CRAN/E | rFIA

rFIA

Estimation of Forest Variables using the FIA Database

Installation

About

The goal of 'rFIA' is to increase the accessibility and use of the United States Forest Services (USFS) Forest Inventory and Analysis (FIA) Database by providing a user-friendly, open source toolkit to easily query and analyze FIA Data. Designed to accommodate a wide range of potential user objectives, 'rFIA' simplifies the estimation of forest variables from the FIA Database and allows all R users (experts and newcomers alike) to unlock the flexibility inherent to the Enhanced FIA design. Specifically, 'rFIA' improves accessibility to the spatial-temporal estimation capacity of the FIA Database by producing space-time indexed summaries of forest variables within user-defined population boundaries. Direct integration with other popular R packages (e.g., 'dplyr', 'tidyr', and 'sf') facilitates efficient space-time query and data summary, and supports common data representations and API design. The package implements design-based estimation procedures outlined by Bechtold & Patterson (2005) doi:10.2737/SRS-GTR-80, and has been validated against estimates and sampling errors produced by FIA 'EVALIDator'. Current development is focused on the implementation of spatially-enabled model-assisted estimators to improve population, change, and ratio estimates.

Citation rFIA citation info
github.com/hunter-stanke/rFIA
Bug report File report

Key Metrics

Version 1.0.0
R ≥ 3.1.0
Published 2021-12-15 863 days ago
Needs compilation? no
License GPL-3
CRAN checks rFIA results

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Maintainer

Maintainer

Hunter Stanke

stankehu@msu.edu

Authors

Hunter Stanke

aut / cre

Andrew Finley

aut

Material

README
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

rFIA archive

Depends

R ≥ 3.1.0

Imports

dplyr ≥ 1.0.0
dtplyr ≥ 1.0.0
tidyr ≥ 1.0.0
stringr
sf
parallel
methods
data.table
bit64
tidyselect ≥ 1.0.0
rlang
ggplot2

Suggests

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