Other packages > Find by keyword >

knfi  

Analysis of Korean National Forest Inventory Database
View on CRAN: Click here


Download and install knfi package within the R console
Install from CRAN:
install.packages("knfi")

Install from Github:
library("remotes")
install_github("cran/knfi")

Install by package version:
library("remotes")
install_version("knfi", "1.0.2")



Attach the package and use:
library("knfi")
Maintained by
Sinyoung Park
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-10-14
Latest Update: 2024-12-03
Description:
Understanding the current status of forest resources is essential for monitoring changes in forest ecosystems and generating 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 stand, forest resource, and forest vegetation surveys. Many researchers use NFI as the primary data for research, such as biomass estimation or analyzing the importance value of each species over time and space, depending on the research purpose. However, the large volume of accumulated forest survey data from across the country can make it challenging to manage and utilize such a vast dataset. To address this issue, we developed an R package that efficiently handles large-scale NFI data across time and space. The package offers a comprehensive workflow for NFI data analysis. It starts with data processing, where read_nfi() function reconstructs NFI data according to the researcher's needs while performing basic integrity checks for data quality.Following this, the package provides analytical tools that operate on the verified data. These include functions like summary_nfi() for summary statistics, diversity_nfi() for biodiversity analysis, iv_nfi() for calculating species importance value, and biomass_nfi() and cwd_biomass_nfi() for biomass estimation. Finally, for visualization, the tsvis_nfi() function generates graphs and maps, allowing users to visualize forest ecosystem changes across various spatial and temporal scales. This integrated approach and its specialized functions can enhance the efficiency of processing and analyzing NFI data, providing researchers with insights into forest ecosystems. The NFI Excel files (.xlsx) are not included in the R package and must be downloadedseparately. Users can access these NFI Excel files by visiting the Korea Forest Service Forestry Statistics Platform <https://kfss.forest.go.kr/stat/ptl/article/articleList.do?curMenu=11694&bbsId=microdataboard> to download the annual NFI Excel files, which are bundled in .zip archives. Please note that this website is only available in Korean, and direct download links can be found in the notes section of the read_nfi() function.
How to cite:
Sinyoung Park (2024). knfi: Analysis of Korean National Forest Inventory Database. R package version 1.0.2, https://cran.r-project.org/web/packages/knfi. Accessed 05 Mar. 2026.
Previous versions and publish date:
1.0.0 (2024-10-14 14:00), 1.0.1.9 (2024-12-03 08:20), 1.0.1 (2024-11-21 05:30)
Other packages that cited knfi R package
View knfi citation profile
Other R packages that knfi depends, imports, suggests or enhances
Complete documentation for knfi
Functions, R codes and Examples using the knfi R package
Full knfi package functions and examples
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

nextGenShinyApps  
Craft Exceptional 'R Shiny' Applications and Dashboards with Novel Responsive Tools
Nove responsive tools for designing and developing 'Shiny' dashboards and applications. The scripts ...
Download / Learn more Package Citations See dependency  
ClimClass  
Climate Classification According to Several Indices
Classification of climate according to Koeppen - Geiger, of aridity indices, of continentality indi ...
Download / Learn more Package Citations See dependency  
imagefx  
Extract Features from Images
Synthesize images into characteristic features for time-series analysis or machine learning applicat ...
Download / Learn more Package Citations See dependency  
roccv  
ROC for Cross Validation Results
Cross validate large genetic data while specifying clinical variables that should always be in the m ...
Download / Learn more Package Citations See dependency  
pinp  
'pinp' is not 'PNAS'
A 'PNAS'-alike style for 'rmarkdown', derived from the 'Proceedings of the National Academy of Scie ...
Download / Learn more Package Citations See dependency  
diffIRT  
Diffusion IRT Models for Response and Response Time Data
Package to fit diffusion-based IRT models to response and response time data. Models are fit using ...
Download / Learn more Package Citations See dependency  

26,264

R Packages

223,360

Dependencies

70,244

Author Associations

26,265

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA