Green-book Estimators
Green-Book (GB) module overview
FIESTA‘s Green-Book (GB) module calculates population
estimates and their sampling errors based on Bechtold and Patterson’s
(2005), ’Green-Book’ for FIA’s nationally-consistent, systematic annual
sample design, chapter 4 (Scott et al. 2005). FIA’s sample design is
based on 2 phases: the first phase uses remotely-sensed data to stratify
the land area to increase precision of estimates; while the 2nd phase
obtains photo and ground observations and measurements for a suite of
information across a hexagonal grid, each approximately 6000 acres in
size. The associated estimators and variance estimators are used for
area and tree attribute totals with the assumption of a simple random,
stratified design and double sampling for stratification. Adjustment
factors are calculated by estimation unit and strata to account for
nonsampled (nonresponse) conditions.
Functions include non-ratio estimators for area and tree estimates by
domain and ratio-of-means estimators for per-acre and per-tree estimates
within domain. In addition, FIESTA adjusts for nonsampled
conditions, supports post-stratification for reducing variance, and
reports by estimation unit or a summed combination of estimation units.
Output from the Green-Book module was tested and compared to output from
FIA’s publicly-available online tool (EVALIDator) for
state-level population estimates and associated sampling errors
generated from the FIA Database (FIADB).
Objective of tutorial
The Green-Book estimators can be used with FIA’s standard state-level population data (i.e, Evaluation) from the FIA database (FIADB) and also population data from a custom boundary. The population data includes a set of FIA plot data and summarized auxiliary information for post-stratification, including a table of area by estimation unit within the population, and a table of strata proportions by estimation unit. This tutorial steps through several examples using FIESTA’s Green Book module, for four different populations: (POP1) an FIA standard Evaluation, Wyoming 561301; (POP2) a custom boundary with one population, Bighorn National Forest; (POP3) a custom boundary with sub-populations, Bighorn National Forest Districts; and (POP4) an FIA standard Evaluation, Rhode Island 441901, stored in a SQLite database. All examples can be used with any population, standard or custom.
GB Examples
GB Example Data
View GB Example Data
Example FIA plot data from FIADB
The examples use FIA plot data from FIA Evaluation 561301, including
three 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.
Wyoming (WY), Inventory Years 2011-2013 (Evaluation 561301)
| Data Frame | Description |
|---|---|
| WYplt | WY plot-level data |
| WYcond | WY condition-level data |
| WYtree | WY tree-level data |
Example Auxiliary data
Auxiliary data for state-level estimates, including plot-level
estimation unit and stratum assignments; area by estimation unit; and
pixel counts by strata class and estimation unit, were downloaded from
FIADB at the same time, from the same FIA Evaluation (i.e., 561301), and
stored as internal data objects in FIESTA. Estimates using
auxiliary data from FIADB can be compared with EVALIDator estimates,
using the 2013 evaluation (https://apps.fs.usda.gov/fiadb-api/evalidator).
Auxiliary data for the custom boundaries are summarized from spatial layers stored as external objects in FIESTA, originating from the USDA Forest Service, Automated Lands Program (ALP; 2018) and from a 250m resolution, Moderate Resolution Imaging Spectroradiometer (MODIS), classified map, reclassified from 3 to 2 classes: 1:forest; 2:nonforest (Ruefenacht et al. 2008)
Wyoming (WY), Auxiliary data from FIADB (Evaluation 561301)
| Data Frame | Description |
|---|---|
| WYpltassgn | WY plot-level data with strata and estimation unit assignments |
| WYunitarea | WY estimation unit look-up table with total acres by estimation unit (ESTUNIT) |
| WYstratalut | WY strata look-up table with pixel counts (P1POINTCNT) by strata and estimation unit |
Wyoming (WY), Auxiliary data from other sources
| External data | Description |
|---|---|
| WYbighorn_adminbnd.shp | Polygon shapefile of WY Bighorn National Forest Administrative boundary1 |
| WYbighorn_districtbnd.shp | Polygon shapefile of WY Bighorn National Forest District boundaries2 |
| WYbighorn_forest_nonforest_250m.tif | GeoTIFF raster of predicted forest/nonforest (1/0)3 |
1USDA Forest Service, Automated Lands Program (ALP). 2018. S_USA.AdministrativeForest (http://data.fs.usda.gov/geodata/edw). Description: An area encompassing all the National Forest System lands administered by an administrative unit. The area encompasses private lands, other governmental agency lands, and may contain National Forest System lands within the proclaimed boundaries of another administrative unit. All National Forest System lands fall within one and only one Administrative Forest Area.
2USDA Forest Service, Automated Lands Program (ALP). 2018. S_USA.RangerDistrict (http://data.fs.usda.gov/geodata/edw). Description: A depiction of the boundary that encompareasses a Ranger District.
3Based on 250m resolution, Moderate Resolution Imaging Spectroradiometer (MODIS), classified map, reclassified from 3 to 2 classes: 1:forest; 2:nonforest. Projected in Albers Conical Equal Area, Datum NAD27 (Ruefenacht et al. 2008).
Set up
First, you’ll need to load the FIESTA library:
Next, you’ll need to set up an “outfolder”. This is just a file path
to a folder where you’d like FIESTA to send your data
output. For this vignette, we have set our outfolder file path as a
temporary directory.
Get auxiliary data for custom examples
Now, we need to get the auxiliary data for the custom boundaries. The FIESTA spGetStrata function is a spatial wrapper function to facilitate extraction and summary of user-defined spatial data used for post-stratification. The function uses the FIESTA spExtractPoly and spExtractRast functions to subset (i.e., clip) plots to the boundary and extract values from estimation unit (i.e., polygon) and strata values (i.e., raster) to plot center locations, respectively. Other internal spatial functions calculate stratum pixel counts and area by estimation unit. If a polygon strata layer is given, the FIESTA spPoly2Rast function converts the polygon layer to raster before calculating strata weights.
Our custom examples demonstrate how to get data for one area of interest, or population (e.g, Bighorn National Forest) and for one area of interest, with multiple estimation units, or subpopulations (e.g., Bighorn National Forest Districts).
Bighorn National Forest
View Getting Strata Data
# File names for spatial layers, stored as external data objects in FIESTA.
WYbhfn <- system.file("extdata", "sp_data/WYbighorn_adminbnd.shp", package = "FIESTA")
fornffn <- system.file("extdata", "sp_data/WYbighorn_forest_nonforest_250m.tif", package = "FIESTA")
# Get estimation unit and strata information for Bighorn National Forest.
stratdat.bh <-
spGetStrata(xyplt = WYplt,
uniqueid = "CN",
unit_layer = WYbhfn,
strat_layer = fornffn,
spMakeSpatial_opts = list(xvar = "LON_PUBLIC",
yvar = "LAT_PUBLIC",
xy.crs = 4269))
# Get names of output components
names(stratdat.bh)output
## [1] "bnd" "pltassgn" "pltassgnid" "unitarea" "unitvar"
## [6] "unitvar2" "areavar" "areaunits" "stratalut" "strvar"
## [11] "getwt" "strwtvar"output
## CN INVYR STATECD CYCLE UNITCD COUNTYCD PLOT MEASYEAR RDDISTCD
## 1 40404876010690 2012 56 3 2 3 83143 2012 6
## 2 40404879010690 2011 56 3 2 3 80153 2011 6
## 3 40404921010690 2013 56 3 2 3 85403 2013 NA
## 4 40404930010690 2012 56 3 2 3 89093 2012 8
## 5 40404939010690 2012 56 3 2 3 86981 2012 6
## 6 40404940010690 2013 56 3 2 3 85570 2013 8
## NF_SAMPLING_STATUS_CD PLOT_STATUS_CD NF_PLOT_STATUS_CD NBRCND NBRCNDSAMP
## 1 0 1 NA 2 2
## 2 0 1 NA 1 1
## 3 0 2 NA 1 1
## 4 0 1 NA 1 1
## 5 0 1 NA 2 2
## 6 0 1 NA 1 1
## NBRCNDFOR CCLIVEPLT FORNONSAMP PLOT_ID ONEUNIT STRATUMCD
## 1 2 67.5 Sampled-Forest ID560200383143 1 1
## 2 1 66.0 Sampled-Forest ID560200380153 1 1
## 3 0 0.0 Sampled-Nonforest ID560200385403 1 1
## 4 1 45.0 Sampled-Forest ID560200389093 1 1
## 5 1 54.0 Sampled-Forest ID560200386981 1 1
## 6 1 52.0 Sampled-Forest ID560200385570 1 1output
## ONEUNIT ACRES_GIS
## 1 1 1112401output
## ONEUNIT STRATUMCD P2POINTCNT strwt P1POINTCNT P1POINTCNTFOR
## 1 1 1 52289 0.7260344 41 33
## 2 1 2 19731 0.2739656 15 4output
## [1] "ONEUNIT"output
## [1] "STRATUMCD"output
## [1] "ACRES_GIS"Bighorn National Forest Districts
View Getting Strata Data (Districts)
