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knfi

1.0.2

Analysis of Korean National Forest Inventory Database

0packages depend
3Kdownloads / year
test coverage
13/13checks pass

Overview

About
Maintained by Sinyoung ParkFirst published 2024-10-144 releasesCRAN page ↗GitHub ↗

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 downloaded separately. 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.

Install

Health

CRAN checks
13OK
Slowest check: 4.9 min · r-oldrel-windows-x86_64
Code health
None
Tests · ratio 0.00
not tracked
Coverage
100%
Documentation · exports
21
Dependencies · direct
Check history
  • OK2026-08-05
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • NOTE2026-08-01
    12 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • OK2026-06-09
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • ERROR2026-06-08
    12 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
  • OK2026-04-25
    12 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Show 1 earlier snapshots
  • NOTE2026-03-10
    11 OK · 3 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMEYes · 384 wordsVignettesYes · dynamicpkgdown siteNoNEWSYes · 100% structuredCode of conductNoContributing guideNo
Examples that run
89%
Documented parameters
100%
Return-value docs
100%
References docs
36%

Downloads

3K
CRAN downloads in the past year
Rank #17,042 · ~8/day · ~254/mo
Daily download trend is not available in this view yet.
20330 days
64890 days
3K1 year
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Repository

Repository
1Stars
0Forks
0Open issues
0Open PRs
1Releases
36Commits
1Contributors
forestryrdata-analysis-r
36 commits · Last activity 2026-01-22

Repository practices

Upstream repositoryBeta

3 development-tooling and community-health practices detected across 3 families in the upstream repository

Checks run against github.com/syoung9836/knfi on 2026-08-23.

Continuous integration (1)
GitHub Actions
CRAN release process (1)
cran-comments.md
Lint, format, editor (1)
RStudio project
How this is detected·Detection ruleset v1 (2026-07-18)

Dependencies

Declared dependencies
23 external dependencies (excludes base and recommended)
Depends (1)
R >= 3.6
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Code & Tests

Datasets

People & History

People (5)
Maintainer (1)
Author, Maintainer
Authors (5)
Author, Maintainer
Author, Contributor
Author, Contributor
Author, Thesis advisor
Author, Contributor
Contributors (3)
Author, Contributor
Author, Contributor
Author, Contributor
Package Timeline

4 releases. Pick two to compare their code metrics. R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
  • 1.0.2Latest
    2026-01-22 · current release · diff ↗
  • R
    R 4.5.0 released · 2025-04-11
  • 1.0.1.9
    2024-12-03 · diff ↗
  • 1.0.1
    2024-11-21 · diff ↗
  • 1.0.0
    2024-10-14
  • R
    R 4.4.0 released · 2024-04-24

Package metadata

First published
2024-10-14
Total releases
4 / 2 yrs
License
GPL-3 OSI
Additional repositories
SYOUNG9836.github.io
Minimum R
≥ 3.6
Bundled data
79 KB / 2 files
Download size
1.7 MB
Installed size
not tracked yet
With dependencies
not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("knfi")
Park, S., Cho, W., Kim, I., Ko, D. W., & Lim, W. (2026). knfi: Analysis of Korean National Forest Inventory Database (Version 1.0.2) [Computer software]. https://doi.org/10.32614/CRAN.package.knfi

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for knfi version 1.0.2 [Data set]. HJJB, LLC. Data release v2026-08-24. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-24, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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