modPB: Photo-Based module - Generate photo-based estimates.

In FIESTA: Forest Inventory Estimation and Analysis

Photo-Based module - Generate photo-based estimates.

Description

Generates percent, area or ratio-of-means estimates, with associated sampling error by domain (and estimation unit). Calculations are based on Patterson (2012) photo-based estimators for the Nevada photo-based inventory.

Usage

modPB(
  PBpopdat = NULL,
  tabtype = "PCT",
  sumunits = FALSE,
  ratio = FALSE,
  landarea = "ALL",
  landarea.filter = NULL,
  nonsamp.pntfilter = NULL,
  pntfilter = NULL,
  pfilter = NULL,
  rowvar = NULL,
  colvar = NULL,
  domlut = NULL,
  domvarlst = NULL,
  ratioden = "ROWVAR",
  gainloss = FALSE,
  gainloss.vals = NULL,
  addtitle = FALSE,
  returntitle = FALSE,
  savedata = FALSE,
  table_opts = NULL,
  title_opts = NULL,
  savedata_opts = NULL,
  gui = FALSE,
  ...
)

Arguments

PBpopdat	List. Population data objects returned from modPBpop().
tabtype	String. Type of units for the table ("PCT", "AREA").
sumunits	Logical. If TRUE, estimation units are combined to one table for output. Note: only available if tabtype="AREA". Acres
ratio	Logical. If TRUE, ratio estimates are generated.
landarea	String. Sample area for estimates ("ALL", "CHANGE"). Used to describe landarea.filter.
landarea.filter	String. filter for land area. Must be R syntax.
nonsamp.pntfilter	String. An expression for filtering nonsampled points (e.g., cloud coverage). Must be R syntax.
pntfilter	String. A global filter for the pnt file. Must be R syntax.
pfilter	String. A global filter for the plt file. Must be R syntax.
rowvar	String. Name of domain variable in pnt used for output estimation table rows. If only 1 domain, must be rowvar. If no domain, rowvar=NULL.
colvar	String. Name of domain variable in pnt used for output estimation table columns. If only 1 domain, colvar=NULL.
domlut	DF/DT or comma-delimited (*.csv). Look-up table to define the variables in the pnt table with category codes (DOMCODE) and code names (DOMNAME), and to set a pretty name for the variable to use in output table (DOMTITLE). This table is also used to populate rowvar/colvar, row.orderby/col.orderby, and title.rowvar/title.colvar parameters. Optional.
domvarlst	String vector. A vector of variable names that can be row or column domains (codes and names). Optional.
ratioden	String. ("ROWVAR" or "COLVAR"). If ratio, defines whether the rowvar or colvar in estimation output table is the denominator.
gainloss	Logical. If TRUE, a table with the difference of gain and loss along with the variance and standard error, in percent, is generated.
gainloss.vals	String vector. A vector of names for values in gainloss table.
addtitle	Logical. If TRUE and savedata=TRUE, adds title to outfile.
returntitle	Logical. If TRUE, returns a character string of the title of the output data frame.
savedata	Logical. If TRUE, saves table(s) to outfolder.
table_opts	List. See help(table_options()) for a list of options.
title_opts	List. See help(title_options()) for a list of options.
savedata_opts	List. See help(savedata_options()) for a list of options. Only used when savedata = TRUE.
gui	Logical. If gui, user is prompted for parameters.
...	Parameters for modPBpop() if PBpopdat is NULL.

Details

If variables are NULL, then it will prompt user to input variables.

Value

A list with estimates with percent sampling error for rowvar (and colvar). If sumunits=TRUE or unitvar=NULL and colvar=NULL, one data frame is returned. Otherwise, a list object is returned with the following information. If savedata=TRUE, all data frames are written to outfolder.

est	DF. Estimated percent cover or area by rowvar, colvar, (and estimation unit).
pse	DF. Percent sampling error of estimates by rowvar, colvar (and estimation unit).
titlelst	List with 1 or 2 string vectors. If returntitle=TRUE a list with table title(s). The list contains one title if est and pse are in the same table and two titles if est and pse are in separate tables. Row and column tables are also included in list.
raw	List of data frames. If rawdata=TRUE, a list including the processing data used for estimation including: number of plots and conditions; stratification information; and 1 to 8 tables with calculated values for table cells and totals (See processing data below).