# File names for external spatial data
WYbhdistfn <- system.file("extdata", "sp_data/WYbighorn_districtbnd.shp", package = "FIESTA")
fornffn <- system.file("extdata", "sp_data/WYbighorn_forest_nonforest_250m.tif", package = "FIESTA")
# Get estimation unit and strata information for Bighorn National Forest Districts
stratdat.bhdist <-
spGetStrata(xyplt = WYplt,
uniqueid = "CN",
unit_layer = WYbhdistfn,
unitvar = "DISTRICTNA",
strat_layer = fornffn,
spMakeSpatial_opts = list(xvar = "LON_PUBLIC",
yvar = "LAT_PUBLIC",
xy.crs = 4269))
# Get names of output list components
names(stratdat.bhdist)output
## [1] "bnd" "pltassgn" "pltassgnid" "unitarea" "unitvar"
## [6] "unitvar2" "areavar" "areaunits" "stratalut" "strvar"
## [11] "getwt" "strwtvar"# Plot assignment of strata and estimation unit (DISTRICTNA, STRATUMCD)
head(stratdat.bhdist$pltassgn)output
## CN INVYR STATECD CYCLE UNITCD COUNTYCD PLOT MEASYEAR RDDISTCD
## 1 40404876010690 2012 56 3 2 3 83143 2012 6
## 2 40404879010690 2011 56 3 2 3 80153 2011 6
## 3 40404921010690 2013 56 3 2 3 85403 2013 NA
## 4 40404930010690 2012 56 3 2 3 89093 2012 8
## 5 40404939010690 2012 56 3 2 3 86981 2012 6
## 6 40406947010690 2011 56 3 2 33 88166 2011 6
## NF_SAMPLING_STATUS_CD PLOT_STATUS_CD NF_PLOT_STATUS_CD NBRCND NBRCNDSAMP
## 1 0 1 NA 2 2
## 2 0 1 NA 1 1
## 3 0 2 NA 1 1
## 4 0 1 NA 1 1
## 5 0 1 NA 2 2
## 6 0 1 NA 3 2
## NBRCNDFOR CCLIVEPLT FORNONSAMP PLOT_ID
## 1 2 67.5 Sampled-Forest ID560200383143
## 2 1 66.0 Sampled-Forest ID560200380153
## 3 0 0.0 Sampled-Nonforest ID560200385403
## 4 1 45.0 Sampled-Forest ID560200389093
## 5 1 54.0 Sampled-Forest ID560200386981
## 6 1 14.0 Sampled-Forest ID560203388166
## DISTRICTNA STRATUMCD
## 1 Medicine Wheel Ranger District 1
## 2 Medicine Wheel Ranger District 1
## 3 Medicine Wheel Ranger District 1
## 4 Medicine Wheel Ranger District 1
## 5 Medicine Wheel Ranger District 1
## 6 Medicine Wheel Ranger District 1output
## DISTRICTNA ACRES_GIS
## 1 Medicine Wheel Ranger District 364522.8
## 2 Powder River Ranger District 334333.7
## 3 Tongue Ranger District 413774.9output
## DISTRICTNA STRATUMCD P2POINTCNT strwt P1POINTCNT
## 1 Medicine Wheel Ranger District 1 14472 0.6127789 9
## 2 Medicine Wheel Ranger District 2 9145 0.3872211 7
## 3 Powder River Ranger District 1 15251 0.7044667 13
## 4 Powder River Ranger District 2 6398 0.2955333 6
## 5 Tongue Ranger District 1 22588 0.8437804 19
## 6 Tongue Ranger District 2 4182 0.1562196 2
## P1POINTCNTFOR
## 1 8
## 2 3
## 3 9
## 4 0
## 5 16
## 6 1output
## [1] "DISTRICTNA"output
## [1] "STRATUMCD"output
## [1] "ACRES_GIS"modGBpop()
FIESTA’s population functions (mod*pop)
check input data and perform population-level calculations, such as:
summing number of sampled plots; adjusting for partial nonresponse; and
standardizing auxiliary data. These functions are specific to each
FIESTA module and are run prior to or within a module for
any population of interest.
For FIESTA’s GB Module, the modGBpop
function calculates and outputs: number of plots, adjustment factors,
and an expansion factor by strata. The outputs are similar to data found
in FIADB’s pop_stratum table. The output from modGBpop can
be used for one or more estimates from modGBarea,
modGBtree, or modGBratio functions.
POP1: FIADB POPULATION - Get population data for post-stratified area and tree estimates for Wyoming
View Example
In this example, we use the sample Wyoming data (2013 Evaluation)
stored in FIESTA to generate population data for the GB
module. We check this output with the FIADB pop_stratum table from FIA
DataMart for 561301 Evalid, using the FIESTA::DBqryCSV
function.
GBpopdat <-
modGBpop(popTabs = list(cond = FIESTA::WYcond, # FIA plot/condition data
tree = FIESTA::WYtree, # FIA tree data
seed = FIESTA::WYseed), # FIA seedling data
popTabIDs = list(cond = "PLT_CN"), # unique ID of plot in cond
pltassgn = FIESTA::WYpltassgn, # plot assignments
pltassgnid = "CN", # unique ID of plot in pltassgn
pjoinid = "PLT_CN", # plot id to join to pltassgn
unitarea = FIESTA::WYunitarea, # area by estimation units
unitvar = "ESTN_UNIT", # name of estimation unit variable
strata = TRUE, # if using post-stratification
stratalut = FIESTA::WYstratalut, # strata classes and pixels counts
strata_opts = strata_options(getwt = TRUE)) # strata optionsTo get the names of the list components associated with the output of
our call of modGBpop, we run the following code:
output
## [1] "module" "popType" "popdatindb" "pltidsadj"
## [5] "pltcondx" "pltflds" "condflds" "pjoinid"
## [9] "cuniqueid" "condid" "ACI" "areawt"
## [13] "areawt2" "adjcase" "dbqueries" "dbqueriesWITH"
## [17] "pltassgnx" "pltassgnid" "unitarea" "areavar"
## [21] "areaunits" "unitvar" "unitvars" "unitltmin"
## [25] "unit.action" "strata" "stratalut" "strvar"
## [29] "strwtvar" "plotsampcnt" "condsampcnt" "states"
## [33] "invyrs" "adj" "P2POINTCNT" "plotunitcnt"
## [37] "treex" "tuniqueid" "treeflds" "seedx"
## [41] "suniqueid" "adjfactors" "adjvarlst" "pop_datsource"From this list outputted by GBpopdat we can access many
things. Some examples include the number of plots by plot status
(plotsampcnt), the number of conditions by condition status
(condsampcnt), the number of plots and adjustment factors
by strata (stratalut), and the adjustment factors added to
the plot-level, tree-level, and seedling data (pltidsadj,
treex, and seedx). These objects can be seen
below:
output
## data frame with 0 columns and 0 rowsoutput
## COND_STATUS_NM COND_STATUS_CD NBRCONDS
## 1 Nonforest land 2 2590
## 2 Forest land 1 590
## 3 Noncensus water 3 10
## 4 Nonsampled 5 14
## 5 Census water 4 20output
## Key: <ESTN_UNIT, STRATUMCD>
## ESTN_UNIT STRATUMCD P1POINTCNT n.total n.strata strwt EXPNS
## <fctr> <num> <num> <int> <int> <num> <num>
## 1: 1 1 30603 133 17 0.17138393 27800.62
## 2: 1 2 147961 133 116 0.82861607 19698.30
## 3: 3 1 15896 98 12 0.12145384 20462.23
## 4: 3 2 114985 98 86 0.87854616 20653.28
## 5: 5 2 198981 152 152 1.00000000 20217.03
## 6: 7 1 50473 245 35 0.15293736 22271.87
## 7: 7 2 279551 245 210 0.84706264 20559.25
## 8: 9 1 13946 133 16 0.07891401 13462.99
## 9: 9 2 162778 133 117 0.92108599 21489.27
## 10: 11 1 34965 85 28 0.29395692 19286.98
## 11: 11 2 83981 85 57 0.70604308 22755.94
## 12: 13 1 60592 290 48 0.15780564 19495.86
## 13: 13 2 323374 290 242 0.84219436 20637.55
## 14: 15 2 92483 70 70 1.00000000 20408.27
## 15: 17 2 83149 58 58 1.00000000 22137.40
## 16: 19 1 24652 128 18 0.14250699 21152.80
## 17: 19 2 148336 128 110 0.85749301 20827.74
## 18: 21 2 111389 86 86 1.00000000 20000.86
## 19: 23 1 49359 132 35 0.29129978 21780.52
## 20: 23 2 120085 132 97 0.70870022 19119.96
## 21: 25 2 222755 175 175 1.00000000 19659.69
## 22: 27 2 108902 79 79 1.00000000 21289.23
## 23: 29 1 140049 216 100 0.48499131 21629.77
## 24: 29 2 148717 216 116 0.51500869 19800.42
## 25: 31 2 87474 64 64 1.00000000 21108.89
## 26: 33 1 24037 82 18 0.22951399 20622.06
## 27: 33 2 80693 82 64 0.77048601 19470.64
## 28: 35 1 55527 158 44 0.27151107 19492.07
## 29: 35 2 148984 158 114 0.72848893 20185.58
## 30: 37 2 434729 339 339 1.00000000 19806.25
## 31: 39 1 128994 125 98 0.73730659 20328.15
## 32: 39 2 45959 125 27 0.26269341 26288.23
## 33: 41 2 86508 63 63 1.00000000 21206.89
## 34: 43 2 92938 63 63 1.00000000 22783.37
## 35: 45 2 99461 73 73 1.00000000 21041.62
## ESTN_UNIT STRATUMCD P1POINTCNT n.total