FIESTA - Data Tools
In FIESTA: Forest Inventory Estimation and Analysis

library(knitr)
knitr::opts_chunk$set(message = F, warning = F)

# Sets up output folding
hooks = knitr::knit_hooks$get()
hook_foldable = function(type) {
  force(type)
  function(x, options) {
    res = hooks[[type]](x, options)

    if (isFALSE(options[[paste0("fold.", type)]])) return(res)

    paste0(
      "<details><summary>", type, "</summary>\n\n",
      res,
      "\n\n</details>"
    )
  }
}
knitr::knit_hooks$set(
  output = hook_foldable("output"),
  plot = hook_foldable("plot")
)

data.table::setDTthreads(2)

FIESTA Overview

The R package, FIESTA (Forest Inventory ESTimation and Analysis) is a research estimation tool for analysts that work with sample-based inventory data like that from the U.S. Department of Agriculture, Forest Service, Forest Inventory and Analysis (FIA) Program to accommodate: unique population boundaries, different evaluation time periods, customized stratification schemes, non-standard variance equations, integration of multi-scale remotely-sensed data and other auxiliary information, and interaction with other modeling and estimation tools from CRAN R's library of packages. FIESTA contains a collection of functions that can access FIA databases, summarize and compile plot and spatial data, and generate estimates with associated sampling errors.

Functions are organized by type or objective and are named with a corresponding prefix:

Core Functions

Database tools (DB) - functions for querying and extracting data from FIA's national database.
Data tools (dat) - functions for summarizing and exploring FIA data.
Spatial tools (sp) - functions for manipulating and summarizing spatial data.

Estimation Modules

Green-Book (GB) - functions for FIA’s standard ‘Green-Book’ estimators.
Photo-Based (PB) - functions for supplementary photo-based estimators.
Small Area (SA) - functions for integration with available small area estimators (SAE).
Model-Assisted (MA) - functions for integration with available Model-Assisted estimators.

Analysis Tools

Analysis tools (an) - wrapper functions for stream-lining estimation processes.

Overview of FIESTA data (dat) tools

FIESTA's dat tools assist with customizing variables as well as summarizing and visualizing FIA data. The datLUTclass and datLUTnm functions help with merging look-up tables to support new variables, standard FIA code names or unique names, or groupings of discrete or continuous data values. The datSum* functions provide tools for aggregating FIA data for estimation, mapping, or exploratory data analyses.

FIESTA's tree estimates require tree data summarized to the condition (base unit) domain level and extrapolated to an acre to account for trees sampled from different plot sizes. An adjustment factor is applied to adjust for nonsampled plots across different strata (adj='samp') within the area of interest for GB estimates or within each plot (adj='plot') for MA and SA estimates.

Objective of tutorial

The objective of this tutorial is to demonstrate the use of FIESTA's dat tools for customizing, summarizing, and visualizing FIA data. The examples use data from two inventory years of field measurements in the state of Wyoming, from FIADB_1.7.2.00, last updated June 20, 2018, downloaded on June 25, 2018 and stored as internal data objects in FIESTA.

FUNCTION | DESCRIPTION -------------- | --------------------------------------------------------------- datFilter() | Subsets a data table by specified filter(s). datFreq() | Generates frequency table. datPivot() | Generates pivot table. datBarplot() | Generates bar plot. datBarplotStacked() | Generates stacked bar plot. datPiechart() | Generates pie chart. datLUTclass() | Merge look-up table for classifying continuous data (e.g., DIA). datLUTnm() | Merge look-up table to append names or categories. datSumCond() | Aggregates numeric condition data to plot level. datSumTree() | Aggregates numeric tree data to the plot or condition-level. datSumTreeDom() | Aggregates numeric tree data by tree domain to plot or condition level.

Set up

We just load the FIESTA library to get started with the examples.

# Load library
library(FIESTA)

The following examples use FIA data from Wyoming for inventory years 2011-2013.

