Unlocking the FIA Database in R

Install the released version from CRAN:

install.packages("rFIA")

Or, the development version from GitHub:

devtools::install_github('hunter-stanke/rFIA')

Find us on Github Report a bug

About rFIA


rFIA is an R package aimed at increasing the accessibility and use of the USFS Forest Inventory and Analysis (FIA) Database. Providing a user-friendly, open source toolset to easily query and analyze FIA Data, rFIA simplifies the estimation of forest variables from the FIA Database and allows all R users (experts and newcomers alike) to unlock the flexibility and potential inherent to the Enhanced FIA design.

Specifically, rFIA improves accessibility to the spatio-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, sp, 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), and has been validated against estimates and sampling errors produced by FIA’S EVALIDator.

Current development is focused on the implementation of spatially-enabled model-assisted estimators to improve point and change estimation at small spatial and temporal scales. We envision rFIA as a key component in the future of the FIA Program, targeting expansion in small area estimation, timber product monitoring, urban inventory, and the development of long-term monitoring and reporting tools.

See Example Usage to get started. To report a bug or suggest additions to rFIA, please use our active issues page on GitHub, or contact Hunter Stanke (lead developer and maintainer). To cite rFIA, please refer to our recent publication in Environmental Modeling and Software (doi: https://doi.org/10.1016/j.envsoft.2020.104664).


Meet the Authors


Recent Posts

We can use FIA data to estimate how forest structure has changed over time (i.e., has density increased or declined) or to estimate the …

The increasing availability of remeasured FIA plots offers the unique opportunity to move from asking questions about the status of …

rFIA v0.3.1 introduced breaking changes to the biomass function. Though we try to avoid breaking changes whenever possible, they are …

Projects

Estimating county-level forest carbon stocks

Here, we use the post-stratified estimators implemented in rFIA to estimate current forest carbon stocks within counties across the …

Estimating temporal trends in merchantable wood volume

Here, we develop a temporally-explicit unit-level estimator of trends in merchantable wood volume in Washington County, Maine, using a …

2020 Forest Health Monitoring National Report

We present three case studies chosen to demonstrate some aspects of rFIA’s potential to advance forest health evaluation and monitoring …

Introducing the Forest Stability Index

Here, we develop a standardized forest demographic index and use it to quantify trends in tree population dynamics over the last two …

Forests of the Appalachian Trail

The Appalachian Trail is uniquely situated to serve as a barometer for the air, water, and biological diversity of the Appalachian …

Sponsors


Contact