONDITIONS","what":"17. Interpretation of Sections 15 and 16","title":"GNU General Public License","text":"disclaimer warranty limitation liability provided given local legal effect according terms, reviewing courts shall apply local law closely approximates absolute waiver civil liability connection Program, unless warranty assumption liability accompanies copy Program return fee. END TERMS CONDITIONS","code":""},{"path":"https://syoung9836.github.io/knfi/LICENSE.html","id":"how-to-apply-these-terms-to-your-new-programs","dir":"","previous_headings":"","what":"How to Apply These Terms to Your New Programs","title":"GNU General Public License","text":"develop new program, want greatest possible use public, best way achieve make free software everyone can redistribute change terms. , attach following notices program. safest attach start source file effectively state exclusion warranty; file least “copyright” line pointer full notice found. Also add information contact electronic paper mail. program terminal interaction, make output short notice like starts interactive mode: hypothetical commands show w show c show appropriate parts General Public License. course, program’s commands might different; GUI interface, use “box”. also get employer (work programmer) school, , sign “copyright disclaimer” program, necessary. information , apply follow GNU GPL, see . GNU General Public License permit incorporating program proprietary programs. program subroutine library, may consider useful permit linking proprietary applications library. want , use GNU Lesser General Public License instead License. first, please read .","code":" Copyright (C) This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program. If not, see . Copyright (C) This program comes with ABSOLUTELY NO WARRANTY; for details type 'show w'. This is free software, and you are welcome to redistribute it under certain conditions; type 'show c' for details."},{"path":"https://syoung9836.github.io/knfi/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Sinyoung Park. Author, maintainer. Wonhee Cho. Author, contributor. Inyoo Kim. Author, contributor. Wontaek Lim. Author, contributor. Dongwook W. Ko. Author, thesis advisor.","code":""},{"path":"https://syoung9836.github.io/knfi/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Park S (2022). Development Algorithm Analysis Korean National Forest Inventory Data : Focusing Biodiversity Biomass Gangwon-. Master's thesis, Kookmin University, 77, Jeongneung-ro, Seongbuk-gu, Seoul, Republic Korea.","code":"@MastersThesis{, title = {Development of an Algorithm for the Analysis of Korean National Forest Inventory Data : Focusing on Biodiversity and Biomass in Gangwon-do}, author = {Sinyoung Park}, school = {Kookmin University}, address = {77, Jeongneung-ro, Seongbuk-gu, Seoul, Republic of Korea}, year = {2022}, }"},{"path":[]},{"path":"https://syoung9836.github.io/knfi/index.html","id":"overview","dir":"","previous_headings":"","what":"Overview","title":"Analysis of Korean National Forest Inventory DB","text":"Understanding current status forest resources essential monitoring changes forest ecosystem producing related statistics. South Korea, National Forest Inventory (NFI) surveys 4,500 sample plots nationwide every five years records 70 items, including forest surveys, forest resource surveys, forest vegetation surveys. Many researchers using NFI primary data research estimating biomass analyzing importance value species time space suitable research purpose. However, accumulation various forest survey data across country limits use vast data. Therefore, study developed algorithm efficiently processes vast amounts NFI data time space using statistical analysis software R. developed algorithm first reconstructs NFI time space according researcher’s purpose performs integrity verification maintain data quality. Subsequently, summary statistics, biodiversity, importance value, biomass analyzed using verified data. Finally, visualizing analysis results allows spatio-temporal access forest ecosystem changes. Distribution National Forest Inventory sample plots (left) sampling design National Forest Inventory (right) (Korea Forest Research Institute, 2011) Plot design National Forest Inventory (Korea Forest Research Institute, 2011)","code":""},{"path":"https://syoung9836.github.io/knfi/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Analysis of Korean National Forest Inventory DB","text":"","code":"# The easiest way to get knfi is to install just knfi: install.packages(\"knfi\") # Or the development version from GitHub: remotes::install_github(\"SYOUNG9836/knfi\")"},{"path":"https://syoung9836.github.io/knfi/reference/biomass_nfi.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate Tree Biomass for National Forest Inventory Data — biomass_nfi","title":"Calculate Tree Biomass for National Forest Inventory Data — biomass_nfi","text":"biomass_nfi() function estimates volume, aboveground biomass, biomass, carbon storage carbon dioxide storage. can provide summaries individual plots, entire study area, specific groups within study area using parameters byplot, plotgrp treegrp. calculating biomass individual trees plots level, users flexibility specifying data inclusion criteria analysis levels using parameters clusterplot, largetreearea, stockedland, talltree. parameters determine whether treat cluster plots single plots, include large tree survey plots, focus Stocked land tall trees. Users can also choose criteria post-stratification using strat parameter.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/biomass_nfi.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate Tree Biomass for National Forest Inventory Data — biomass_nfi","text":"","code":"biomass_nfi( data, byplot = FALSE, plotgrp = NULL, treegrp = NULL, strat = \"FORTYP_SUB\", clusterplot = FALSE, largetreearea = TRUE, stockedland = TRUE, talltree = TRUE )"},{"path":"https://syoung9836.github.io/knfi/reference/biomass_nfi.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate Tree Biomass for National Forest Inventory Data — biomass_nfi","text":"data : list generated read_nfi contains 'plot' 'tree' data frames. byplot : logical flag (default FALSE); TRUE, calculates statistics plot separately. FALSE, calculates entire dataset groups specified plotgrp treegrp. plotgrp : character vector; variables 'plot' tables grouping. Use c() combine multiple variables. treegrp : character vector; variables 'tree' tables grouping. Use c() combine multiple variables. strat : character vector; variable used post-stratification. National Forest Inventory Korea, typically used forest type. clusterplot : logical flag (default FALSE); TRUE, treats cluster plot single unit. FALSE, calculates subplot separately. largetreearea : logical flag (default TRUE); TRUE, includes large tree survey plots analysis. FALSE, uses standard tree plots. stockedland : logical flag (default TRUE); TRUE, includes stocked land. FALSE, includes land types. talltree : logical flag (default TRUE); TRUE, includes tall trees. FALSE, includes trees shrubs.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/biomass_nfi.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate Tree Biomass for National Forest Inventory Data — biomass_nfi","text":"data.frame includes biomass estimates. structure depends input parameters: byplot = TRUE, row represents plot. byplot = FALSE, row represents entire dataset group specified plotgrp treegrp","code":""},{"path":"https://syoung9836.github.io/knfi/reference/biomass_nfi.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculate Tree Biomass for National Forest Inventory Data — biomass_nfi","text":"function calculates biomass using methodologies employed national statistics (mean, variance, standard error, relative standard error): Applies national carbon emission factors calculate biomass individual tree level. Estimates biomass per hectare cluster subplot level, options include basic survey trees basic large tree survey trees. Uses Double Sampling Post-stratification (DSS) method derive annual statistics. Applies Weighted Moving Average (WMA) method integrate annual statistics 20% plots surveyed year single time point.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/biomass_nfi.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Calculate Tree Biomass for National Forest Inventory Data — biomass_nfi","text":"Biomass calculation involves dividing data groups based plotgrp applying post-stratification group. result, data group sufficiently large, relative standard error (RSE) may high. important check RSE statistical measures biomass results.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/biomass_nfi.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Calculate Tree Biomass for National Forest Inventory Data — biomass_nfi","text":"Son, Y., Kim, R., Lee, K., Pyo, J., Kim, S., Hwang, J., Lee, S., & Park, H. (2014). Carbon emission factors biomass allometric equations species Korea. Korea Forest Research Institute. Yim, J., Moon, G., Lee, M., Kang, J., Won, M., Ahn, E., & Jeon, J. (2021). 2020 Forest inventory Korea. Korea Forest Research Institute.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/biomass_nfi.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate Tree Biomass for National Forest Inventory Data — biomass_nfi","text":"","code":"data(\"nfi_donghae\") # Basic usage biomass <- biomass_nfi(nfi_donghae) # \\donttest{ # Calculate biomass by administrative district district_biomass <- biomass_nfi(nfi_donghae, plotgrp = \"SGG\") # Calculate biomass for each plot plot_biomass <- biomass_nfi(nfi_donghae, byplot = TRUE) #> Warning: param 'byplot' has priority over param 'strat' # }"},{"path":"https://syoung9836.github.io/knfi/reference/col_name.html","id":null,"dir":"Reference","previous_headings":"","what":"The Korean and English names of the column names — col_name","title":"The Korean and English names of the column names — col_name","text":"Korean English names column names","code":""},{"path":"https://syoung9836.github.io/knfi/reference/col_name.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"The Korean and English names of the column names — col_name","text":"","code":"col_name"},{"path":"https://syoung9836.github.io/knfi/reference/col_name.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"The Korean and English names of the column names — col_name","text":"object class data.frame 174 rows 3 columns.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/cwd_biomass_nfi.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate biomass of Coarse Woody Debris — cwd_biomass_nfi","title":"Calculate biomass of Coarse Woody Debris — cwd_biomass_nfi","text":"cwd_biomass_nfi() function estimates volume, carbon storage carbon dioxide storage Coarse Woody Debris (CWD). can estimate individual plots, entire study area, specific groups within study area using parameters byplot, plotgrp treegrp. Users can choose criteria post-stratification using strat parameter. Users can specify whether focus Stocked land using stockedland parameter.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/cwd_biomass_nfi.