`datFilter()`

The datFilter function subsets a data table by specified filter(s) or logical statement and returns a list of the filtered data table and the filter.

FIESTA Forest Inventory Estimation and Analysis

FIESTA - Data Tools In FIESTA: Forest Inventory Estimation and Analysis

FIESTA Overview

Overview of FIESTA data (dat) tools

Objective of tutorial

Set up

Example 1: Subset National Forest Conditions in Wyoming

Example 2: Subset Trees That Are Standing Dead Aspen Trees in Wyoming

Example 3: Subset Trees That Are Standing Dead Aspens in Wyoming, and Subset Other Tables to Match

Example: Multiple Uses

Example: Multiple Uses

Example 1: Reference Table Stored in FIESTA with 2-inch Diameter Classes

Example 2: Create New Reference Table and Merge to Tree Table

Example 3: Use Cutbreaks to Classify LIVE_CANOPY_CVR_PCT variable from WYcond Table

Example: Multiple Uses

Example: Multiple Uses

Example 1: Sum of Basal Area and Net Cubic-foot Volume of Live Trees by Plot (TPA=FALSE)

Example 2: Sum of Basal Area Per Acre and Net Cubic-foot Volume Per Acre of Live Trees by Plot (TPA=TRUE)

Example 1 & 2 Check: Test BA Results for 1 Plot

Example 3: Average Diameter and Height of Live Trees by Plot

Example 4a: Number of Live Trees by Plot (TPA=TRUE)

Example 4b: Adjust Summed Live Tree Volume to Account for Nonsampled Conditions on Plot

Example 4c: Compare with Unadjusted Estimate for Plot Where 25% of Plot is Nonsampled (COND_STATUS_CD = 5 and CONDPROP_UNADJ = 0.25)

Example 5a: Number of Live Trees Plus Seedlings by Plot (TPA=TRUE)

Example 5b: Number of Live Trees Plus Seedlings by Plot (TPA=TRUE) - Adjusted

Example 1: Sum of Live Basal Area Per Acre by Species

Example 2: Number of Live Trees by Species

Example 3: Number of Live Trees by Species - Seedlings

Example 4: Number of Live Trees by Species, Including Seedlings

Example 5: Presence of Live Trees by Species, Including Seedlings

Example 6: Presence and Proportion of Live Trees by Species, Including Seedlings

Example 7: Presence and Proportion and Cover of Live Trees by Species, Including Seedlings (Add Barplot)

Example 8: Presence and Proportion of Live Trees by Species, Including Seedlings (Add Barplot)

Example 9: Total Basal Area Per Acre of Limber Pine (SPCD=113) Trees >= 1.0 DIA

Example 10: Species and Diameter Class

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FIESTA
Forest Inventory Estimation and Analysis

FIESTA - Data Tools
In FIESTA: Forest Inventory Estimation and Analysis

Example 1: Reference Table Stored in `FIESTA` with 2-inch Diameter Classes

Example 3: Use Cutbreaks to Classify `LIVE_CANOPY_CVR_PCT` variable from `WYcond` Table

Example 1: Sum of Basal Area and Net Cubic-foot Volume of Live Trees by Plot (`TPA=FALSE`)

Example 2: Sum of Basal Area Per Acre and Net Cubic-foot Volume Per Acre of Live Trees by Plot (`TPA=TRUE`)

Example 4a: Number of Live Trees by Plot (`TPA=TRUE`)

Example 4c: Compare with Unadjusted Estimate for Plot Where 25% of Plot is Nonsampled (`COND_STATUS_CD = 5` and `CONDPROP_UNADJ = 0.25`)

Example 5a: Number of Live Trees Plus Seedlings by Plot (`TPA=TRUE`)

Example 5b: Number of Live Trees Plus Seedlings by Plot (`TPA=TRUE`) - Adjusted

Example 9: Total Basal Area Per Acre of Limber Pine (`SPCD=113`) Trees >= 1.0 DIA