readFIA: Load FIA database into R environment from local directory
In rFIA: Estimation of Forest Variables using the FIA Database

Description Usage Arguments Details Value Note Author(s) References See Also Examples

Loads FIA Datatables into R from .csv files stored in a local directory. If you have not previously downloaded FIA Data from the FIA Datamart, use getFIA to download data for your region of interest and load it into R. Capable of merging multiple state downloads of the FIA database for regional analysis. Simply store each set of state data, as downloaded from the FIA Datamart, in the same directory and hand to readFIA.

1 2	readFIA(dir, common = TRUE, tables = NULL, states = NULL, inMemory = TRUE, nCores = 1, ...)

`dir`	directory where FIA Datatables are stored.
`common`	logical; if TRUE, only import most commonly used tables, including all required for `rFIA` functions (see Details for list of tables).
`tables`	character vector; names of specific tables to be imported (e.g. 'PLOT', 'TREE', 'COND', 'TREE_GRM_COMPONENT').
`states`	character; state/ US territory abbreviations (e.g. 'AL', 'MI', etc.) indicating which state subsets to read. Data for each state must be in `dir`. Choose to read multiple states by passing character vector of state abbreviations (e.g. `states = c('RI', 'CT', 'MA')`). If `states = NULL`, data for all states within `dir` will be read in and merged into a regional database.
`inMemory`	logical; should data be stored in-memory? If FALSE, data will be read in state-by-state when an estimator function is called (e.g., `tpa`). This conserves RAM and allows the user to to produce estimates using very large databases that does not all fit in memory at once.
`nCores`	numeric; number of cores to use for parallel implementation. Check available cores using `detectCores`. Default = 1, serial processing.
`...`	other arguments to pass to `fread`.

Download subsets of the FIA Database using getFIA (recommended), or manually from the FIA Datamart: https://apps.fs.usda.gov/fia/datamart/datamart.html. Once downloaded, unzip the directory (if downloaded manually), and read into R using readFIA.

If common = TRUE, the following tables will be imported: COND, COND_DWM_CALC, INVASIVE_SUBPLOT_SPP, PLOT, POP_ESTN_UNIT, POP_EVAL, POP_EVAL_GRP, POP_EVAL_TYP, POP_PLOT_STRATUM_ASSGN, POP_STRATUM, SUBPLOT, TREE, TREE_GRM_COMPONENT. These tables currently support all functionality with rFIA, and it is recommended that only these tables be imported to conserve RAM and reduce processing time.

If you wish to merge multiple state downloads of FIA data (e.g. Michigan and Indiana state downloads), simply place both sets of datatables in the same directory (done for you when using getFIA) and import with readFIA. Upon import, corresponding tables (e.g. MI_PLOT and IN_PLOT) will be merged, and analysis can be completed for the entire region or within spatial units which transcend state boundaries (e.g. Ecoregion subsections).

Easy, efficient parallelization is implemented with the parallel package. Users must only specify the nCores argument with a value greater than 1 in order to implement parallel processing on their machines. Parallel implementation is achieved using a snow type cluster on any Windows OS, and with multicore forking on any Unix OS (Linux, Mac). Implementing parallel processing may substantially decrease decrease free memory during processing, particularly on Windows OS. Thus, users should be cautious when running in parallel, and consider implementing serial processing for this task if computational resources are limited (nCores = 1).

List object containing FIA Datatables. List elements represent individual FIA Datatables stored as data.frame objects. Names of list elements reflect names of files from which they were read into R environment (File names should not be changed after download from FIA Datamart).

If multiple subsets of the FIA database are held in the same directory (e.g. Michigan and Indiana state downloads), corresponding tables will be merged (e.g. PLOT table returned contains plots in both Michigan and Indiana).

To download subsets of the FIA Database manually, go online to the FIA Datamart (https://apps.fs.usda.gov/fia/datamart/datamart.html) and choose to download .csv files. Here you can choose to download subsets of the full database for individual states, or select to download individual tables. For use with the rFIA package, we recommend download of subsets of the full database representing individual states of interest. Files must be unzipped in order to be imported.

Alternatively, use getFIA to automate the download, reading, and saving process for you (recommended).

Hunter Stanke and Andrew Finley

FIA DataMart: https://apps.fs.usda.gov/fia/datamart/datamart.html

FIA Database User Guide: https://www.fia.fs.fed.us/library/database-documentation/

clipFIA, getFIA

## Not run: \donttest{
## The following examples shows how you
## can take an existing in-memory FIA.Datbase,
## save it, and read it back in!


## First download the common tables for Rhode Island,
## load into R, but don't save it anywhere yet
db <- getFIA(states = 'RI')



## Now we write it all out
## Replace tempdir() with the path to your
## directory (where data will be saved)
writeFIA(db, dir = tempdir())


## Then read it back in with readFIA
db <- readFIA(dir = tempdir())

}
## End(Not run)