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate biomass of Coarse Woody Debris — cwd_biomass_nfi","text":"","code":"cwd_biomass_nfi( data, byplot = FALSE, plotgrp = NULL, treegrp = NULL, strat = \"FORTYP_SUB\", stockedland = TRUE )"},{"path":"https://syoung9836.github.io/knfi/reference/cwd_biomass_nfi.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate biomass of Coarse Woody Debris — cwd_biomass_nfi","text":"data : list generated read_nfi contains 'plot' 'cwd' data frames. byplot : logical flag (default FALSE); TRUE, calculates statistics plot separately. FALSE, calculates entire dataset. plotgrp : character vector; variables 'plot' tables grouping. Use c() combine multiple variables. treegrp : character vector; variables 'tree' tables grouping. Use c() combine multiple variables. strat : character vector; variable used post-stratification. National Forest Inventory Korea, typically used forest type. stockedland : logical flag (default TRUE); TRUE, includes stocked land. FALSE, includes land types.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/cwd_biomass_nfi.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate biomass of Coarse Woody Debris — cwd_biomass_nfi","text":"data.frame includes CWD biomass plot study areas. structure depends input parameters: byplot = TRUE, row represents plot. byplot = FALSE, row represents entire dataset group specified plotgrp treegrp","code":""},{"path":"https://syoung9836.github.io/knfi/reference/cwd_biomass_nfi.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculate biomass of Coarse Woody Debris — cwd_biomass_nfi","text":"function calculates CWD biomass using methodologies employed national statistics (mean, variance, standard error, relative standard error): Applies national carbon emission factors calculate CWD biomass individual tree level. Estimates biomass per hectare plot level. Uses Double Sampling Post-stratification (DSS) method derive annual statistics. Applies Weighted Moving Average (WMA) method integrate annual statistics 20% plots surveyed year single time point.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/cwd_biomass_nfi.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Calculate biomass of Coarse Woody Debris — cwd_biomass_nfi","text":"Biomass calculation involves dividing data groups based plotgrp applying post-stratification group. result, data group sufficiently large, relative standard error (RSE) may high. important check RSE statistical measures biomass results.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/cwd_biomass_nfi.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Calculate biomass of Coarse Woody Debris — cwd_biomass_nfi","text":"Son, Y., Kim, R., Lee, K., Pyo, J., Kim, S., Hwang, J., Lee, S., & Park, H. (2014). Carbon emission factors biomass allometric equations species Korea. Korea Forest Research Institute. Yim, J., Moon, G., Lee, M., Kang, J., Won, M., Ahn, E., & Jeon, J. (2021). 2020 Forest inventory Korea. Korea Forest Research Institute.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/cwd_biomass_nfi.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate biomass of Coarse Woody Debris — cwd_biomass_nfi","text":"","code":"data(\"nfi_donghae\") # Basic usage cwd <- cwd_biomass_nfi(nfi_donghae) # \\donttest{ # Calculate CWD biomass grouped by administrative district and decay class cwd_grp <- cwd_biomass_nfi(nfi_donghae, plotgrp = \"SGG\", treegrp = \"DECAY\") # Calculate CWD biomass for each plot plot_biomass <- cwd_biomass_nfi(nfi_donghae, byplot = TRUE) #> Warning: param 'byplot' has priority over param 'strat' # }"},{"path":"https://syoung9836.github.io/knfi/reference/diversity_nfi.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate species diversity indices for National Forest Inventory Data — diversity_nfi","title":"Calculate species diversity indices for National Forest Inventory Data — diversity_nfi","text":"diversity_nfi() function calculates species richness, evenness Shannon Simpson diversity indices National Forest Inventory (NFI) data. can provide diversity measures individual plots, entire study area, specific groups within study area using parameters byplot plotgrp. function can calculate diversity species genus level different vegetation components (trees, herbs, vegetation, saplings). uses diversity function vegan package core calculations. Users flexibility specifying data inclusion criteria analysis levels using parameters clusterplot, largetreearea, stockedland, talltree. parameters determine whether treat cluster plots single plots, include large tree survey plots, focus Stocked land tall trees.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/diversity_nfi.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate species diversity indices for National Forest Inventory Data — diversity_nfi","text":"","code":"diversity_nfi( data, sp = \"SP\", table = \"tree\", basal = FALSE, plotgrp = NULL, byplot = FALSE, clusterplot = FALSE, largetreearea = FALSE, stockedland = TRUE, talltree = TRUE )"},{"path":"https://syoung9836.github.io/knfi/reference/diversity_nfi.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate species diversity indices for National Forest Inventory Data — diversity_nfi","text":"data : list generated read_nfi contains 'plot' one ('tree', 'herb', 'veg', 'sapling') data frames. sp : character vector; column name species information (e.g., \"SP\" species, \"GENUS\" genus-level analysis). table : character vector; Specifies vegetation table use diversity analysis. Must one 'tree', 'herb', 'veg', 'sapling'. basal : logical flag (default FALSE); TRUE, calculates tree diversity using basal area. FALSE, uses number individuals. applicable table = \"tree\". plotgrp : character vector; specifies variables 'plot' table use grouping. Use c() combine multiple variables. byplot : logical flag (default FALSE); TRUE, calculates statistics plot separately. FALSE, calculates entire dataset. clusterplot : logical flag (default FALSE); TRUE, treats cluster plot single unit. FALSE, calculates subplot separately. largetreearea : logical flag (default FALSE); TRUE, includes large tree survey plots analysis. FALSE, uses standard tree plots. stockedland : logical flag (default TRUE); TRUE, includes stocked land. FALSE, includes land types. talltree : logical flag (default TRUE); TRUE, includes tall trees. FALSE, includes trees shrubs.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/diversity_nfi.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate species diversity indices for National Forest Inventory Data — diversity_nfi","text":"data.frame includes diversity indices. structure depends input parameters: byplot = TRUE, row represents plot. byplot = FALSE, row represents entire dataset group specified plotgrp","code":""},{"path":"https://syoung9836.github.io/knfi/reference/diversity_nfi.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculate species diversity indices for National Forest Inventory Data — diversity_nfi","text":"function calculates following diversity indices (mean standard error): Species richness: total number species surveyed. Shannon-Wiener index: Calculated sum proportions individuals basal area species relative total. Gini-Simpson index: Calculated 1 minus Simpson's index. Ranges 0 1, higher values indicating greater diversity. Species evenness: Calculated dividing Shannon diversity natural logarithm species richness. Ranges 0 1, 1 indicating species evenly distributed.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/diversity_nfi.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Calculate species diversity indices for National Forest Inventory Data — diversity_nfi","text":"'herb', 'veg', 'sapling' tables may contain lot errors, use caution interpreting results tables.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/diversity_nfi.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Calculate species diversity indices for National Forest Inventory Data — diversity_nfi","text":"Shannon, C. E. (1948). mathematical theory communication. Bell System Technical Journal, 27(3), 379–423. Simpson, E. H. (1949). Measurement diversity. Nature, 163(4148), 688–688. Pielou, E. C. (1966). measurement diversity different types biological collections. Journal Theoretical Biology, 13, 131–144.","code":""},{"path":[]},{"path":"https://syoung9836.github.io/knfi/reference/diversity_nfi.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate species diversity indices for National Forest Inventory Data — diversity_nfi","text":"","code":"data(\"nfi_donghae\") # Calculate tree diversity indices using basal area tree_ba_diversity <- diversity_nfi(nfi_donghae, sp = \"SP\", table = \"tree\", basal = TRUE) # \\donttest{ # Calculate tree diversity indices using number of individuals tree_indi_diversity <- diversity_nfi(nfi_donghae, sp = \"SP\", table = \"tree\", basal = FALSE) # }"},{"path":"https://syoung9836.github.io/knfi/reference/filter_nfi.html","id":null,"dir":"Reference","previous_headings":"","what":"Filter National Forest Inventory Data — filter_nfi","title":"Filter National Forest Inventory Data — filter_nfi","text":"filter_nfi() function provides hierarchical non-hierarchical filtering approaches complex structure National Forest Inventory data based user-provided condition expressions (expr_texts). function enables effective filtering maintaining relationship plot data (parent data) data (child data).","code":""},{"path":"https://syoung9836.github.io/knfi/reference/filter_nfi.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Filter National Forest Inventory Data — filter_nfi","text":"","code":"filter_nfi(data, expr_texts, hier = TRUE)"},{"path":"https://syoung9836.github.io/knfi/reference/filter_nfi.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Filter National Forest Inventory Data — filter_nfi","text":"data : list generated read_nfi. dataframe 'SUB_PLOT' column. expr_texts : @param expr_texts : character vector; expressions specifying filtering conditions. expression combine dataframe name, dollar sign, condition, separate expressions data frame. (e.g., c(\"plot$OWN_CD == '5'\", \"tree$FAMILY == 'Pinaceae'\"). Conditions must valid R expressions. hier : logical flag (default TRUE); indicates whether apply hierarchical filtering (TRUE) non-hierarchical filtering (FALSE). Hierarchical filtering ensures connected dataframes filtered based results filters applied parent frame.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/filter_nfi.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Filter National Forest Inventory Data — filter_nfi","text":"list dataframes.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/filter_nfi.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Filter National Forest Inventory Data — filter_nfi","text":"function parses expressions targeting specific columns dataframes within provided list. Expression requirements: expression expr_texts must start valid dataframe name list (e.g., \"plot\", \"tree\", \"cwd\") combine dataframe name, dollar sign, condition (e.g. c(\"plot$OWN_CD == '5'\"). Separate expressions must provided dataframe filtered (e.g. c(\"plot$OWN_CD == '5'\", \"tree$FAMILY == 'Pinaceae' | tree$WDY_PLNTS_TYP_CD == '1'\"). Hierarchical filtering (hier = TRUE): Filters applied plot table affect connected child data (tree, CWD, stump, etc.). Filters applied child data operate within dataframe affect dataframes. Example: coniferous forest subplots selected plot table, child data retain tree, CWD, stump, etc., associated subplots. Non-hierarchical filtering (hier = FALSE): Filters applied parent dataframe (plot table) affect child data. Filtering results child data affect parent child data. Example: certain species selected tree table, plot table, CWD table, stump table, etc., filtered based remaining subplots selection.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/filter_nfi.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Filter National Forest Inventory Data — filter_nfi","text":"","code":"data(\"nfi_donghae\") # Applying hierarchical filtering to select only privately owned forest subplots. # Ensures all child tables' subplots match the filtered plot table's subplots. # Expected results after filtering: # all(nfi_donghae$tree$SUB_PLOT %in% nfi_donghae$plot$SUB_PLOT) result: TRUE nfi_donghae <- filter_nfi(nfi_donghae, c(\"plot$OWN_CD == '5'\"), hier = TRUE) # \\donttest{ # Non-hierarchical filtering to select only privately owned forest subplots. # Child tables remain unfiltered and may not correspond to the plot table subplots. # Expected results after filtering: # all(nfi_donghae$tree$SUB_PLOT %in% nfi_donghae$plot$SUB_PLOT) result: FALSE nfi_donghae <- filter_nfi(nfi_donghae, c(\"plot$OWN_CD == '5'\"), hier = FALSE) # Non-Hierarchical Filtering with only woody plants. # Other tables remain filtered and correspond to the tree table. # Expected results after filtering: # all(nfi_donghae$plot$SUB_PLOT %in% nfi_donghae$tree$SUB_PLOT) result: TRUE nfi_donghae <- filter_nfi(nfi_donghae, c(\"tree$WDY_PLNTS_TYP_CD == '1'\"), hier = FALSE) # Combining multiple filters across different dataframes nfi_donghae <- filter_nfi(nfi_donghae, c(\"plot$OWN_CD == '5'\", \"tree$FAMILY == 'Pinaceae' | tree$WDY_PLNTS_TYP_CD == '1'\")) # }"},{"path":"https://syoung9836.github.io/knfi/reference/iv_nfi.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates the importance values for National Forest Inventory Data — iv_nfi","title":"Calculates the importance values for National Forest Inventory Data — iv_nfi","text":"iv_nfi() function calculates importance values tree species based frequency, density coverage. can estimate entire study area specific groups within using plotgrp parameter. uses importancevalue function BiodiversityR package core calculations. Users flexibility specifying data inclusion criteria analysis levels using parameters frequency, clusterplot, largetreearea, stockedland, talltree. parameters determine whether include frequency importance calculations, treat cluster plots single plots, include large tree survey plots, focus Stocked land tall trees.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/iv_nfi.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates the importance values for National Forest Inventory Data — iv_nfi","text":"","code":"iv_nfi( data, sp = \"SP\", plotgrp = NULL, frequency = TRUE, clusterplot = FALSE, largetreearea = FALSE, stockedland = TRUE, talltree = TRUE )"},{"path":"https://syoung9836.github.io/knfi/reference/iv_nfi.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates the importance values for National Forest Inventory Data — iv_nfi","text":"data : list generated read_nfi contains 'plot' 'tree' data frames. sp :character vector; column name species information (e.g., \"SP\" species, \"GENUS\" genus-level analysis). plotgrp : character vector; specifies variables 'plot' table use grouping. Use c() combine multiple variables. frequency : logical flag (default TRUE); TRUE, includes frequency importance value calculations. clusterplot : logical flag (default FALSE); TRUE, treats cluster plot single unit. FALSE, calculates subplot separately. largetreearea : logical flag (default FALSE); TRUE, includes large tree survey plots analysis. FALSE, uses standard tree plots. stockedland : logical flag (default TRUE); TRUE, includes stocked land. FALSE, includes land types. talltree : logical flag (default TRUE); TRUE, includes tall trees. FALSE, includes trees shrubs.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/iv_nfi.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates the importance values for National Forest Inventory Data — iv_nfi","text":"data.frame includes importance value tree species. row represents combination tree species groups specified plotgrp treegrp.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/iv_nfi.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculates the importance values for National Forest Inventory Data — iv_nfi","text":"importance value (ranging 0 100) calculated mean : Relative frequency: (number plots species observed / total survey plots) * 100 Relative density: (total number individuals species / sum species' densities) * 100 Relative coverage: (total basal area species / sum species' basal area) * 100","code":""},{"path":"https://syoung9836.github.io/knfi/reference/iv_nfi.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Calculates the importance values for National Forest Inventory Data — iv_nfi","text":"Consider calculating importance genus rather species due potential incompleteness species classification. Since frequencies species may identical across nation, may desirable exclude frequency importance calculation.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/iv_nfi.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Calculates the importance values for National Forest Inventory Data — iv_nfi","text":"Curtis, J. T. & McIntosh, R. P. (1951). upland forest continuum prairie-forest border region Wisconsin. Ecology, 32(3), 476–496.","code":""},{"path":[]},{"path":"https://syoung9836.github.io/knfi/reference/iv_nfi.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates the importance values for National Forest Inventory Data — iv_nfi","text":"","code":"data(\"nfi_donghae\") # Calculate importance values without frequency importance <- iv_nfi(nfi_donghae, sp = \"SP\", frequency = FALSE) # \\donttest{ # Calculate importance values using genus genus_importance <- iv_nfi(nfi_donghae, sp = \"GENUS\") # }"},{"path":"https://syoung9836.github.io/knfi/reference/nfi_donghae.html","id":null,"dir":"Reference","previous_headings":"","what":"National Forest Inventory data for Donghae-si, Gangwon-do, Republic of Korea for testing the function — nfi_donghae","title":"National Forest Inventory data for Donghae-si, Gangwon-do, Republic of Korea for testing the function — nfi_donghae","text":"National Forest Inventory data Donghae-si, Gangwon-, Republic Korea testing function","code":""},{"path":"https://syoung9836.github.io/knfi/reference/nfi_donghae.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"National Forest Inventory data for Donghae-si, Gangwon-do, Republic of Korea for testing the function — nfi_donghae","text":"","code":"nfi_donghae"},{"path":"https://syoung9836.github.io/knfi/reference/nfi_donghae.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"National Forest Inventory data for Donghae-si, Gangwon-do, Republic of Korea for testing the function — nfi_donghae","text":"object class list length 3.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/read_nfi.html","id":null,"dir":"Reference","previous_headings":"","what":"Read Korean National Forest Inventory — read_nfi","title":"Read Korean National Forest Inventory — read_nfi","text":"read_nfi() function reads processes Korean National Forest Inventory (NFI). loads annual NFI files local computer, transforms data analysis-friendly format, performs data integrity verification. Users can specify districts tables load. NFI data can downloaded https://kfss.forest.go.kr/stat/.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/read_nfi.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read Korean National Forest Inventory — read_nfi","text":"","code":"read_nfi(dir, district = NULL, tables = c(\"tree\", \"cwd\"))"},{"path":"https://syoung9836.github.io/knfi/reference/read_nfi.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read Korean National Forest Inventory — read_nfi","text":"dir : character vector; directory containing NFI files. district : character vector; district names Korean (sido, sigungu, eupmyondong levels). NULL, entire dataset loaded. Combine multiple districts using c(). tables : character vector; tables import. Options: 'tree', 'cwd', 'stump', 'sapling', 'veg', 'herb', 'soil'. Combine multiple tables using c(). e.g., c('tree', 'cwd', 'stump', 'sapling', 'veg', 'herb', 'soil').","code":""},{"path":"https://syoung9836.github.io/knfi/reference/read_nfi.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read Korean National Forest Inventory — read_nfi","text":"data.frame; processed NFI data, structured easy analysis.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/read_nfi.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Read Korean National Forest Inventory — read_nfi","text":"function can load following tables: plot Base table containing subplot data including site, stand non-forest area, among details (automatically included). tree Tree survey table including species, DBH, height, among others. Data collected trees large trees survey plot subplot. cwd Coarse woody debris table including species, tree decay level, cause death, among details. Data collected center subplot cluster plot. stump Stumps table including species diameter 20 cm ground, among details. Data collected center subplot cluster. sapling Saplings table including species, diameter 20 cm ground, number individuals, among details. Data collected sapling survey plot subplot. veg Vegetation table (woody herbaceous plants). records species, number individuals, dominance, among others. Data collected three vegetation survey plots located within selected center subplot. selection includes 25% total number center subplots. herb Herbaceous table focused herbaceous list. Data collected sapling survey plot subplot. soil Soil table including thickness organic layer soil depth, among others. Data collected three soil survey plots located within selected center subplot. selection includes 25% total number center subplots. details, refer National Forest Inventory guidelines. function performs several data integrity validation. Corrects administrative region information subplots. (col: SIDO, SIDO_CD, SGG, SGG_CD, EMD, EMD_CD) Adds ecoregion catchment subplots. (col: ECOREGION, CATCHMENT) Verifies corrects coniferous/deciduous classification tree species. (col: CONDEC_CLASS, CONDEC_CLASS_CD, WDY_PLNTS_TYP, WDY_PLNTS_TYP_CD) Adds scientific names species. (col: SCIENTIFIC_NAME) Adds Korean English names plant families genera. (col: FAMILY, FAMILY_KOREAN, GENUS, GENUS_KOREAN) Adds whether plant native cultivated, identifies food, medicinal, fiber, ornamental resource. (col: NATIVE_CULTIVATED, FOOD, MEDICINAL, FIBER, ORNAMENTAL) Calculates basal area individual tree (col: BASAL_AREA) Calculates forest type, dominant species, dominant species percentage subplot cluster plot. (col: FORTYP_SUB, DOMIN_PERCNT_SUB, DOMIN_SP_SUB, FORTYP_CLST, DOMIN_PERCNT_CLST, DOMIN_SP_CLST) Species classification taxonomy follow standards set Korean Plant Names Index Committee Korea National Arboretum http://www.nature.go.kr/kpni/index..","code":""},{"path":"https://syoung9836.github.io/knfi/reference/read_nfi.