n.strata strwt EXPNS
## <fctr> <num> <num> <int> <int> <num> <num>output
## Key: <CN>
## CN ADJ_FACTOR_COND ADJ_FACTOR_SUBP ADJ_FACTOR_MACR
## <char> <num> <num> <int>
## 1: 40404728010690 1.000000 1.000000 0
## 2: 40404729010690 1.000000 1.000000 0
## 3: 40404730010690 1.014925 1.014925 0
## 4: 40404731010690 1.000000 1.000000 0
## 5: 40404733010690 1.000000 1.000000 0
## 6: 40404734010690 1.000000 1.000000 0
## ADJ_FACTOR_MICR
## <num>
## 1: 1.000000
## 2: 1.000000
## 3: 1.014925
## 4: 1.000000
## 5: 1.000000
## 6: 1.000000output
## Key: <PLT_CN, CONDID, SUBP, TREE>
## PLT_CN CONDID SUBP TREE STATUSCD SPCD SPGRPCD DIA HT
## <char> <num> <num> <num> <num> <num> <num> <num> <num>
## 1: 40404729010690 1 1 1 2 113 24 7.7 18
## 2: 40404729010690 1 1 2 1 66 23 10.8 14
## 3: 40404729010690 1 1 3 2 113 24 5.2 23
## 4: 40404729010690 1 1 4 1 113 24 5.2 18
## 5: 40404729010690 1 3 1 1 113 24 8.8 21
## 6: 40404729010690 1 4 1 1 113 24 8.9 28
## TREECLCD AGENTCD STANDING_DEAD_CD VOLCFNET VOLCFGRS VOLBFNET TPA_UNADJ
## <num> <num> <num> <num> <num> <num> <num>
## 1: 3 10 1 1.001201 1.820365 NA 6.018046
## 2: 3 NA NA NA NA NA 6.018046
## 3: 3 10 1 0.466414 0.848025 NA 6.018046
## 4: 2 NA NA 0.630180 0.630180 NA 6.018046
## 5: 3 NA NA 2.491559 2.931246 NA 6.018046
## 6: 3 NA NA 3.824139 4.202350 NA 6.018046
## DRYBIO_AG CARBON_AG tadjfac
## <num> <num> <num>
## 1: 68.32740 34.43701 1
## 2: 128.28703 61.19291 1
## 3: 40.24585 20.28391 1
## 4: 40.61207 19.49379 1
## 5: 144.25115 69.24055 1
## 6: 182.53588 87.61722 1output
## Key: <PLT_CN, CONDID, SUBP>
## PLT_CN SUBP CONDID SPCD SPGRPCD TPA_UNADJ TREECOUNT
## <char> <num> <num> <num> <num> <num> <num>
## 1: 40404729010690 2 1 113 24 74.96528 1
## 2: 40404730010690 2 1 202 10 224.89585 3
## 3: 40404738010690 2 1 746 44 2323.92376 31
## 4: 40404738010690 4 1 19 12 74.96528 1
## 5: 40404738010690 4 1 113 24 74.96528 1
## 6: 40404742010690 4 1 746 44 1124.47924 15
## TREECOUNT_CALC tadjfac
## <num> <num>
## 1: 1 1.000000
## 2: 3 1.014925
## 3: 31 1.014925
## 4: 1 1.014925
## 5: 1 1.014925
## 6: 15 1.014925POP2: CUSTOM POPULATION - Get population data for post-stratified area and tree estimates for the Bighorn National Forest
View Example
In this example, we use the sample WY plot data (2013 Evaluation) in
FIESTA and output from spGetStrata to generate population
data for the Bighorn National Forest. Here, we have only one estimation
unit within the population of interest (Bighorn National Forest),
therefore strata and pixel counts are summarized to the population.
If the FIESTA::spGetStrata function is used to obtain
stratification data, the output list object can be input directly into
modGBpop through the stratdat parameter.
GBpopdat.bh <-
modGBpop(popTabs = popTables(plt = WYplt,
cond = WYcond,
tree = WYtree,
seed = WYseed),
stratdat = stratdat.bh)
# Get names of output list components
names(GBpopdat.bh)output
## [1] "module" "popType" "popdatindb" "pltidsadj"
## [5] "pltcondx" "pltflds" "condflds" "pjoinid"
## [9] "cuniqueid" "condid" "ACI" "areawt"
## [13] "areawt2" "adjcase" "dbqueries" "dbqueriesWITH"
## [17] "pltassgnx" "pltassgnid" "unitarea" "areavar"
## [21] "areaunits" "unitvar" "unitvars" "unitltmin"
## [25] "unit.action" "strata" "stratalut" "strvar"
## [29] "strwtvar" "plotsampcnt" "condsampcnt" "states"
## [33] "invyrs" "adj" "P2POINTCNT" "plotunitcnt"
## [37] "treex" "tuniqueid" "treeflds" "seedx"
## [41] "suniqueid" "adjfactors" "adjvarlst" "pop_datsource"The utilization of the stratdat parameter shown above is
simply a shortcut that is available when spGetStrata() was
used. Alternatively, the data can be input through individual parameters
as shown below.
## Using output as individual parameter inputs
GBpopdat.bh <-
modGBpop(popTabs = popTables(plt = WYplt,
cond = WYcond,
tree = WYtree,
seed = WYseed),
popTabIDs = popTableIDs(plt = "CN"),
pltassgn = stratdat.bh$pltassgn,
pltassgnid = "CN",
unitvar = stratdat.bh$unitvar,
unitarea = stratdat.bh$unitarea,
areavar = stratdat.bh$areavar,
strata = TRUE,
stratalut =stratdat.bh$stratalut,
strvar = stratdat.bh$strvar)
## Get names of output list components
names(GBpopdat.bh)output
## [1] "module" "popType" "popdatindb" "pltidsadj"
## [5] "pltcondx" "pltflds" "condflds" "pjoinid"
## [9] "cuniqueid" "condid" "ACI" "areawt"
## [13] "areawt2" "adjcase" "dbqueries" "dbqueriesWITH"
## [17] "pltassgnx" "pltassgnid" "unitarea" "areavar"
## [21] "areaunits" "unitvar" "unitvars" "unitltmin"
## [25] "unit.action" "strata" "stratalut" "strvar"
## [29] "strwtvar" "plotsampcnt" "condsampcnt" "states"
## [33] "invyrs" "adj" "P2POINTCNT" "plotunitcnt"
## [37] "treex" "tuniqueid" "treeflds" "seedx"
## [41] "suniqueid" "adjfactors" "adjvarlst" "pop_datsource"POP3: CUSTOM SUB-POPULATIONS - Get sub-population data for area and tree estimates for the Bighorn National Forest Districts, using post-stratification
View Example
In this example, we use the sample Wyoming plot data (2013
Evaluation) stored in FIESTA and output from spGetStrata to
generate sub-population data for Bighorn National Forest Districts.
Here, we have more than one estimation unit (i.e., sub-population)
within the population of interest (i.e., Bighorn National Forest
Districts), therefore strata and pixel counts are summarized by each
District within the population.
# Bighorn National Forest District
# Using output list from spGetStrata()
GBpopdat.bhdist <-
modGBpop(popTabs = popTables(plt = WYplt,
cond = WYcond,
tree = WYtree,
seed = WYseed),
stratdat = stratdat.bhdist)
## Get names of output list components
names(GBpopdat.bhdist)output
## [1] "module" "popType" "popdatindb" "pltidsadj"
## [5] "pltcondx" "pltflds" "condflds" "pjoinid"
## [9] "cuniqueid" "condid" "ACI" "areawt"
## [13] "areawt2" "adjcase" "dbqueries" "dbqueriesWITH"
## [17] "pltassgnx" "pltassgnid" "unitarea" "areavar"
## [21] "areaunits" "unitvar" "unitvars" "unitltmin"
## [25] "unit.action" "strata" "stratalut" "strvar"
## [29] "strwtvar" "plotsampcnt" "condsampcnt" "states"
## [33] "invyrs" "adj" "P2POINTCNT" "plotunitcnt"
## [37] "treex" "tuniqueid" "treeflds" "seedx"
## [41] "suniqueid" "adjfactors" "adjvarlst" "pop_datsource"POP4: FIADB POPULATION - Get population data for area and tree estimates for Rhode Island, using post-stratification, with data stored in a SQLite database
View Example
In this example, we use the sample Rhode Island data (441901
Evaluation) stored in a SQLite database as external data in
FIESTA. Data were extracted from the FIA database on June
6, 2022. All output can be compared with output from other FIA
tools.
First, let’s look at the SQLite database. Use the DBI package explore the contents.
SQLitefn <- system.file("extdata", "FIA_data/RIdat_eval2019.db", package="FIESTA")
conn <- DBI::dbConnect(RSQLite::SQLite(), SQLitefn)
DBI::dbListTables(conn)
DBI::dbDisconnect(conn)GBpopdat.RI <-
modGBpop(popTabs = popTables(plt = "plot",
cond = "cond",
tree = "tree",
seed = "seed"),
datsource = "sqlite",
dsn = SQLitefn,
pltassgn = "pop_plot_stratum_assgn",
stratalut = "pop_stratum",
unitarea = "pop_estn_unit",
unitvar = "ESTN_UNIT",
areavar = "AREA_USED",
strata_opts = strata_options(getwt = TRUE,
getwtvar = "P1POINTCNT"))
names(GBpopdat.RI)
# Strata-level population data, including number of plots and adjustment factors
GBpopdat.RI$stratalut modGBarea()
FIESTA‘s modGBarea function generates acre
estimates. Calculations are based on Scott et al. 2015 (’Green-Book’)
for mapped forest inventory plots. The non-ratio estimator for
estimating area by stratum and domain is used. Plots that are totally
nonsampled are excluded from the estimation dataset. Next, an adjustment
factor is calculated by strata to adjust for nonsampled (nonresponse)
conditions that have proportion less than 1. The attribute is the
proportion of the plot which is divided by the adjustment factor, and
averaged by stratum. Strata means are combined using the strata weights
and then expanded to acres using the total land area in the
population.