Raw data

pntsampcnt	Table. Number of points by rowvar/colvar (sampled and nonsampled).
stratdat	Data frame. Strata information by estimation unit.

	Variable	Description
	unitvar	estimation unit
	strvar	strata
	areavar	If tabtype='AREA', area by strata for estimation unit
	n.strata	number of plots in strata (after totally nonsampled plots removed)
	n.total	number of plots for estimation unit
	TOTAREA	If tabtype='AREA', total area for estimation unit
	strwt	proportion of area (or number of plots) by strata (strata weight)

processing data

Data frames. Separate data frames of variables used in estimation process for the rowvar, colvar and combination of rowvar and colvar (if colvar is not NULL), and grand total by estimation unit (unit.rowest, unit.colest, unit.grpest, respectively) and summed estimation units, if FIA=TRUE (rowest, colest, grpest, respectively). The data frames include the following information: Variable Description phat estimated proportion of covered land phat.var variance of estimated proportion of covered land areavar If tabtype='AREA', total area for estimation unit est If tabtype='AREA', estimated area of land phat*areavar If tabtype='PCT', estimated percent cover of land phat*100 est.var variance of estimated area of land phat.var*areavar If tabtype='PCT', estimated percent cover of land phat.var*100 est.se standard error of estimated area or percent cover sqrt(est.var) est.cv coefficient of variance of estimated area or percent cover est.se/est est.pse percent sampling error of estimated area of percent cover est.cv*100 CI99left left tail of 99 percent confidence interval for estimate CI99right right tail of 99 percent confidence interval for estimate CI95left left tail of 95 percent confidence interval for estimate CI95right right tail of 95 percent confidence interval for estimate CI67left left tail of 67 percent confidence interval for estimate CI67right right tail of 67 percent confidence interval for estimate if ratio=TRUE: Variable Description phat.n estimated proportion of covered land, for numerator (colvar) phat.var.n variance of estimated proportion of covered land, for numerator (colvar) phat.d estimated proportion of covered land, for denominator (rowvar) phat.var.d variance of estimated proportion of covered land, for denominator (rowvar) covar covariance of estimated proportion of numerator (rowvar) and denominator (colvar) rhat ratio of estimated proportions (numerator-colvar / denominator-rowvar) rhat.var variance of ratio of estimated proportions rhat.se standard error of ratio of estimated proportions sqrt(rhat.var) rhat.cv coefficient of variation of ratio of estimated proportions rhat.se/rhat areavar If tabtype='AREA', total area for estimation unit est If tabtype='AREA', estimated area of land rhat*areavar If tabtype='PCT', estimated percent cover of land rhat*100 est.var variance of estimated area of land rhat.var*areavar If tabtype='PCT', estimated percent cover of land rhat.var*100 est.se standard error of estimated area or percent cover sqrt(est.var) est.cv coefficient of variance of estimated area or percent cover est.se/est est.pse percent sampling error of estimated area of percent cover est.cv*100 CI99left left tail of 99 percent confidence interval for estimated area CI99right right tail of 99 percent confidence interval for estimated area CI95left left tail of 95 percent confidence interval for estimated area CI95right right tail of 95 percent confidence interval for estimated area CI67left left tail of 67 percent confidence interval for estimated area CI67right right tail of 67 percent confidence interval for estimated area

Note

STRATA:
Stratification is used to reduce variance in population estimates by partitioning the population into homogenous classes (strata), such as forest and nonforest. For stratified sampling methods, the strata sizes (weights) must be either known or estimated. Remotely-sensed data is often used to generate strata weights with proporation of pixels by strata. If stratification is desired (strata=TRUE), the required data include: stratum assignment for the center location of each plot, stored in either pltassgn or cond; and a look-up table with the area or proportion of the total area of each strata value by estimation unit, making sure the name of the strata (and estimation unit) variable and values match the plot assignment name(s) and value(s).

sumunits:
An estimation unit is a population, or area of interest, with known area and number of plots. Individual counties or combined Super-counties are common estimation units for FIA. An estimation unit may also be a subpopulation of a larger population (e.g., Counties within a State). Subpopulations are mutually exclusive and independent within a population, therefore estimated totals and variances are additive. For example, State-level estimates are generated by summing estimates from all subpopulations within the State (Bechtold and Patterson. 2005. Chapter 2). Each plot must be assigned to only one estimation unit.

If sumunits=TRUE, estimates are generated by estimation unit, summed together, and returned as one estimate. If rawdata=TRUE, estimates by individual estimation unit are also returned.

If sumunits=FALSE, estimates are generated and returned by estimation unit as one data frame. If savedata=TRUE, a separate file is written for each estimation unit.

stratcombine:
If TRUE and less than 2 plots in any one estimation unit, all estimation units with 10 or less plots are combined. The current method for combining is to group the estimation unit with less than 10 plots with the estimation unit following in consecutive order (numeric or alphabetical), restrained by survey unit (UNITCD) if included in dataset, and continuing until the number of plots equals 10. If there are no estimation units following in order, it is combined with the estimation unit previous in order.

rowlut/collut:
There are several objectives for including rowlut/collut look-up tables: 1) to include descriptive names that match row/column codes in the input table; 2) to use number codes that match row/column names in the input table for ordering rows; 3) to add rows and/or columns with 0 values for consistency. No duplicate names are allowed.

Include 2 columns in the table:
1-the merging variable with same name as the variable in the input merge table;
2-the ordering or descriptive variable.
If the ordering variable is the rowvar/colvar in the input table and the descriptive variable is in rowlut/collut, set row.orderby/col.orderby equal to rowvar/colvar. If the descriptive variable is the rowvar/colvar in the input table, and the ordering code variable is in rowlut/collut, set row.orderby/col.orderby equal to the variable name of the code variable in rowlut/collut.

Author(s)

Tracey S. Frescino, Paul L. Patterson, Elizabeth A. Freeman

References

Frescino, Tracey S.; Moisen, Gretchen G.; Megown, Kevin A.; Nelson, Val J.; Freeman, Elizabeth A.; Patterson, Paul L.; Finco, Mark; Brewer, Ken; Menlove, James 2009. Nevada Photo-Based Inventory Pilot (NPIP) photo sampling procedures. Gen. Tech. Rep. RMRS-GTR-222. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 30 p.

Patterson, Paul L. 2012. Photo-based estimators for the Nevada photo-based inventory. Res. Pap. RMRS-RP-92. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 14 p.

Examples

# Load necessary data from FIESTA
## Point data
icepntfn <- system.file("extdata",
                        "PB_data/icepnt_utco1135.csv",
                         package = "FIESTA")
icepnt <- read.csv(icepntfn)

## Plot data
icepltfn <- system.file("extdata",
                        "PB_data/icepltassgn_utco1135.csv",
                         package = "FIESTA")
iceplt <- read.csv(icepltfn)

## County data
unitareafn <- system.file("extdata", 
                          "PB_data/unitarea_utco1135.csv",
                           package = "FIESTA")
unitarea <- read.csv(unitareafn)

## ICE Cover
icecoverfn <- system.file("extdata",
                          "PB_data/cover_LUT.csv",
                           package = "FIESTA")
icecover <- read.csv(icecoverfn)
names(icecover) <- sub("cover", "cover_1", names(icecover))

# Set up population data (see ?modPBpop() for more information)
PBpopunit <- modPBpop(pnt = icepnt, 
                      pltassgn = iceplt, 
                      pltassgnid = "plot_id", 
                      pntid = "dot_cnt",
                      unitarea = unitarea, 
                      unitvar = "ESTN_UNIT")
# Photo-based estimation with point-level data by estimation unit (county)                       
## Without summing units
cover1.unit.area <- modPB(
  PBpopdat = PBpopunit,
  tabtype = "AREA",
  rowvar = "cover_1",
  nonsamp.pntfilter = "cover_1 != 999",
  table_opts = list(rowlut = icecover),
  title_opts = list(title.rowvar = "Land Cover (2011)")
) 

cover1.unit.area$est
                          
## With summing units
cover1.unit.area.sum <- modPB(
  PBpopdat = PBpopunit,
  tabtype = "AREA",
  rowvar = "cover_1",
  nonsamp.pntfilter = "cover_1 != 999",
  sumunits = TRUE,
  table_opts = list(rowlut = icecover),
  title_opts = list(title.rowvar = "Land Cover (2011)")
)

cover1.unit.area.sum$est   
          

FIESTA documentation built on Nov. 22, 2023, 1:07 a.m.