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Read Korean National Forest Inventory — read_nfi","text":"manually download subsets annual NFI file, visit Korea Forest Service Forestry Statistics Platform (https://kfss.forest.go.kr/stat/), download .zip files, extract . Use data(\"col_name\") view Korean English names column names. National Forest Inventory undergoes rigorous quality control, including internal reviews field inspections, errors may still exist due extensive nature survey (approximately 4,000 plots 70 items 7th phase). Please use data cautiously report anomalies help improve algorithms. want save results computer, can save Excel format. example, can use following code:writexl::write_xlsx(data, \"data.xlsx\") want read saved data back, use code : path <-\"../nfi_donghae.xlsx\" sheet_names <- readxl::excel_sheets(path) (sheet_name sheet_names) {nfi[[sheet_name]] <- readxl::read_excel(path, sheet = sheet_name) }","code":""},{"path":"https://syoung9836.github.io/knfi/reference/read_nfi.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read Korean National Forest Inventory — read_nfi","text":"","code":"if (FALSE) { # \\dontrun{ # Load tree and CWD data for all districts nfi5_data <- read_nfi(\"D:/NFI/NFI5\", district = NULL, tables = c(\"tree\", \"cwd\")) } # }"},{"path":"https://syoung9836.github.io/knfi/reference/summary_nfi.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate descriptive statistics for National Forest Inventory Data — summary_nfi","title":"Calculate descriptive statistics for National Forest Inventory Data — summary_nfi","text":"summary_nfi() function calculates comprehensive descriptive statistics National Forest Inventory (NFI) data. can provide summaries individual plots, entire study area, specific groups within study area using parameters byplot plotgrp. Users flexibility specifying data inclusion criteria analysis levels using parameters clusterplot, largetreearea, stockedland, talltree. parameters determine whether treat cluster plots single plots, include large tree survey plots, focus Stocked land tall trees.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/summary_nfi.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate descriptive statistics for National Forest Inventory Data — summary_nfi","text":"","code":"summary_nfi( data, plotgrp = NULL, byplot = FALSE, clusterplot = FALSE, largetreearea = TRUE, stockedland = TRUE, talltree = TRUE )"},{"path":"https://syoung9836.github.io/knfi/reference/summary_nfi.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate descriptive statistics for National Forest Inventory Data — summary_nfi","text":"data : list containing 'plot' 'tree' data frames, typically generated read_nfi. plotgrp : character vector; specifies variables 'plot' table use grouping. Use c() combine multiple variables. byplot : logical flag (default FALSE); TRUE, calculates statistics plot separately. FALSE, calculates entire dataset. clusterplot : logical flag (default FALSE); TRUE, treats cluster plot single unit. FALSE, calculates subplot separately. largetreearea : logical flag (default TRUE); TRUE, includes large tree survey plots analysis. FALSE, uses standard tree plots. stockedland : logical flag (default TRUE); TRUE, includes stocked land. FALSE, includes land types. talltree : logical flag (default TRUE); TRUE, includes tall trees. FALSE, includes trees shrubs.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/summary_nfi.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate descriptive statistics for National Forest Inventory Data — summary_nfi","text":"data.frame includes summary statistics. structure depends input parameters: byplot = TRUE, row represents plot. byplot = FALSE, row represents entire dataset group specified plotgrp","code":""},{"path":"https://syoung9836.github.io/knfi/reference/summary_nfi.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculate descriptive statistics for National Forest Inventory Data — summary_nfi","text":"function calculates following statistics: Plot-related statistics: Number cluster plots Number subplots Number subplots large trees (\\(\\geq\\) 30cm) observed Tree-related statistics: Number individual trees Number large trees Number dominant trees Number tree species Tree measurements stand statistics (mean standard deviation): DBH (Diameter Breast Height) Tree height Height dominant trees Number trees per hectare Basal area per hectare Volume per hectare largetreearea parameter affects calculations differently: per-hectare statistics (trees per hectare, basal area per hectare, volume per hectare), setting largetreearea = TRUE includes data large tree survey plots. statistics, trees large tree survey plots always excluded, regardless largetreearea setting.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/summary_nfi.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate descriptive statistics for National Forest Inventory Data — summary_nfi","text":"","code":"data(\"nfi_donghae\") # Basic usage summary_stats <- summary_nfi(nfi_donghae) # \\donttest{ # Summarize by the group, including all land types grouped_stats <- summary_nfi(nfi_donghae, plotgrp = \"OWN_CD\", stockedland = FALSE) # Summarize by individual plots, including both trees and shrubs plot_summaries <- summary_nfi(nfi_donghae, byplot = TRUE, talltree = FALSE) # }"},{"path":"https://syoung9836.github.io/knfi/reference/switchcol_nfi.html","id":null,"dir":"Reference","previous_headings":"","what":"Switch column names — switchcol_nfi","title":"Switch column names — switchcol_nfi","text":"switchcol_nfi() function allows switching original Korean column names English column names. input data English column names, changes original Korean names, vice versa.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/switchcol_nfi.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Switch column names — switchcol_nfi","text":"","code":"switchcol_nfi(data)"},{"path":"https://syoung9836.github.io/knfi/reference/switchcol_nfi.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Switch column names — switchcol_nfi","text":"data : list generated read_nfi.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/switchcol_nfi.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Switch column names — switchcol_nfi","text":"list dataframes switched column names.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/switchcol_nfi.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Switch column names — switchcol_nfi","text":"Important: Data original Korean column names used read_nfi functions except colchange_nfi() . option revert original Korean names provided solely users wish store process NFI data original column names.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/switchcol_nfi.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Switch column names — switchcol_nfi","text":"","code":"data(\"nfi_donghae\") #Switch column names from English to original Korean names nfi_donghae_kor <- switchcol_nfi(nfi_donghae) # \\donttest{ # Switch column names from original Korean to English names nfi_donghae_eng <- switchcol_nfi(nfi_donghae_kor) # }"},{"path":"https://syoung9836.github.io/knfi/reference/tsvis_nfi.html","id":null,"dir":"Reference","previous_headings":"","what":"Visualize time series data for National Forest Inventory Data — tsvis_nfi","title":"Visualize time series data for National Forest Inventory Data — tsvis_nfi","text":"tsvis_nfi() function analyzes visualizes data time series format. can visualize 'biomass', 'cwd', 'iv' data 'table', 'line', 'bar', 'map'. Users need select specific biomass variable, volume carbon visualize biomass. map visualization biomass, users must choose administrative unit level. uses iv_nfi biomass_nfi cwd_biomass_nfi function core calculations.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/tsvis_nfi.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Visualize time series data for National Forest Inventory Data — tsvis_nfi","text":"","code":"tsvis_nfi( data, y = \"biomass\", bm_type = NULL, output = \"line\", plotgrp = NULL, isannual = TRUE, admin = NULL, strat = \"FORTYP_SUB\", clusterplot = FALSE, largetreearea = TRUE, stockedland = TRUE, talltree = TRUE, sp = \"SP\", frequency = TRUE )"},{"path":"https://syoung9836.github.io/knfi/reference/tsvis_nfi.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Visualize time series data for National Forest Inventory Data — tsvis_nfi","text":"data : list generated read_nfi contains 'plot' 'tree' data frames. y : character vector; variable visualize. Must one 'biomass', 'cwd', 'iv'. bm_type : character vector; specific variable visualize 'biomass' 'cwd'. Must one 'volume', 'biomass', 'AG_biomass', 'carbon', 'co2'. output : character vector; desired type visualization. Must one 'table', 'line', 'bar', 'map'. plotgrp : character vector; specifies variables 'plot' table use grouping. Use c() combine multiple variables, output map, line bar plot, one variable can used. isannual : logical flag (default TRUE); TRUE, result provided annually, FALSE, provided 5-year intervals. admin : character vector; administrative unit visualizing 'biomass' 'cwd' map. Must one 'sido', 'sgg', 'emg'. strat : character vector; variable used post-stratification. National Forest Inventory Korea, typically used forest type. clusterplot : logical flag (default FALSE); TRUE, treats cluster plot single unit. FALSE, calculates subplot separately. largetreearea : logical flag (default FALSE); TRUE, includes large tree survey plots analysis. FALSE, uses standard tree plots. stockedland : logical flag (default TRUE); TRUE, includes stocked land. FALSE, includes land types. talltree : logical flag (default TRUE); TRUE, includes tall trees. FALSE, includes trees shrubs. sp : character vector; column name species information (e.g., \"SP\" species, \"GENUS\" genus-level analysis). frequency : logical flag (default TRUE); TRUE, includes frequency importance value calculations.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/tsvis_nfi.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Visualize time series data for National Forest Inventory Data — tsvis_nfi","text":"output map, line, bar plot: object class ggplot. output table: data.frame.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/tsvis_nfi.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Visualize time series data for National Forest Inventory Data — tsvis_nfi","text":"visualize data map, need agree install kadmin package function execution install advance. kadmin package loads shapefiles Korea's Si, Si, Gun, Gu Eup, Myeon, Dong. Use drat::addRepo(\"SYOUNG9836\") install.packages(\"kadmin\") remotes::install_github(\"SYOUNG9836/kadmin\")","code":""},{"path":[]},{"path":"https://syoung9836.github.io/knfi/reference/tsvis_nfi.