If there are more than one estimation unit (i.e., subpopulation)
within the population, estimates are generated by estimation unit. If
sumunits=TRUE, the estimates and percent standard errors
returned are a sum combination of all estimation units. If
rawdata=TRUE, the raw data returned will include estimates
by estimation unit.
Parameters defined in the following examples are organized by category: population data (pop); estimation information (est); and output details (out).
POP1: 1.1 Area of forest land, Wyoming, 2011-2013
View Example
Using the modGBarea function we generate estimates by
estimation unit (i.e., ESTN_UNIT) and sum to population (i.e., WY).
FIESTA then returns raw data for area of forest land,
Wyoming, 2011-2013 (sum estimation units).
The following estimates match output from EVALIDator using the WY 2013 Evaluation.
To get the names of the list components associated with the output of
our call of modGBarea, we run the following code:
output
## [1] "est" "raw" "statecd" "states" "invyr"To easily access our estimate and percent sampling error of estimate
we can just grab the est object from out outputted
list:
output
## TOTAL Estimate Percent Sampling Error
## 1 Total 10455772 2.37We can also look at raw data and estimates, as shown below:
output
## [1] "unit_totest" "totest" "domdat" "domdatqry" "module"
## [6] "esttype" "popType" "GBmethod" "rowvar" "colvar"
## [11] "areaunits"output
## ESTN_UNIT nhat nhat.var NBRPLT.gt0 AREAUSED est est.var
## 1 1 0.20844715 4.226522e-04 24 2757613 574816.6 3214028956
## 12 3 0.10668695 4.474630e-04 12 2021729 215692.1 1828954833
## 21 5 0.06743421 3.592846e-04 14 3072988 207224.5 3392815857
## 22 7 0.14429591 7.611799e-05 36 5096959 735470.3 1977468570
## 23 9 0.09134873 2.718698e-04 18 2729653 249350.3 2025703496
## 2 11 0.25385133 5.556666e-04 26 1837124 466356.4 1875388511
## est.se est.cv pse CI99left CI99right CI95left CI95right
## 1 56692.41 0.09862695 9.862695 428786.60 720846.5 463701.49 685931.6
## 12 42766.28 0.19827468 19.827468 105533.46 325850.7 131871.73 299512.5
## 21 58247.88 0.28108586 28.108586 57187.92 357261.1 93060.77 321388.3
## 22 44468.74 0.06046299 6.046299 620926.45 850014.2 648313.21 822627.5
## 23 45007.82 0.18050032 18.050032 133417.88 365282.8 161136.63 337564.0
## 2 43305.76 0.09285979 9.285979 354808.14 577904.6 381478.66 551234.1
## CI68left CI68right NBRPLT
## 1 518438.4 631194.8 133
## 12 173162.8 258221.4 98
## 21 149299.5 265149.6 152
## 22 691248.0 779692.6 245
## 23 204592.0 294108.7 133
## 2 423290.6 509422.1 85output
## TOTAL est est.var NBRPLT.gt0 AREAUSED est.se est.cv pse
## 1 1 10455771 61379281561 556 62600430 247748.4 0.0236949 2.36949
## CI99left CI99right CI95left CI95right CI68left CI68right NBRPLT
## 1 9817614 11093929 9970194 10941349 10209396 10702147 3047POP1: 1.2 Area by forest type on forest land, Wyoming, 2011-2013
View Example
In this example, we look at adding rows to the output and include
returntitle=TRUE to return title information. We use the
variable rowvar to specify a domain whose levels we want to
calculate estimates by.
## Area of forest land by forest type, Wyoming, 2011-2013
area1.2 <-
modGBarea(GBpopdat = GBpopdat,
landarea = "FOREST", # est - forest land filter
rowvar = "FORTYPCD", # est - row domain
sumunits = TRUE, # est - sum estimation units to population
returntitle = TRUE) # out - return title informationAgain, we can look at the contents of the output list. The output now includes titlelst, a list of associated titles.
output
## [1] "est" "titlelst" "raw" "statecd" "states" "invyr"And the estimates:
output
## Forest type Estimate Percent Sampling Error
## 1 182 632481.7 17.28
## 2 184 339749.8 23.85
## 3 185 14854.7 100
## 4 201 881189 14.21
## 5 221 889542.8 12.82
## 6 265 467196.7 19.99
## 7 266 1521792.8 10.41
## 8 268 950041.6 13.55
## 9 269 19120 101.99
## 10 281 2483772.2 7.79
## 11 366 236355.9 28.47
## 12 367 362502.8 22.36
## 13 509 95082.1 45.29
## 14 517 19287 107.34
## 15 703 87991.9 44.35
## 16 706 10593.4 100
## 17 901 617017 17.39
## 18 999 827200.1 14.62
## 19 Total 10455771.5 2.37Along with raw data and titles:
output
## [1] "unit_totest" "totest" "unit_rowest" "rowest" "domdat"
## [6] "domdatqry" "module" "esttype" "popType" "GBmethod"
## [11] "rowvar" "colvar" "areaunits"output
## ESTN_UNIT nhat nhat.var NBRPLT.gt0 AREAUSED est est.var
## 1 1 0.20844715 4.226522e-04 24 2757613 574816.6 3214028956
## 12 3 0.10668695 4.474630e-04 12 2021729 215692.1 1828954833
## 21 5 0.06743421 3.592846e-04 14 3072988 207224.5 3392815857
## 22 7 0.14429591 7.611799e-05 36 5096959 735470.3 1977468570
## 23 9 0.09134873 2.718698e-04 18 2729653 249350.3 2025703496
## 2 11 0.25385133 5.556666e-04 26 1837124 466356.4 1875388511
## est.se est.cv pse CI99left CI99right CI95left CI95right
## 1 56692.41 0.09862695 9.862695 428786.60 720846.5 463701.49 685931.6
## 12 42766.28 0.19827468 19.827468 105533.46 325850.7 131871.73 299512.5
## 21 58247.88 0.28108586 28.108586 57187.92 357261.1 93060.77 321388.3
## 22 44468.74 0.06046299 6.046299 620926.45 850014.2 648313.21 822627.5
## 23 45007.82 0.18050032 18.050032 133417.88 365282.8 161136.63 337564.0
## 2 43305.76 0.09285979 9.285979 354808.14 577904.6 381478.66 551234.1
## CI68left CI68right NBRPLT
## 1 518438.4 631194.8 133
## 12 173162.8 258221.4 98
## 21 149299.5 265149.6 152
## 22 691248.0 779692.6 245
## 23 204592.0 294108.7 133
## 2 423290.6 509422.1 85output
## TOTAL est est.var NBRPLT.gt0 AREAUSED est.se est.cv pse
## 1 1 10455771 61379281561 556 62600430 247748.4 0.0236949 2.36949
## CI99left CI99right CI95left CI95right CI68left CI68right NBRPLT
## 1 9817614 11093929 9970194 10941349 10209396 10702147 3047output
## ESTN_UNIT Forest type nhat nhat.var NBRPLT.gt0 AREAUSED est
## 1 1 182 0.01428648 0.0001066487 2 2757613 39396.59
## 2 1 201 0.01023188 0.0000809180 1 2757613 28215.56
## 3 1 221 0.03239380 0.0002137597 4 2757613 89329.58
## 4 1 266 0.04092751 0.0002629835 4 2757613 112862.22
## 5 1 268 0.01023188 0.0000809180 1 2757613 28215.56
## 6 1 281 0.03854903 0.0002367898 4 2757613 106303.32
## est.var est.se est.cv pse CI99left CI99right CI95left CI95right
## 1 811002553 28478.11 0.7228571 72.28571 0 112751.34 0.00 95212.66
## 2 615335251 24805.95 0.8791587 87.91587 0 92111.45 0.00 76834.33
## 3 1625520387 40317.74 0.4513370 45.13370 0 193181.20 10308.25 168350.90
## 4 1999839565 44719.57 0.3962315 39.62315 0 228052.19 25213.48 200510.96
## 5 615335251 24805.95 0.8791587 87.91587 0 92111.45 0.00 76834.33
## 6 1800651626 42434.09 0.3991793 39.91793 0 215606.28 23134.04 189472.60
## CI68left CI68right
## 1 11076.316 67716.87
## 2 3547.081 52884.03
## 3 49235.278 129423.87
## 4 68390.497 157333.95
## 5 3547.081 52884.03
## 6 64104.407 148502.23output
## Forest type est est.var NBRPLT.gt0 est.se est.cv pse
## 1 182 632481.70 11940316027 36 109271.75 0.1727667 17.27667
## 2 184 339749.83 6565509067 18 81027.83 0.2384926 23.84926
## 3 185 14854.69 220661757 1 14854.69 1.0000000 100.00000
## 4 201 881188.96 15674351133 47 125197.25 0.1420776 14.20776
## 5 221 889542.77 13008784420 51 114056.06 0.1282187 12.82187
## 6 265 467196.69 8723584461 27 93400.13 0.1999161 19.99161
## CI99left CI99right CI95left CI95right CI68left CI68right
## 1 351016.3 913947.08 418313.0 846650.40 523815.54425 741147.86
## 2 131036.0 548463.69 180938.2 498561.46 259171.07046 420328.60
## 3 0.0 53117.83 0.0 43969.34 82.32642 29627.05
## 4 558702.2 1203675.70 635806.9 1126571.06 756685.57030 1005692.35
## 5 595753.8 1183331.71 665997.0 1113088.54 776118.82419 1002966.72
## 6 226613.9 707779.49 284135.8 650257.59 374314.19798 560079.19output
## [1] "title.estpse" "title.unitvar" "title.ref" "outfn.estpse"
## [5] "outfn.rawdat" "outfn.param" "title.rowvar" "title.row"
## [9] "title.unit"output
## $title.estpse
## [1] "Area, in acres, and percent sampling error on forest land by forest type"
##
## $title.unitvar
## [1] "ESTN_UNIT"
##
## $title.ref
## [1] "Wyoming, 2011-2013"
##
## $outfn.estpse
## [1] "area_FORTYPCD_forestland"
##
## $outfn.rawdat
## [1] "area_FORTYPCD_forestland_rawdata"
##
## $outfn.param
## [1] "area_FORTYPCD_forestland_parameters"
##
## $title.rowvar
## [1] "Forest type"
##
## $title.row
## [1] "Area, in acres, on forest land by forest type; Wyoming, 2011-2013"
##
## $title.unit
## [1] "acres"POP1: 1.3 Area by forest type and stand-size class on forest land, Wyoming, 2011-2013
View Example
In this example, we look at generating estimates by multiple domains.
In order to enhance the readability of the output we use FIA names as
labels. We also output estimates and percent standard error in the same
cell with the allin1 argument in table_options
and save data to an outfolder with the outfolder argument
in savedata_options.
## Area of forest land by forest type and stand-size class, Wyoming, 2011-2013
area1.3 <-
modGBarea(GBpopdat = GBpopdat, # pop - population calculations for WY, post-stratification
landarea = "FOREST", # est - forest land filter
rowvar = "FORTYPCD", # est - row domain
colvar = "STDSZCD", # est - column domain
sumunits = TRUE, # est - sum estimation units to population
savedata = TRUE, # out - save data to outfolder
returntitle = TRUE, # out - return title information
table_opts = table_options(row.FIAname = TRUE, # table - row domain names
col.FIAname = TRUE, # table - column domain names
allin1 = TRUE), # table - return output with est(pse)
savedata_opts = savedata_options(outfolder = outfolder, # save - outfolder for saving data
outfn.pre = "WY")) # save - prefix for output filesWe can again look at the output list, estimates, raw data, and titles:
output
## [1] "est" "titlelst" "raw" "statecd" "states" "invyr"output
## Forest type Large diameter Medium diameter
## 1 Rocky Mountain juniper 477,452.6 ( 19.91) 63,177.6 ( 51.17)
## 2 Juniper woodland 317,612.4 ( 24.54) -- ( --)
## 3 Pinyon / juniper woodland 14,854.7 (100.00) -- ( --)
## 4 Douglas-fir 589,713.2 ( 17.41) 111,576.9 ( 41.36)
## 5 Ponderosa pine 786,751.8 ( 13.52) 46,720.3 ( 60.51)
## 6 Engelmann spruce 332,893.7 ( 24.00) 68,400.6 ( 54.85)
## Small diameter Nonstocked Total
## 1 91,851.5 ( 46.14) -- ( --) 632,481.7 ( 17.28)
## 2 22,137.4 (100.00) -- ( --) 339,749.8 ( 23.85)
## 3 -- ( --) -- ( --) 14,854.7 (100.00)
## 4 179,898.8 ( 31.91) -- ( --) 881,189.0 ( 14.21)
## 5 56,070.7 ( 58.39) -- ( --) 889,542.8 ( 12.82)
## 6 65,902.4 ( 50.88) -- ( --) 467,196.7 ( 19.99)# Raw data (list object) for estimate
raw1.3 <- area1.3$raw # extract raw data list object from output
names(raw1.3)output
## [1] "unit_totest" "totest" "unit_rowest" "rowest" "unit_colest"
## [6] "colest" "unit_grpest" "grpest" "domdat" "domdatqry"
## [11] "module" "esttype" "popType" "GBmethod" "rowvar"
## [16] "colvar" "areaunits"output
## ESTN_UNIT nhat nhat.var NBRPLT.gt0 AREAUSED est est.var
## 1 1 0.20844715 4.226522e-04 24 2757613 574816.6 3214028956
## 12 3 0.10668695 4.474630e-04 12 2021729 215692.1 1828954833
## 21 5 0.06743421 3.592846e-04 14 3072988 207224.5 3392815857
## 22 7 0.14429591 7.611799e-05 36 5096959 735470.3 1977468570
## 23 9 0.09134873 2.718698e-04 18 2729653 249350.3 2025703496
## 2 11 0.25385133 5.556666e-04 26 1837124 466356.4 1875388511
## est.se est.cv pse CI99left CI99right CI95left CI95right
## 1 56692.41 0.09862695 9.862695 428786.60 720846.5 463701.49 685931.6
## 12 42766.28 0.19827468 19.827468 105533.46 325850.7 131871.73 299512.5
## 21 58247.88 0.28108586 28.108586 57187.92 357261.1 93060.77 321388.3
## 22 44468.74 0.06046299 6.046299 620926.45 850014.2 648313.21 822627.5
## 23 45007.82 0.18050032 18.050032 133417.88 365282.8 161136.63 337564.0
## 2 43305.76 0.09285979 9.285979 354808.14 577904.6 381478.66 551234.1
## CI68left CI68right NBRPLT
## 1 518438.4 631194.8 133
## 12 173162.8 258221.4 98
## 21 149299.5 265149.6 152
## 22 691248.0 779692.6 245
## 23 204592.0 294108.7 133
## 2 423290.6 509422.1 85output
## TOTAL est est.var NBRPLT.gt0 AREAUSED est.se est.cv pse
## 1 1 10455771 61379281561 556 62600430 247748.4 0.0236949 2.36949
## CI99left CI99right CI95left CI95right CI68left CI68right NBRPLT
## 1 9817614 11093929 9970194 10941349 10209396 10702147 3047output
## ESTN_UNIT FORTYPCD Forest type nhat nhat.var
## 1 1 182 Rocky Mountain juniper 0.01428648 0.0001066487
## 2 1 201 Douglas-fir 0.01023188 0.0000809180
## 3 1 221 Ponderosa pine 0.03239380 0.0002137597
## 4 1 266 Engelmann spruce / subalpine fir 0.04092751 0.0002629835
## 5 1 268 Subalpine fir 0.01023188 0.0000809180
## 6 1 281 Lodgepole pine 0.03854903 0.0002367898
## NBRPLT.gt0 AREAUSED est est.var est.se est.cv pse CI99left
## 1 2 2757613 39396.59 811002553 28478.11 0.7228571 72.28571 0
## 2 1 2757613 28215.56 615335251 24805.95 0.8791587 87.91587 0
## 3 4 2757613 89329.58 1625520387 40317.74 0.4513370 45.13370 0
## 4 4 2757613 112862.22 1999839565 44719.57 0.3962315 39.62315 0
## 5 1 2757613 28215.56 615335251 24805.95 0.8791587 87.91587 0
## 6 4 2757613 106303.32 1800651626 42434.09 0.3991793 39.91793 0
## CI99right CI95left CI95right CI68left CI68right
## 1 112751.34 0.00 95212.66 11076.316 67716.87
## 2 92111.45 0.00 76834.33 3547.081 52884.03
## 3 193181.20 10308.25 168350.90 49235.278 129423.87
## 4 228052.19 25213.48 200510.96 68390.497 157333.95
## 5 92111.45 0.00 76834.33 3547.081 52884.03
## 6 215606.28 23134.04 189472.60 64104.407 148502.23output
## Forest type FORTYPCD est est.var NBRPLT.gt0 est.se
## 1 Rocky Mountain juniper 182 632481.70 11940316027 36 109271.75
## 2 Juniper woodland 184 339749.83 6565509067 18 81027.83
## 3 Pinyon / juniper woodland 185 14854.69 220661757 1 14854.69
## 4 Douglas-fir 201 881188.96 15674351133 47 125197.25
## 5 Ponderosa pine 221 889542.77 13008784420 51 114056.06
## 6 Engelmann spruce 265 467196.69 8723584461 27 93400.13
## est.cv pse CI99left CI99right CI95left CI95right CI68left
## 1 0.1727667 17.27667 351016.3 913947.08 418313.0 846650.40 523815.54425
## 2 0.2384926 23.84926 131036.0 548463.69 180938.2 498561.46 259171.07046
## 3 1.0000000 100.00000 0.0 53117.83 0.0 43969.34 82.32642
## 4 0.1420776 14.20776 558702.2 1203675.70 635806.9 1126571.06 756685.57030
## 5 0.1282187 12.82187 595753.8 1183331.71 665997.0 1113088.54 776118.82419
## 6 0.1999161 19.99161 226613.9 707779.49 284135.8 650257.59 374314.19798
## CI68right
## 1 741147.86
## 2 420328.60
## 3 29627.05
## 4 1005692.35
## 5 1002966.72
## 6 560079.19output
## ESTN_UNIT STDSZCD Stand-size class nhat nhat.var NBRPLT.gt0
## 1 1 1 Large diameter 0.077375917 4.560626e-04 9
## 2 1 2 Medium diameter 0.061391258 3.337868e-04 6
## 3 1 3 Small diameter 0.059978760 3.953596e-04 7
## 4 1 5 Nonstocked 0.009701211 5.884949e-05 2
## 5 3 1 Large diameter 0.083776075 4.661326e-04 9
## 6 3 2 Medium diameter 0.007729145 5.975619e-05 1
## AREAUSED est est.var est.se est.cv pse CI99left CI99right
## 1 2757613 213372.84 3468095619 58890.54 0.2759983 27.59983 61680.86 365064.81
## 2 2757613 169293.33 2538257910 50381.13 0.2975966 29.75966 39520.15 299066.51
## 3 2757613 165398.21 3006484369 54831.42 0.3315116 33.15116 24161.84 306634.58
## 4 2757613 26752.19 447516758 21154.59 0.7907613 79.07613 0.00 81242.80
## 5 2021729 169372.52 1905264791 43649.34 0.2577120 25.77120 56939.27 281805.77
## 6 2021729 15626.24 244246754 15628.40 1.0001382 100.01382 0.00 55882.32
## CI95left CI95right CI68left CI68right
## 1 97949.50 328796.17 154808.67452 271937.00
## 2 70548.14 268038.53 119191.42369 219395.24
## 3 57930.61 272865.81 110870.67336 219925.74
## 4 0.00 68214.42 5714.83513 47789.54
## 5 83821.39 254923.65 125965.09125 212779.95
## 6 0.00 46257.33 84.45543 31168.02output
## Stand-size class STDSZCD est est.var NBRPLT.gt0 est.se est.cv
## 1 Large diameter 1 5344066.4 64292474661 297 253559.6 0.04744694
## 2 Medium diameter 2 1918907.4 30844444919 104 175625.9 0.09152389
## 3 Small diameter 3 2365597.5 39151933793 127 197868.5 0.08364419
## 4 Nonstocked 5 827200.1 14625718427 53 120936.8 0.14620022
## pse CI99left CI99right CI95left CI95right CI68left CI68right
## 1 4.744694 4690940.2 5997193 4847098.7 5841034 5091912.1 5596220.8
## 2 9.152389 1466525.2 2371290 1574687.1 2263128 1744254.9 2093560.0
## 3 8.364419 1855922.1 2875273 1977782.4 2753413 2168825.6 2562369.4
## 4 14.620022 515687.5 1138713 590168.3 1064232 706933.5 947466.7output
## ESTN_UNIT FORTYPCD Forest type STDSZCD Stand-size class
## 1 1 182 Rocky Mountain juniper 1 Large diameter
## 2 1 182 Rocky Mountain juniper 3 Small diameter
## 3 1 201 Douglas-fir 1 Large diameter
## 4 1 221 Ponderosa pine 1 Large diameter
## 5 1 266 Engelmann spruce / subalpine fir 1 Large diameter
## 6 1 266 Engelmann spruce / subalpine fir 2 Medium diameter
## nhat nhat.var NBRPLT.gt0 AREAUSED est est.var est.se
## 1 0.007143242 5.379211e-05 1 2757613 19698.30 409058305 20225.19
## 2 0.007143242 5.379211e-05 1 2757613 19698.30 409058305 20225.19
## 3 0.010231876 8.091800e-05 1 2757613 28215.56 615335251 24805.95
## 4 0.032393804 2.137597e-04 4 2757613 89329.58 1625520387 40317.74
## 5 0.020463753 1.517213e-04 2 2757613 56431.11 1153753595 33966.95
## 6 0.020463753 1.517213e-04 2 2757613 56431.11 1153753595 33966.95
## est.cv pse CI99left CI99right CI95left CI95right CI68left CI68right
## 1 1.0267481 102.67481 0 71794.93 0.00 59338.94 0.000 39811.40
## 2 1.0267481 102.67481 0 71794.93 0.00 59338.94 0.000 39811.40
## 3 0.8791587 87.91587 0 92111.45 0.00 76834.33 3547.081 52884.03
## 4 0.4513370 45.13370 0 193181.20 10308.25 168350.90 49235.278 129423.87
## 5 0.6019188 60.19188 0 143924.17 0.00 123005.11 22652.411 90209.81
## 6 0.6019188 60.19188 0 143924.17 0.00 123005.11 22652.411 90209.81output
## Forest type Stand-size class FORTYPCD STDSZCD est
## 1 Rocky Mountain juniper Large diameter 182 1 477452.63
## 2 Rocky Mountain juniper Medium diameter 182 2 63177.58
## 3 Rocky Mountain juniper Small diameter 182 3 91851.49
## 4 Juniper woodland Large diameter 184 1 317612.44
## 5 Juniper woodland Small diameter 184 3 22137.40
## 6 Pinyon / juniper woodland Large diameter 185 1 14854.69
## est.var NBRPLT.gt0 est.se est.cv pse CI99left CI99right
## 1 9035011628 28 95052.68 0.1990829 19.90829 232613.2 722292.11
## 2 1045063815 4 32327.45 0.5116918 51.16918 0.0 146447.56
## 3 1795723195 5 42375.97 0.4613532 46.13532 0.0 201004.76
## 4 6075444741 17 77945.14 0.2454096 24.54096 116839.1 518385.81
## 5 490064326 1 22137.40 1.0000000 100.00000 0.0 79159.55
## 6 220661757 1 14854.69 1.0000000 100.00000 0.0 53117.83
## CI95left CI95right CI68left CI68right
## 1 291152.806 663752.46 382926.74707 571978.52
## 2 0.000 126538.21 31029.29567 95325.86
## 3 8796.105 174906.87 49710.36671 133992.61
## 4 164842.771 470382.10 240099.27894 395125.60
## 5 0.000 65525.90 122.68804 44152.11
## 6 0.000 43969.34 82.32642 29627.05output
## [1] "title.estpse" "title.unitvar" "title.ref" "outfn.estpse"
## [5] "outfn.rawdat" "outfn.param" "title.rowvar" "title.row"
## [9] "title.colvar" "title.col" "title.unit"output
## $title.estpse
## [1] "Area, in acres (percent sampling error), by forest type and stand-size class on forest land"
##
## $title.unitvar
## [1] "ESTN_UNIT"
##
## $title.ref
## [1] "Wyoming, 2011-2013"
##
## $outfn.estpse
## [1] "WY_area_FORTYPCD_STDSZCD_forestland"
##
## $outfn.rawdat
## [1] "WY_area_FORTYPCD_STDSZCD_forestland_rawdata"
##
## $outfn.param
## [1] "WY_area_FORTYPCD_STDSZCD_forestland_parameters"
##
## $title.rowvar
## [1] "Forest type"
##
## $title.row
## [1] "Area, in acres (percent sampling error), by forest type on forest land; Wyoming, 2011-2013"
##
## $title.colvar
## [1] "Stand-size class"
##
## $title.col
## [1] "Area, in acres (percent sampling error), by stand-size class on forest land; Wyoming, 2011-2013"
##
## $title.unit
## [1] "acres"output
## [1] "WY_area_FORTYPCD_STDSZCD_forestland.csv"output
## [1] "WY_WY_area_FORTYPCD_STDSZCD_forestland_rawdata_colest.csv"
## [2] "WY_WY_area_FORTYPCD_STDSZCD_forestland_rawdata_domdat.csv"
## [3] "WY_WY_area_FORTYPCD_STDSZCD_forestland_rawdata_grpest.csv"
## [4] "WY_WY_area_FORTYPCD_STDSZCD_forestland_rawdata_rowest.csv"
## [5] "WY_WY_area_FORTYPCD_STDSZCD_forestland_rawdata_totest.csv"
## [6] "WY_WY_area_FORTYPCD_STDSZCD_forestland_rawdata_unit_colest.csv"
## [7] "WY_WY_area_FORTYPCD_STDSZCD_forestland_rawdata_unit_grpest.csv"
## [8] "WY_WY_area_FORTYPCD_STDSZCD_forestland_rawdata_unit_rowest.csv"
## [9] "WY_WY_area_FORTYPCD_STDSZCD_forestland_rawdata_unit_totest.csv"POP2: 2.1 Area by forest type and stand-size class, Bighorn National Forest
View Example
We now shift to producing estimates for the Bighorn National Forest.
In this example, we utilize the title_opts argument to
customize the title outputs.
area2.1 <-
modGBarea(GBpopdat = GBpopdat.bh, # pop - population calculations for Bighorn NF, post-stratification
landarea = "FOREST", # est - forest land filter
rowvar = "FORTYPCD", # est - row domain
colvar = "STDSZCD", # est - column domain
returntitle = TRUE, # out - return title information
title_opts = title_options(
title.ref = "Bighorn National Forest, 2011-2013"), # title - customize title reference
table_opts = table_options(row.FIAname = TRUE, # table - return FIA row names
col.FIAname = TRUE)) # table - return FIA column namesTo get the names of the list components associated with the output of
our call of modGBarea, we run the following code:
output
## [1] "est" "pse" "titlelst" "raw" "statecd" "states" "invyr"To easily access our estimate and percent sampling error of estimate
we can just grab the est object from our ouputted list:
output
## Forest type Large diameter Medium diameter
## 1 Douglas-fir 19819.4 --
## 2 Engelmann spruce 45091.6 19819.4
## 3 Engelmann spruce / subalpine fir 49548.6 9909.7
## 4 Subalpine fir 24774.3 --
## 5 Lodgepole pine 164008.2 203149.2
## 6 Aspen -- --
## 7 Nonstocked -- --
## 8 Total 303242.1 232878.3
## Small diameter Nonstocked Total
## 1 19819.4 -- 39638.9
## 2 -- -- 64911
## 3 9909.7 -- 69368
## 4 20317.3 -- 45091.6
## 5 40136.7 -- 407294.1
## 6 19819.4 -- 19819.4
## 7 -- 19819.4 19819.4
## 8 110002.6 19819.4 665942.4We can also look at raw data and titles for estimate, as shown below. Note the change in titles.
output
## [1] "unit_totest" "totest" "unit_rowest" "rowest" "unit_colest"
## [6] "colest" "unit_grpest" "grpest" "domdat" "domdatqry"
## [11] "module" "esttype" "popType" "GBmethod" "rowvar"
## [16] "colvar" "areaunits"output
## ONEUNIT FORTYPCD Forest type STDSZCD Stand-size class
## 1 1 201 Douglas-fir 1 Large diameter
## 2 1 201 Douglas-fir 3 Small diameter
## 3 1 265 Engelmann spruce 1 Large diameter
## 4 1 265 Engelmann spruce 2 Medium diameter
## 5 1 266 Engelmann spruce / subalpine fir 1 Large diameter
## 6 1 266 Engelmann spruce / subalpine fir 2 Medium diameter
## nhat nhat.var NBRPLT.gt0 AREAUSED est est.var est.se
## 1 0.017816796 3.222659e-04 1 1112401 19819.430 398783824 19969.572
## 2 0.017816796 3.222659e-04 1 1112401 19819.430 398783824 19969.572
## 3 0.040535366 6.799631e-04 3 1112401 45091.601 841411576 29007.095
## 4 0.017816796 3.222659e-04 1 1112401 19819.430 398783824 19969.572
## 5 0.044541990 6.928718e-04 3 1112401 49548.576 857385222 29281.141
## 6 0.008908398 8.056649e-05 1 1112401 9909.715 99695956 9984.786
## est.cv pse CI99left CI99right CI95left CI95right CI68left CI68right
## 1 1.0075755 100.75755 0 71257.64 0 58959.07 0.00 39678.33
## 2 1.0075755 100.75755 0 71257.64 0 58959.07 0.00 39678.33
## 3 0.6432926 64.32926 0 119808.93 0 101944.46 16245.27 73937.94
## 4 1.0075755 100.75755 0 71257.64 0 58959.07 0.00 39678.33
## 5 0.5909583 59.09583 0 124971.80 0 106938.56 20429.71 78667.44
## 6 1.0075755 100.75755 0 35628.82 0 29479.54 0.00 19839.16output
## [1] "title.est" "title.pse" "title.unitvar" "title.ref"
## [5] "outfn.estpse" "outfn.rawdat" "outfn.param" "title.rowvar"
## [9] "title.row" "title.colvar" "title.col" "title.unit"output
## $title.est
## [1] "Area, in acres, on forest land by forest type and stand-size class"
##
## $title.pse
## [1] "Percent sampling error of area, in acres, on forest land by forest type and stand-size class"
##
## $title.unitvar
## [1] "ONEUNIT"
##
## $title.ref
## [1] "Bighorn National Forest, 2011-2013"
##
## $outfn.estpse
## [1] "area_FORTYPCD_STDSZCD_forestland"
##
## $outfn.rawdat
## [1] "area_FORTYPCD_STDSZCD_forestland_rawdata"
##
## $outfn.param
## [1] "area_FORTYPCD_STDSZCD_forestland_parameters"
##
## $title.rowvar
## [1] "Forest type"
##
## $title.row
## [1] "Area, in acres, on forest land by forest type; Bighorn National Forest, 2011-2013"
##
## $title.colvar
## [1] "Stand-size class"
##
## $title.col
## [1] "Area, in acres, on forest land by stand-size class; Bighorn National Forest, 2011-2013"
##
## $title.unit
## [1] "acres"POP2: 2.2 Area by forest type group and primary disturbance class, Bighorn National Forest
View Example
Note: Since we only have one estimation unit within the population of interest, we set sumunits=FALSE. Let’s also add a few more table options to control the forest type groups displayed in the table (rowlut) and fill the NULL values with 0s (estnull).
area2.2 <-
modGBarea(GBpopdat = GBpopdat.bh, # pop - population calculations for Bighorn NF, post-stratification
landarea = "FOREST", # est - forest land filter
sumunits = TRUE, # est - sum estimation units to population
rowvar = "FORTYPGRPCD", # est - row domain
colvar = "DSTRBCD1", # est - column domain
returntitle = TRUE, # out - return title information
title_opts = title_options(
title.ref = "Bighorn National Forest, 2011-2013" # title - customize title reference
),
table_opts = table_options(row.FIAname = TRUE, # table - return FIA row names
col.FIAname = TRUE, # table - return FIA column names
estnull = 0,
rowlut = c(180, 200, 220, 260, 280, 900, 999),
raw.keep0 = TRUE)
)To get the names of the list components associated with the output of
our call of modGBarea, we run the following code:
output
## [1] "est" "pse" "titlelst" "raw" "statecd" "states" "invyr"To easily access our estimate and percent sampling error of estimate
we can just grab the est object from our ouputted list:
output
## Forest-type group No visible disturbance Disease Disease to trees Fire
## 1 180 0 0 0 0
## 2 200 39638.9 0 0 0
## 3 220 0 0 0 0
## 4 260 133781.2 4954.9 20317.3 20317.3
## 5 280 352292.8 35181.9 0 0
## 6 900 19819.4 0 0 0
## 7 999 19819.4 0 0 0
## 8 Total 565351.6 40136.7 20317.3 20317.3
## Wind Total
## 1 0 0.0
## 2 0 39638.9
## 3 0 0.0
## 4 0 179370.6
## 5 19819.4 407294.1
## 6 0 19819.4
## 7 0 19819.4
## 8 19819.4 665942.4We can also look at raw data and titles for estimate, as shown below. Note the change in titles.
## Raw data (list object) for estimate
raw2.2 <- area2.2$raw # extract raw data list object from output
names(raw2.2)output
## [1] "unit_totest" "totest" "unit_rowest" "rowest" "unit_colest"
## [6] "colest" "unit_grpest" "grpest" "domdat" "domdatqry"
## [11] "module" "esttype" "popType" "GBmethod" "rowvar"
## [16] "colvar" "areaunits"output
## ONEUNIT Forest-type group DSTRBCD1 Primary disturbance nhat
## 1 1 200 0 No visible disturbance 0.035633592
## 2 1 260 0 No visible disturbance 0.120263373
## 3 1 260 20 Disease 0.004454199
## 4 1 260 22 Disease to trees 0.018264371
## 5 1 260 30 Fire 0.018264371
## 6 1 280 0 No visible disturbance 0.316695703
## nhat.var NBRPLT.gt0 AREAUSED est est.var est.se est.cv
## 1 6.284186e-04 2 1112401 39638.860 777628457 27885.990 0.7035013
## 2 1.552919e-03 9 1112401 133781.154 1921639553 43836.509 0.3276733
## 3 2.014162e-05 1 1112401 4954.858 24923989 4992.393 1.0075755
## 4 3.415839e-04 1 1112401 20317.313 422688561 20559.391 1.0119148
## 5 3.415839e-04 1 1112401 20317.313 422688561 20559.391 1.0119148
## 6 3.345707e-03 20 1112401 352292.769 4140101523 64343.621 0.1826425
## pse CI99left CI99right CI95left CI95right CI68left CI68right
## 1 70.35013 0.00 111468.41 0.00 94294.40 11907.42 67370.303
## 2 32.76733 20865.79 246696.52 47863.17 219699.13 90187.59 177374.716
## 3 100.75755 0.00 17814.41 0.00 14739.77 0.00 9919.582
## 4 101.19148 0.00 73274.80 0.00 60612.98 0.00 40762.762
## 5 101.19148 0.00 73274.80 0.00 60612.98 0.00 40762.762
## 6 18.26425 186554.59 518030.95 226181.59 478403.95 288305.75 416279.790output
## [1] "title.est" "title.pse" "title.unitvar" "title.ref"
## [5] "outfn.estpse" "outfn.rawdat" "outfn.param" "title.rowvar"
## [9] "title.row" "title.colvar" "title.col" "title.unit"output
## $title.est
## [1] "Area, in acres, on forest land by forest-type group and primary disturbance"
##
## $title.pse
## [1] "Percent sampling error of area, in acres, on forest land by forest-type group and primary disturbance"
##
## $title.unitvar
## [1] "ONEUNIT"
##
## $title.ref
## [1] "Bighorn National Forest, 2011-2013"
##
## $outfn.estpse
## [1] "area_FORTYPGRPCD_DSTRBCD1_forestland"
##
## $outfn.rawdat
## [1] "area_FORTYPGRPCD_DSTRBCD1_forestland_rawdata"
##
## $outfn.param
## [1] "area_FORTYPGRPCD_DSTRBCD1_forestland_parameters"
##
## $title.rowvar
## [1] "Forest-type group"
##
## $title.row
## [1] "Area, in acres, on forest land by forest-type group; Bighorn National Forest, 2011-2013"
##
## $title.colvar
## [1] "Primary disturbance"
##
## $title.col
## [1] "Area, in acres, on forest land by primary disturbance; Bighorn National Forest, 2011-2013"
##
## $title.unit
## [1] "acres"POP3: 3.1 Area by forest type group and primary disturbance class, Bighorn National Forest Districts
View Example
In this example, we add a filter to remove instances where there is no visible disturbance from the table output. This filter does not change the population data set the estimates are derived from, it only changes the output.