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Visualize time series data for National Forest Inventory Data — tsvis_nfi","text":"","code":"data(\"nfi_donghae\") # \\donttest{ # Visualize importance values as a table tsvis_iv <- tsvis_nfi(nfi_donghae, y = \"iv\", output = \"table\") # 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, grouped by age class tsvis_bm_line <- tsvis_nfi(nfi_donghae, y = \"biomass\", bm_type = \"carbon\", output = \"line\", plotgrp = \"AGE_CLS\") # } if (FALSE) { # \\dontrun{ # 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\") } # }"},{"path":"https://syoung9836.github.io/knfi/news/index.html","id":"knfi-100","dir":"Changelog","previous_headings":"","what":"knfi 1.0.0","title":"knfi 1.0.0","text":"Initial CRAN submission.","code":""}] +[{"path":"https://syoung9836.github.io/knfi/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Sinyoung Park. Author, maintainer. Wonhee Cho. Author, contributor. Inyoo Kim. Author, contributor. Wontaek Lim. Author, contributor. Dongwook W. Ko. Author, thesis advisor.","code":""},{"path":"https://syoung9836.github.io/knfi/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Park S (2022). Development Algorithm Analysis Korean National Forest Inventory Data : Focusing Biodiversity Biomass Gangwon-. Master's thesis, Kookmin University, 77, Jeongneung-ro, Seongbuk-gu, Seoul, Republic Korea.","code":"@MastersThesis{, title = {Development of an Algorithm for the Analysis of Korean National Forest Inventory Data : Focusing on Biodiversity and Biomass in Gangwon-do}, author = {Sinyoung Park}, school = {Kookmin University}, address = {77, Jeongneung-ro, Seongbuk-gu, Seoul, Republic of Korea}, year = {2022}, }"},{"path":[]},{"path":"https://syoung9836.github.io/knfi/index.html","id":"overview","dir":"","previous_headings":"","what":"Overview","title":"Analysis of Korean National Forest Inventory database","text":"Understanding current status forest resources essential monitoring changes forest ecosystem producing related statistics. South Korea, National Forest Inventory (NFI) surveys 4,500 sample plots nationwide every five years records 70 items, including forest surveys, forest resource surveys, forest vegetation surveys. Many researchers using NFI primary data research estimating biomass analyzing importance value species time space suitable research purpose. However, accumulation various forest survey data across country limits use vast data. Therefore, study developed algorithm efficiently processes vast amounts NFI data time space using statistical analysis software R. developed algorithm first reconstructs NFI time space according researcher’s purpose performs integrity verification maintain data quality. Subsequently, summary statistics, biodiversity, importance value, biomass analyzed using verified data. Finally, visualizing analysis results allows spatio-temporal access forest ecosystem changes. algorithmic approach significantly enhances efficiency processing analyzing NFI data. ’s important note raw NFI data included developed R package. Researchers interested accessing original NFI datasets visit Korea Forest Service Forestry Statistics Platform https://kfss.forest.go.kr/stat/ptl/article/articleList.?curMenu=11694&bbsId=microdataboard manually download annual NFI file subsets .zip files. package designed process analyze downloaded datasets. Distribution National Forest Inventory sample plots (left) sampling design National Forest Inventory (right) (Korea Forest Research Institute, 2011) Plot design National Forest Inventory (Korea Forest Research Institute, 2011)","code":""},{"path":"https://syoung9836.github.io/knfi/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Analysis of Korean National Forest Inventory database","text":"","code":"# The easiest way to get knfi is to install just knfi: install.packages(\"knfi\") # Or the development version from GitHub: remotes::install_github(\"SYOUNG9836/knfi\")"},{"path":"https://syoung9836.github.io/knfi/reference/biomass_nfi.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate Tree Biomass for National Forest Inventory Data — biomass_nfi","title":"Calculate Tree Biomass for National Forest Inventory Data — biomass_nfi","text":"biomass_nfi() function estimates volume, aboveground biomass, biomass, carbon storage carbon dioxide storage. can provide summaries individual plots, entire study area, specific groups within study area using parameters byplot, plotgrp treegrp. calculating biomass individual trees plots level, users flexibility specifying data inclusion criteria analysis levels using parameters clusterplot, largetreearea, stockedland, talltree. parameters determine whether treat cluster plots single plots, include large tree survey plots, focus Stocked land tall trees. Users can also choose criteria post-stratification using strat parameter.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/biomass_nfi.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate Tree Biomass for National Forest Inventory Data — biomass_nfi","text":"","code":"biomass_nfi( data, byplot = FALSE, plotgrp = NULL, treegrp = NULL, strat = \"FORTYP_SUB\", clusterplot = FALSE, largetreearea = TRUE, stockedland = TRUE, talltree = TRUE )"},{"path":"https://syoung9836.github.io/knfi/reference/biomass_nfi.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate Tree Biomass for National Forest Inventory Data — biomass_nfi","text":"data : list generated read_nfi contains 'plot' 'tree' data frames. byplot : logical flag (default FALSE); TRUE, calculates statistics plot separately. FALSE, calculates entire dataset groups specified plotgrp treegrp. plotgrp : character vector; variables 'plot' tables grouping. Use c() combine multiple variables. treegrp : character vector; variables 'tree' tables grouping. Use c() combine multiple variables. strat : character vector; variable used post-stratification. National Forest Inventory Korea, typically used forest type. clusterplot : logical flag (default FALSE); TRUE, treats cluster plot single unit. FALSE, calculates subplot separately. largetreearea : logical flag (default TRUE); TRUE, includes large tree survey plots analysis. FALSE, uses standard tree plots. stockedland : logical flag (default TRUE); TRUE, includes stocked land. FALSE, includes land types. talltree : logical flag (default TRUE); TRUE, includes tall trees. FALSE, includes trees shrubs.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/biomass_nfi.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate Tree Biomass for National Forest Inventory Data — biomass_nfi","text":"data.frame includes biomass estimates. structure depends input parameters: byplot = TRUE, row represents plot. byplot = FALSE, row represents entire dataset group specified plotgrp treegrp","code":""},{"path":"https://syoung9836.github.io/knfi/reference/biomass_nfi.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculate Tree Biomass for National Forest Inventory Data — biomass_nfi","text":"function calculates biomass using methodologies employed national statistics (mean, variance, standard error, relative standard error): Applies national carbon emission factors calculate biomass individual tree level. Estimates biomass per hectare cluster subplot level, options include basic survey trees basic large tree survey trees. Uses Double Sampling Post-stratification (DSS) method derive annual statistics. Applies Weighted Moving Average (WMA) method integrate annual statistics 20% plots surveyed year single time point.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/biomass_nfi.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Calculate Tree Biomass for National Forest Inventory Data — biomass_nfi","text":"Biomass calculation involves dividing data groups based plotgrp applying post-stratification group. result, data group sufficiently large, relative standard error (RSE) may high. important check RSE statistical measures biomass results.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/biomass_nfi.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Calculate Tree Biomass for National Forest Inventory Data — biomass_nfi","text":"Son, Y., Kim, R., Lee, K., Pyo, J., Kim, S., Hwang, J., Lee, S., & Park, H. (2014). Carbon emission factors biomass allometric equations species Korea. Korea Forest Research Institute. Yim, J., Moon, G., Lee, M., Kang, J., Won, M., Ahn, E., & Jeon, J. (2021). 2020 Forest inventory Korea. Korea Forest Research Institute.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/biomass_nfi.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate Tree Biomass for National Forest Inventory Data — biomass_nfi","text":"","code":"data(\"nfi_donghae\") # Basic usage biomass <- biomass_nfi(nfi_donghae) # Calculate biomass by administrative district district_biomass <- biomass_nfi(nfi_donghae, plotgrp = \"SGG\") # Calculate biomass for each plot plot_biomass <- biomass_nfi(nfi_donghae, byplot = TRUE) #> Warning: param 'byplot' has priority over param 'strat'"},{"path":"https://syoung9836.github.io/knfi/reference/col_name.html","id":null,"dir":"Reference","previous_headings":"","what":"The Korean and English names of the column names — col_name","title":"The Korean and English names of the column names — col_name","text":"Korean English names column names","code":""},{"path":"https://syoung9836.github.io/knfi/reference/col_name.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"The Korean and English names of the column names — col_name","text":"","code":"col_name"},{"path":"https://syoung9836.github.io/knfi/reference/col_name.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"The Korean and English names of the column names — col_name","text":"object class data.frame 174 rows 3 columns.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/cwd_biomass_nfi.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate biomass of Coarse Woody Debris — cwd_biomass_nfi","title":"Calculate biomass of Coarse Woody Debris — cwd_biomass_nfi","text":"cwd_biomass_nfi() function estimates volume, carbon storage carbon dioxide storage Coarse Woody Debris (CWD). can estimate individual plots, entire study area, specific groups within study area using parameters byplot, plotgrp treegrp. Users can choose criteria post-stratification using strat parameter. Users can specify whether focus Stocked land using stockedland parameter.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/cwd_biomass_nfi.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate biomass of Coarse Woody Debris — cwd_biomass_nfi","text":"","code":"cwd_biomass_nfi( data, byplot = FALSE, plotgrp = NULL, treegrp = NULL, strat = \"FORTYP_SUB\", stockedland = TRUE )"},{"path":"https://syoung9836.github.io/knfi/reference/cwd_biomass_nfi.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate biomass of Coarse Woody Debris — cwd_biomass_nfi","text":"data : list generated read_nfi contains 'plot' 'cwd' data frames. byplot : logical flag (default FALSE); TRUE, calculates statistics plot separately. FALSE, calculates entire dataset. plotgrp : character vector; variables 'plot' tables grouping. Use c() combine multiple variables. treegrp : character vector; variables 'tree' tables grouping. Use c() combine multiple variables. strat : character vector; variable used post-stratification. National Forest Inventory Korea, typically used forest type. stockedland : logical flag (default TRUE); TRUE, includes stocked land. FALSE, includes land types.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/cwd_biomass_nfi.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate biomass of Coarse Woody Debris — cwd_biomass_nfi","text":"data.frame includes CWD biomass plot study areas. structure depends input parameters: byplot = TRUE, row represents plot. byplot = FALSE, row represents entire dataset group specified plotgrp treegrp","code":""},{"path":"https://syoung9836.github.io/knfi/reference/cwd_biomass_nfi.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculate biomass of Coarse Woody Debris — cwd_biomass_nfi","text":"function calculates CWD biomass using methodologies employed national statistics (mean, variance, standard error, relative standard error): Applies national carbon emission factors calculate CWD biomass individual tree level. Estimates biomass per hectare plot level. Uses Double Sampling Post-stratification (DSS) method derive annual statistics. Applies Weighted Moving Average (WMA) method integrate annual statistics 20% plots surveyed year single time point.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/cwd_biomass_nfi.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Calculate biomass of Coarse Woody Debris — cwd_biomass_nfi","text":"Biomass calculation involves dividing data groups based plotgrp applying post-stratification group. result, data group sufficiently large, relative standard error (RSE) may high. important check RSE statistical measures biomass results.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/cwd_biomass_nfi.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Calculate biomass of Coarse Woody Debris — cwd_biomass_nfi","text":"Son, Y., Kim, R., Lee, K., Pyo, J., Kim, S., Hwang, J., Lee, S., & Park, H. (2014). Carbon emission factors biomass allometric equations species Korea. Korea Forest Research Institute. Yim, J., Moon, G., Lee, M., Kang, J., Won, M., Ahn, E., & Jeon, J. (2021). 2020 Forest inventory Korea. Korea Forest Research Institute.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/cwd_biomass_nfi.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate biomass of Coarse Woody Debris — cwd_biomass_nfi","text":"","code":"data(\"nfi_donghae\") # Basic usage cwd <- cwd_biomass_nfi(nfi_donghae) # Calculate CWD biomass grouped by administrative district and decay class cwd_grp <- cwd_biomass_nfi(nfi_donghae, plotgrp = \"SGG\", treegrp = \"DECAY\") # Calculate CWD biomass for each plot plot_biomass <- cwd_biomass_nfi(nfi_donghae, byplot = TRUE) #> Warning: param 'byplot' has priority over param 'strat'"},{"path":"https://syoung9836.github.io/knfi/reference/diversity_nfi.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate species diversity indices for National Forest Inventory Data — diversity_nfi","title":"Calculate species diversity indices for National Forest Inventory Data — diversity_nfi","text":"diversity_nfi() function calculates species richness, evenness Shannon Simpson diversity indices National Forest Inventory (NFI) data. can provide diversity measures individual plots, entire study area, specific groups within study area using parameters byplot plotgrp. function can calculate diversity species genus level different vegetation components (trees, herbs, vegetation, saplings). uses diversity function vegan package core calculations. Users flexibility specifying data inclusion criteria analysis levels using parameters clusterplot, largetreearea, stockedland, talltree. parameters determine whether treat cluster plots single plots, include large tree survey plots, focus Stocked land tall trees.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/diversity_nfi.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate species diversity indices for National Forest Inventory Data — diversity_nfi","text":"","code":"diversity_nfi( data, sp = \"SP\", table = \"tree\", basal = FALSE, plotgrp = NULL, byplot = FALSE, clusterplot = FALSE, largetreearea = FALSE, stockedland = TRUE, talltree = TRUE )"},{"path":"https://syoung9836.github.io/knfi/reference/diversity_nfi.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate species diversity indices for National Forest Inventory Data — diversity_nfi","text":"data : list generated read_nfi contains 'plot' one ('tree', 'herb', 'veg', 'sapling') data frames. sp : character vector; column name species information (e.g., \"SP\" species, \"GENUS\" genus-level analysis). table : character vector; Specifies vegetation table use diversity analysis. Must one 'tree', 'herb', 'veg', 'sapling'. basal : logical flag (default FALSE); TRUE, calculates tree diversity using basal area. FALSE, uses number individuals. applicable table = \"tree\". plotgrp : character vector; specifies variables 'plot' table use grouping. Use c() combine multiple variables. byplot : logical flag (default FALSE); TRUE, calculates statistics plot separately. FALSE, calculates entire dataset. clusterplot : logical flag (default FALSE); TRUE, treats cluster plot single unit. FALSE, calculates subplot separately. largetreearea : logical flag (default FALSE); TRUE, includes large tree survey plots analysis. FALSE, uses standard tree plots. stockedland : logical flag (default TRUE); TRUE, includes stocked land. FALSE, includes land types. talltree : logical flag (default TRUE); TRUE, includes tall trees. FALSE, includes trees shrubs.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/diversity_nfi.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate species diversity indices for National Forest Inventory Data — diversity_nfi","text":"data.frame includes diversity indices. structure depends input parameters: byplot = TRUE, row represents plot. byplot = FALSE, row represents entire dataset group specified plotgrp","code":""},{"path":"https://syoung9836.github.io/knfi/reference/diversity_nfi.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculate species diversity indices for National Forest Inventory Data — diversity_nfi","text":"function calculates following diversity indices (mean standard error): Species richness: total number species surveyed. Shannon-Wiener index: Calculated sum proportions individuals basal area species relative total. Gini-Simpson index: Calculated 1 minus Simpson's index. Ranges 0 1, higher values indicating greater diversity. Species evenness: Calculated dividing Shannon diversity natural logarithm species richness. Ranges 0 1, 1 indicating species evenly distributed.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/diversity_nfi.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Calculate species diversity indices for National Forest Inventory Data — diversity_nfi","text":"'herb', 'veg', 'sapling' tables may contain lot errors, use caution interpreting results tables.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/diversity_nfi.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Calculate species diversity indices for National Forest Inventory Data — diversity_nfi","text":"Shannon, C. E. (1948). mathematical theory communication. Bell System Technical Journal, 27(3), 379–423. Simpson, E. H. (1949). Measurement diversity. Nature, 163(4148), 688–688. Pielou, E. C. (1966). measurement diversity different types biological collections. Journal Theoretical Biology, 13, 131–144.","code":""},{"path":[]},{"path":"https://syoung9836.github.io/knfi/reference/diversity_nfi.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate species diversity indices for National Forest Inventory Data — diversity_nfi","text":"","code":"data(\"nfi_donghae\") # Calculate tree diversity indices using basal area tree_ba_diversity <- diversity_nfi(nfi_donghae, sp = \"SP\", table = \"tree\", basal = TRUE) # Calculate tree diversity indices using number of individuals tree_indi_diversity <- diversity_nfi(nfi_donghae, sp = \"SP\", table = \"tree\", basal = FALSE)"},{"path":"https://syoung9836.github.io/knfi/reference/filter_nfi.html","id":null,"dir":"Reference","previous_headings":"","what":"Filter National Forest Inventory Data — filter_nfi","title":"Filter National Forest Inventory Data — filter_nfi","text":"filter_nfi() function provides hierarchical non-hierarchical filtering approaches complex structure National Forest Inventory data based user-provided condition expressions (expr_texts). function enables effective filtering maintaining relationship plot data (parent data) data (child data).","code":""},{"path":"https://syoung9836.github.io/knfi/reference/filter_nfi.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Filter National Forest Inventory Data — filter_nfi","text":"","code":"filter_nfi(data, expr_texts, hier = TRUE)"},{"path":"https://syoung9836.github.io/knfi/reference/filter_nfi.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Filter National Forest Inventory Data — filter_nfi","text":"data : list generated read_nfi. dataframe 'SUB_PLOT' column. expr_texts : @param expr_texts : character vector; expressions specifying filtering conditions. expression combine dataframe name, dollar sign, condition, separate expressions data frame. (e.g., c(\"plot$OWN_CD == '5'\", \"tree$FAMILY == 'Pinaceae'\"). Conditions must valid R expressions. hier : logical flag (default TRUE); indicates whether apply hierarchical filtering (TRUE) non-hierarchical filtering (FALSE). Hierarchical filtering ensures connected dataframes filtered based results filters applied parent frame.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/filter_nfi.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Filter National Forest Inventory Data — filter_nfi","text":"list dataframes.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/filter_nfi.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Filter National Forest Inventory Data — filter_nfi","text":"function parses expressions targeting specific columns dataframes within provided list. Expression requirements: expression expr_texts must start valid dataframe name list (e.g., \"plot\", \"tree\", \"cwd\") combine dataframe name, dollar sign, condition (e.g. c(\"plot$OWN_CD == '5'\"). Separate expressions must provided dataframe filtered (e.g. c(\"plot$OWN_CD == '5'\", \"tree$FAMILY == 'Pinaceae' | tree$WDY_PLNTS_TYP_CD == '1'\"). Hierarchical filtering (hier = TRUE): Filters applied plot table affect connected child data (tree, CWD, stump, etc.). Filters applied child data operate within dataframe affect dataframes. Example: coniferous forest subplots selected plot table, child data retain tree, CWD, stump, etc., associated subplots. Non-hierarchical filtering (hier = FALSE): Filters applied parent dataframe (plot table) affect child data. Filtering results child data affect parent child data. Example: certain species selected tree table, plot table, CWD table, stump table, etc., filtered based remaining subplots selection.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/filter_nfi.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Filter National Forest Inventory Data — filter_nfi","text":"","code":"data(\"nfi_donghae\") # Applying hierarchical filtering to select only privately owned forest subplots. # Ensures all child tables' subplots match the filtered plot table's subplots. # Expected results after filtering: # all(nfi_donghae$tree$SUB_PLOT %in% nfi_donghae$plot$SUB_PLOT) result: TRUE nfi_donghae <- filter_nfi(nfi_donghae, c(\"plot$OWN_CD == '5'\"), hier = TRUE) # \\donttest{ # Non-hierarchical filtering to select only privately owned forest subplots. # Child tables remain unfiltered and may not correspond to the plot table subplots. # Expected results after filtering: # all(nfi_donghae$tree$SUB_PLOT %in% nfi_donghae$plot$SUB_PLOT) result: FALSE nfi_donghae <- filter_nfi(nfi_donghae, c(\"plot$OWN_CD == '5'\"), hier = FALSE) # Non-Hierarchical Filtering with only woody plants. # Other tables remain filtered and correspond to the tree table. # Expected results after filtering: # all(nfi_donghae$plot$SUB_PLOT %in% nfi_donghae$tree$SUB_PLOT) result: TRUE nfi_donghae <- filter_nfi(nfi_donghae, c(\"tree$WDY_PLNTS_TYP_CD == '1'\"), hier = FALSE) # Combining multiple filters across different dataframes nfi_donghae <- filter_nfi(nfi_donghae, c(\"plot$OWN_CD == '5'\", \"tree$FAMILY == 'Pinaceae' | tree$WDY_PLNTS_TYP_CD == '1'\")) # }"},{"path":"https://syoung9836.github.io/knfi/reference/iv_nfi.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates the importance values for National Forest Inventory Data — iv_nfi","title":"Calculates the importance values for National Forest Inventory Data — iv_nfi","text":"iv_nfi() function calculates importance values tree species based frequency, density coverage. can estimate entire study area specific groups within using plotgrp parameter. uses importancevalue function BiodiversityR package core calculations. Users flexibility specifying data inclusion criteria analysis levels using parameters frequency, clusterplot, largetreearea, stockedland, talltree. parameters determine whether include frequency importance calculations, treat cluster plots single plots, include large tree survey plots, focus Stocked land tall trees.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/iv_nfi.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates the importance values for National Forest Inventory Data — iv_nfi","text":"","code":"iv_nfi( data, sp = \"SP\", plotgrp = NULL, frequency = TRUE, clusterplot = FALSE, largetreearea = FALSE, stockedland = TRUE, talltree = TRUE )"},{"path":"https://syoung9836.github.io/knfi/reference/iv_nfi.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates the importance values for National Forest Inventory Data — iv_nfi","text":"data : list generated read_nfi contains 'plot' 'tree' data frames. sp :character vector; column name species information (e.g., \"SP\" species, \"GENUS\" genus-level analysis). plotgrp : character vector; specifies variables 'plot' table use grouping. Use c() combine multiple variables. frequency : logical flag (default TRUE); TRUE, includes frequency importance value calculations. clusterplot : logical flag (default FALSE); TRUE, treats cluster plot single unit. FALSE, calculates subplot separately. largetreearea : logical flag (default FALSE); TRUE, includes large tree survey plots analysis. FALSE, uses standard tree plots. stockedland : logical flag (default TRUE); TRUE, includes stocked land. FALSE, includes land types. talltree : logical flag (default TRUE); TRUE, includes tall trees. FALSE, includes trees shrubs.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/iv_nfi.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates the importance values for National Forest Inventory Data — iv_nfi","text":"data.frame includes importance value tree species. row represents combination tree species groups specified plotgrp treegrp.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/iv_nfi.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculates the importance values for National Forest Inventory Data — iv_nfi","text":"importance value (ranging 0 100) calculated mean : Relative frequency: (number plots species observed / total survey plots) * 100 Relative density: (total number individuals species / sum species' densities) * 100 Relative coverage: (total basal area species / sum species' basal area) * 100","code":""},{"path":"https://syoung9836.github.io/knfi/reference/iv_nfi.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Calculates the importance values for National Forest Inventory Data — iv_nfi","text":"Consider calculating importance genus rather species due potential incompleteness species classification. Since frequencies species may identical across nation, may desirable exclude frequency importance calculation.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/iv_nfi.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Calculates the importance values for National Forest Inventory Data — iv_nfi","text":"Curtis, J. T. & McIntosh, R. P. (1951). upland forest continuum prairie-forest border region Wisconsin. Ecology, 32(3), 476–496.","code":""},{"path":[]},{"path":"https://syoung9836.github.io/knfi/reference/iv_nfi.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates the importance values for National Forest Inventory Data — iv_nfi","text":"","code":"data(\"nfi_donghae\") # Calculate importance values without frequency importance <- iv_nfi(nfi_donghae, sp = \"SP\", frequency = FALSE) # Calculate importance values using genus genus_importance <- iv_nfi(nfi_donghae, sp = \"GENUS\")"},{"path":"https://syoung9836.github.io/knfi/reference/nfi_donghae.html","id":null,"dir":"Reference","previous_headings":"","what":"National Forest Inventory data for Donghae-si, Gangwon-do, Republic of Korea for testing the function — nfi_donghae","title":"National Forest Inventory data for Donghae-si, Gangwon-do, Republic of Korea for testing the function — nfi_donghae","text":"National Forest Inventory data Donghae-si, Gangwon-, Republic Korea testing function","code":""},{"path":"https://syoung9836.github.io/knfi/reference/nfi_donghae.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"National Forest Inventory data for Donghae-si, Gangwon-do, Republic of Korea for testing the function — nfi_donghae","text":"","code":"nfi_donghae"},{"path":"https://syoung9836.github.io/knfi/reference/nfi_donghae.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"National Forest Inventory data for Donghae-si, Gangwon-do, Republic of Korea for testing the function — nfi_donghae","text":"object class list length 3.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/read_nfi.html","id":null,"dir":"Reference","previous_headings":"","what":"Read Korean National Forest Inventory — read_nfi","title":"Read Korean National Forest Inventory — read_nfi","text":"read_nfi() function reads processes Korean National Forest Inventory (NFI). loads annual NFI files local computer, transforms data analysis-friendly format, performs data integrity verification. Users can specify districts tables load. NFI data can downloaded https://kfss.forest.go.kr/stat/.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/read_nfi.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read Korean National Forest Inventory — read_nfi","text":"","code":"read_nfi(dir, district = NULL, tables = c(\"tree\", \"cwd\"))"},{"path":"https://syoung9836.github.io/knfi/reference/read_nfi.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read Korean National Forest Inventory — read_nfi","text":"dir : character vector; directory containing NFI files. district : character vector; district names Korean (sido, sigungu, eupmyondong levels). NULL, entire dataset loaded. Combine multiple districts using c(). tables : character vector; tables import. Options: 'tree', 'cwd', 'stump', 'sapling', 'veg', 'herb', 'soil'. Combine multiple tables using c(). e.g., c('tree', 'cwd', 'stump', 'sapling', 'veg', 'herb', 'soil').","code":""},{"path":"https://syoung9836.github.io/knfi/reference/read_nfi.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read Korean National Forest Inventory — read_nfi","text":"data.frame; processed NFI data, structured easy analysis.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/read_nfi.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Read Korean National Forest Inventory — read_nfi","text":"function can load following tables: plot Base table containing subplot data including site, stand non-forest area, among details (automatically included). tree Tree survey table including species, DBH, height, among others. Data collected trees large trees survey plot subplot. cwd Coarse woody debris table including species, tree decay level, cause death, among details. Data collected center subplot cluster plot. stump Stumps table including species diameter 20 cm ground, among details. Data collected center subplot cluster. sapling Saplings table including species, diameter 20 cm ground, number individuals, among details. Data collected sapling survey plot subplot. veg Vegetation table (woody herbaceous plants). records species, number individuals, dominance, among others. Data collected three vegetation survey plots located within selected center subplot. selection includes 25% total number center subplots. herb Herbaceous table focused herbaceous list. Data collected sapling survey plot subplot. soil Soil table including thickness organic layer soil depth, among others. Data collected three soil survey plots located within selected center subplot. selection includes 25% total number center subplots. details, refer National Forest Inventory guidelines. function performs several data integrity validation. Corrects administrative region information subplots. (col: SIDO, SIDO_CD, SGG, SGG_CD, EMD, EMD_CD) Adds ecoregion catchment subplots. (col: ECOREGION, CATCHMENT) Verifies corrects coniferous/deciduous classification tree species. (col: CONDEC_CLASS, CONDEC_CLASS_CD, WDY_PLNTS_TYP, WDY_PLNTS_TYP_CD) Adds scientific names species. (col: SCIENTIFIC_NAME) Adds Korean English names plant families genera. (col: FAMILY, FAMILY_KOREAN, GENUS, GENUS_KOREAN) Adds whether plant native cultivated, identifies food, medicinal, fiber, ornamental resource. (col: NATIVE_CULTIVATED, FOOD, MEDICINAL, FIBER, ORNAMENTAL) Calculates basal area individual tree (col: BASAL_AREA) Calculates forest type, dominant species, dominant species percentage subplot cluster plot. (col: FORTYP_SUB, DOMIN_PERCNT_SUB, DOMIN_SP_SUB, FORTYP_CLST, DOMIN_PERCNT_CLST, DOMIN_SP_CLST) Species classification taxonomy follow standards set Korean Plant Names Index Committee Korea National Arboretum http://www.nature.go.kr/kpni/index..","code":""},{"path":"https://syoung9836.github.io/knfi/reference/read_nfi.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Read Korean National Forest Inventory — read_nfi","text":"manually download subsets annual NFI file, visit Korea Forest Service Forestry Statistics Platform (https://kfss.forest.go.kr/stat/), download .zip files, extract . -5th National Forest Inventory file: https://kfss.forest.go.kr/stat/ptl/article/articleFileDown.?fileSeq=2995&workSeq=2203 -6th National Forest Inventory file: https://kfss.forest.go.kr/stat/ptl/article/articleFileDown.?fileSeq=2996&workSeq=2204 -7th National Forest Inventory file: https://kfss.forest.go.kr/stat/ptl/article/articleFileDown.?fileSeq=2997&workSeq=2205 Use data(\"col_name\") view Korean English names column names. National Forest Inventory undergoes rigorous quality control, including internal reviews field inspections, errors may still exist due extensive nature survey (approximately 4,000 plots 70 items 7th phase). Please use data cautiously report anomalies help improve algorithms. want save results computer, can save Excel format. example, can use following code:writexl::write_xlsx(data, \"data.xlsx\") want read saved data back, use code : path <-\"../nfi_donghae.xlsx\" sheet_names <- readxl::excel_sheets(path) (sheet_name sheet_names) {nfi[[sheet_name]] <- readxl::read_excel(path, sheet = sheet_name) }","code":""},{"path":"https://syoung9836.github.io/knfi/reference/read_nfi.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read Korean National Forest Inventory — read_nfi","text":"","code":"# \\donttest{ # Load tree and CWD data for all districts nfi5_data <- read_nfi(\"D:/NFI/NFI5\", district = NULL, tables = c(\"tree\", \"cwd\")) #> Error in read_nfi(\"D:/NFI/NFI5\", district = NULL, tables = c(\"tree\", \"cwd\")): Directory D:/NFI/NFI5/ does not exist. # }"},{"path":"https://syoung9836.github.io/knfi/reference/summary_nfi.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate descriptive statistics for National Forest Inventory Data — summary_nfi","title":"Calculate descriptive statistics for National Forest Inventory Data — summary_nfi","text":"summary_nfi() function calculates comprehensive descriptive statistics National Forest Inventory (NFI) data. can provide summaries individual plots, entire study area, specific groups within study area using parameters byplot plotgrp. Users flexibility specifying data inclusion criteria analysis levels using parameters clusterplot, largetreearea, stockedland, talltree. parameters determine whether treat cluster plots single plots, include large tree survey plots, focus Stocked land tall trees.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/summary_nfi.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate descriptive statistics for National Forest Inventory Data — summary_nfi","text":"","code":"summary_nfi( data, plotgrp = NULL, byplot = FALSE, clusterplot = FALSE, largetreearea = TRUE, stockedland = TRUE, talltree = TRUE )"},{"path":"https://syoung9836.github.io/knfi/reference/summary_nfi.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate descriptive statistics for National Forest Inventory Data — summary_nfi","text":"data : list containing 'plot' 'tree' data frames, typically generated read_nfi. plotgrp : character vector; specifies variables 'plot' table use grouping. Use c() combine multiple variables. byplot : logical flag (default FALSE); TRUE, calculates statistics plot separately. FALSE, calculates entire dataset. clusterplot : logical flag (default FALSE); TRUE, treats cluster plot single unit. FALSE, calculates subplot separately. largetreearea : logical flag (default TRUE); TRUE, includes large tree survey plots analysis. FALSE, uses standard tree plots. stockedland : logical flag (default TRUE); TRUE, includes stocked land. FALSE, includes land types. talltree : logical flag (default TRUE); TRUE, includes tall trees. FALSE, includes trees shrubs.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/summary_nfi.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate descriptive statistics for National Forest Inventory Data — summary_nfi","text":"data.frame includes summary statistics. structure depends input parameters: byplot = TRUE, row represents plot. byplot = FALSE, row represents entire dataset group specified plotgrp","code":""},{"path":"https://syoung9836.github.io/knfi/reference/summary_nfi.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculate descriptive statistics for National Forest Inventory Data — summary_nfi","text":"function calculates following statistics: Plot-related statistics: Number cluster plots Number subplots Number subplots large trees (\\(\\geq\\) 30cm) observed Tree-related statistics: Number individual trees Number large trees Number dominant trees Number tree species Tree measurements stand statistics (mean standard deviation): DBH (Diameter Breast Height) Tree height Height dominant trees Number trees per hectare Basal area per hectare Volume per hectare largetreearea parameter affects calculations differently: per-hectare statistics (trees per hectare, basal area per hectare, volume per hectare), setting largetreearea = TRUE includes data large tree survey plots. statistics, trees large tree survey plots always excluded, regardless largetreearea setting.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/summary_nfi.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate descriptive statistics for National Forest Inventory Data — summary_nfi","text":"","code":"data(\"nfi_donghae\") # Basic usage summary_stats <- summary_nfi(nfi_donghae) # Summarize by the group, including all land types grouped_stats <- summary_nfi(nfi_donghae, plotgrp = \"OWN_CD\", stockedland = FALSE) # Summarize by individual plots, including both trees and shrubs plot_summaries <- summary_nfi(nfi_donghae, byplot = TRUE, talltree = FALSE)"},{"path":"https://syoung9836.github.io/knfi/reference/switchcol_nfi.html","id":null,"dir":"Reference","previous_headings":"","what":"Switch column names — switchcol_nfi","title":"Switch column names — switchcol_nfi","text":"switchcol_nfi() function allows switching original Korean column names English column names. input data English column names, changes original Korean names, vice versa.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/switchcol_nfi.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Switch column names — switchcol_nfi","text":"","code":"switchcol_nfi(data)"},{"path":"https://syoung9836.github.io/knfi/reference/switchcol_nfi.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Switch column names — switchcol_nfi","text":"data : list generated read_nfi.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/switchcol_nfi.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Switch column names — switchcol_nfi","text":"list dataframes switched column names.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/switchcol_nfi.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Switch column names — switchcol_nfi","text":"Important: Data original Korean column names used read_nfi functions except colchange_nfi() . option revert original Korean names provided solely users wish store process NFI data original column names.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/switchcol_nfi.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Switch column names — switchcol_nfi","text":"","code":"data(\"nfi_donghae\") #Switch column names from English to original Korean names nfi_donghae_kor <- switchcol_nfi(nfi_donghae) # Switch column names from original Korean to English names nfi_donghae_eng <- switchcol_nfi(nfi_donghae_kor)"},{"path":"https://syoung9836.github.io/knfi/reference/tsvis_nfi.html","id":null,"dir":"Reference","previous_headings":"","what":"Visualize time series data for National Forest Inventory Data — tsvis_nfi","title":"Visualize time series data for National Forest Inventory Data — tsvis_nfi","text":"tsvis_nfi() function analyzes visualizes data time series format. can visualize 'biomass', 'cwd', 'iv' data 'table', 'line', 'bar', 'map'. Users need select specific biomass variable, volume carbon visualize biomass. map visualization biomass, users must choose administrative unit level. uses iv_nfi biomass_nfi cwd_biomass_nfi function core calculations.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/tsvis_nfi.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Visualize time series data for National Forest Inventory Data — tsvis_nfi","text":"","code":"tsvis_nfi( data, y = \"biomass\", bm_type = NULL, output = \"line\", plotgrp = NULL, isannual = TRUE, admin = NULL, strat = \"FORTYP_SUB\", clusterplot = FALSE, largetreearea = TRUE, stockedland = TRUE, talltree = TRUE, sp = \"SP\", frequency = TRUE )"},{"path":"https://syoung9836.github.io/knfi/reference/tsvis_nfi.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Visualize time series data for National Forest Inventory Data — tsvis_nfi","text":"data : list generated read_nfi contains 'plot' 'tree' data frames. y : character vector; variable visualize. Must one 'biomass', 'cwd', 'iv'. bm_type : character vector; specific variable visualize 'biomass' 'cwd'. Must one 'volume', 'biomass', 'AG_biomass', 'carbon', 'co2'. output : character vector; desired type visualization. Must one 'table', 'line', 'bar', 'map'. plotgrp : character vector; specifies variables 'plot' table use grouping. Use c() combine multiple variables, output map, line bar plot, one variable can used. isannual : logical flag (default TRUE); TRUE, result provided annually, FALSE, provided 5-year intervals. admin : character vector; administrative unit visualizing 'biomass' 'cwd' map. Must one 'sido', 'sgg', 'emg'. strat : character vector; variable used post-stratification. National Forest Inventory Korea, typically used forest type. clusterplot : logical flag (default FALSE); TRUE, treats cluster plot single unit. FALSE, calculates subplot separately. largetreearea : logical flag (default FALSE); TRUE, includes large tree survey plots analysis. FALSE, uses standard tree plots. stockedland : logical flag (default TRUE); TRUE, includes stocked land. FALSE, includes land types. talltree : logical flag (default TRUE); TRUE, includes tall trees. FALSE, includes trees shrubs. sp : character vector; column name species information (e.g., \"SP\" species, \"GENUS\" genus-level analysis). frequency : logical flag (default TRUE); TRUE, includes frequency importance value calculations.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/tsvis_nfi.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Visualize time series data for National Forest Inventory Data — tsvis_nfi","text":"output map, line, bar plot: object class ggplot. output table: data.frame.","code":""},{"path":"https://syoung9836.github.io/knfi/reference/tsvis_nfi.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Visualize time series data for National Forest Inventory Data — tsvis_nfi","text":"visualize data map, need agree install kadmin package function execution install advance. kadmin package loads shapefiles Korea's Si, Si, Gun, Gu Eup, Myeon, Dong. Use drat::addRepo(\"SYOUNG9836\") install.packages(\"kadmin\") remotes::install_github(\"SYOUNG9836/kadmin\")","code":""},{"path":[]},{"path":"https://syoung9836.github.io/knfi/reference/tsvis_nfi.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Visualize time series data for National Forest Inventory Data — tsvis_nfi","text":"","code":"data(\"nfi_donghae\") # Visualize importance values as a table tsvis_iv <- tsvis_nfi(nfi_donghae, y = \"iv\", output = \"table\") # 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, grouped by age class tsvis_bm_line <- tsvis_nfi(nfi_donghae, y = \"biomass\", bm_type = \"carbon\", output = \"line\", plotgrp = \"AGE_CLS\") # \\donttest{ # 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\") # }"},{"path":"https://syoung9836.github.io/knfi/news/index.html","id":"knfi-100","dir":"Changelog","previous_headings":"","what":"knfi 1.0.0","title":"knfi 1.0.0","text":"Initial CRAN submission.","code":""}] diff --git a/sitemap.xml b/sitemap.xml index 85bf8b4..bcfbfb4 100644 --- a/sitemap.xml +++ b/sitemap.xml @@ -1,7 +1,5 @@ https://syoung9836.github.io/knfi/404.html -https://syoung9836.github.io/knfi/LICENSE-text.html -https://syoung9836.github.io/knfi/LICENSE.html https://syoung9836.github.io/knfi/articles/index.html https://syoung9836.github.io/knfi/articles/knfi.html https://syoung9836.github.io/knfi/authors.html