area3.1 <-
modGBarea(GBpopdat = GBpopdat.bhdist, # pop - population calculations for Bighorn NF, post-stratification
landarea = "FOREST", # est - forest land filter
sumunits = TRUE, # est - sum estimation units to population
pcfilter = "DSTRBCD1 > 0", # est - condition filter for table output
rowvar = "FORTYPGRPCD", # est - row domain
colvar = "DSTRBCD1", # est - column domain
returntitle = TRUE, # out - return title information
title_opts = title_options(
title.ref = "Bighorn National Forest, 2011-2013" # title - customize title reference
),
table_opts = table_options(row.FIAname = TRUE, # table - return FIA row names
col.FIAname = TRUE) # table - return FIA column names
)To get the names of the list components associated with the output of
our call of modGBarea, we run the following code:
output
## [1] "est" "pse" "titlelst" "raw" "statecd" "states" "invyr"To easily access our estimate and percent sampling error of estimate
we can just grab the est object from our ouputted list:
output
## Forest-type group Disease Disease to trees Fire
## 1 Fir / spruce / mountain hemlock group 6382.1 20164.4 20164.4
## 2 Lodgepole pine group 39310.6 -- --
## 3 Total 45692.6 20164.4 20164.4
## Wind Total
## 1 -- 46710.9
## 2 18375.5 57686.1
## 3 18375.5 104397We can also look at raw data and titles for estimate, as shown below:
output
## [1] "unit_totest" "totest" "unit_rowest" "rowest" "unit_colest"
## [6] "colest" "unit_grpest" "grpest" "domdat" "domdatqry"
## [11] "module" "esttype" "popType" "GBmethod" "rowvar"
## [16] "colvar" "areaunits"output
## DISTRICTNA FORTYPGRPCD
## 1 Medicine Wheel Ranger District 260
## 2 Medicine Wheel Ranger District 280
## 3 Tongue Ranger District 280
## Forest-type group nhat nhat.var NBRPLT.gt0
## 1 Fir / spruce / mountain hemlock group 0.12814256 0.006624630 3
## 2 Lodgepole pine group 0.10784120 0.006431702 2
## 3 Lodgepole pine group 0.04440949 0.002133382 1
## AREAUSED est est.var est.se est.cv pse CI99left CI99right
## 1 364522.8 46710.89 880260198 29669.18 0.6351663 63.51663 0 123133.63
## 2 364522.8 39310.58 854624495 29233.96 0.7436665 74.36665 0 114612.27
## 3 413774.9 18375.53 365255577 19111.66 1.0400602 104.00602 0 67603.91
## CI95left CI95right CI68left CI68right
## 1 0 104861.41 17206.14 76215.64
## 2 0 96608.09 10238.64 68382.52
## 3 0 55833.70 0.00 37381.27output
## Forest-type group FORTYPGRPCD est est.var
## 1 Fir / spruce / mountain hemlock group 260 46710.89 880260198
## 2 Lodgepole pine group 280 57686.11 1219880072
## NBRPLT.gt0 est.se est.cv pse CI99left CI99right CI95left CI95right
## 1 3 29669.18 0.6351663 63.51663 0 123133.6 0 104861.4
## 2 3 34926.78 0.6054626 60.54626 0 147651.5 0 126141.3
## CI68left CI68right
## 1 17206.14 76215.64
## 2 22952.90 92419.32output
## DISTRICTNA DSTRBCD1 Primary disturbance nhat
## 1 Medicine Wheel Ranger District 20 Disease 0.12534917
## 2 Medicine Wheel Ranger District 22 Disease to trees 0.05531730
## 3 Medicine Wheel Ranger District 30 Fire 0.05531730
## 4 Tongue Ranger District 52 Wind 0.04440949
## nhat.var NBRPLT.gt0 AREAUSED est est.var est.se est.cv
## 1 0.008479138 2 364522.8 45692.63 1126681476 33566.08 0.7346059
## 2 0.003799284 1 364522.8 20164.42 504836949 22468.58 1.1142686
## 3 0.003799284 1 364522.8 20164.42 504836949 22468.58 1.1142686
## 4 0.002133382 1 413774.9 18375.53 365255577 19111.66 1.0400602
## pse CI99left CI99right CI95left CI95right CI68left CI68right
## 1 73.46059 0 132153.12 0 111480.93 12312.58 79072.68
## 2 111.42686 0 78039.64 0 64202.02 0.00 42508.47
## 3 111.42686 0 78039.64 0 64202.02 0.00 42508.47
## 4 104.00602 0 67603.91 0 55833.70 0.00 37381.27output
## Primary disturbance DSTRBCD1 est est.var NBRPLT.gt0 est.se
## 1 Disease 20 45692.63 1126681476 2 33566.08
## 2 Disease to trees 22 20164.42 504836949 1 22468.58
## 3 Fire 30 20164.42 504836949 1 22468.58
## 4 Wind 52 18375.53 365255577 1 19111.66
## est.cv pse CI99left CI99right CI95left CI95right CI68left CI68right
## 1 0.7346059 73.46059 0 132153.12 0 111480.93 12312.58 79072.68
## 2 1.1142686 111.42686 0 78039.64 0 64202.02 0.00 42508.47
## 3 1.1142686 111.42686 0 78039.64 0 64202.02 0.00 42508.47
## 4 1.0400602 104.00602 0 67603.91 0 55833.70 0.00 37381.27output
## [1] "title.est" "title.pse" "title.unitvar" "title.ref"
## [5] "outfn.estpse" "outfn.rawdat" "outfn.param" "title.rowvar"
## [9] "title.row" "title.colvar" "title.col" "title.unit"output
## $title.est
## [1] "Area, in acres, on forest land by forest-type group and primary disturbance (DSTRBCD1 > 0)"
##
## $title.pse
## [1] "Percent sampling error of area, in acres, on forest land by forest-type group and primary disturbance (DSTRBCD1 > 0)"
##
## $title.unitvar
## [1] "DISTRICTNA"
##
## $title.ref
## [1] "Bighorn National Forest, 2011-2013"
##
## $outfn.estpse
## [1] "area_FORTYPGRPCD_DSTRBCD1_forestland"
##
## $outfn.rawdat
## [1] "area_FORTYPGRPCD_DSTRBCD1_forestland_rawdata"
##
## $outfn.param
## [1] "area_FORTYPGRPCD_DSTRBCD1_forestland_parameters"
##
## $title.rowvar
## [1] "Forest-type group"
##
## $title.row
## [1] "Area, in acres, on forest land by forest-type group (DSTRBCD1 > 0); Bighorn National Forest, 2011-2013"
##
## $title.colvar
## [1] "Primary disturbance"
##
## $title.col
## [1] "Area, in acres, on forest land by primary disturbance (DSTRBCD1 > 0); Bighorn National Forest, 2011-2013"
##
## $title.unit
## [1] "acres"POP4: 4.1 Area by forest type group and stand-size class, Rhode Island, 2019
View Example
Note: estimates should match other FIA tools.
area4.1 <-
modGBarea(GBpopdat = GBpopdat.RI, # pop - population calculations for Bighorn NF, post-stratification
landarea = "FOREST", # est - forest land filter
sumunits = TRUE, # est - sum estimation units to population
rowvar = "FORTYPCD", # est - row domain
colvar = "STDSZCD", # est - column domain
returntitle = TRUE, # out - return title information
table_opts = table_options(row.FIAname = TRUE, # table - return FIA row names
col.FIAname = TRUE) # table - return FIA column names
)To get the names of the list components associated with the output of
our call of modGBarea, we run the following code:
output
## [1] "est" "pse" "titlelst" "raw" "statecd" "states" "invyr"To easily access our estimate and percent sampling error of estimate
we can just grab the est object from our ouputted list:
output
## Forest type Large diameter
## 1 Eastern white pine 29664.4
## 2 Eastern hemlock 1015.5
## 3 Pitch pine 11079.8
## 4 Eastern white pine / northern red oak / white ash 11494.2
## 5 Other pine / hardwood 1267.4
## 6 Chestnut oak --
## 7 White oak / red oak / hickory 75625.8
## 8 White oak 11354.2
## 9 Northern red oak 31766.7
## 10 Yellow-poplar / white oak / northern red oak 3745.7
## 11 Scarlet oak 6384.2
## 12 Chestnut oak / black oak / scarlet oak 31237.2
## 13 Red maple / oak 15559.7
## 14 Mixed upland hardwoods 4800.7
## 15 Sweetbay / swamp tupelo / red maple 18424.4
## 16 Silver maple / American elm 1411.5
## 17 Red maple / lowland 3187.3
## 18 Sugar maple / beech / yellow birch 8744
## 19 Black cherry 2304.4
## 20 Red maple / upland 3745.7
## 21 Aspen 1990.2
## 22 Other hardwoods 1942.8
## 23 Nonstocked --
## 24 Total 276745.7
## Medium diameter Small diameter Nonstocked Total
## 1 -- -- -- 29664.4
## 2 -- -- -- 1015.5
## 3 -- -- -- 11079.8
## 4 2888.3 -- -- 14382.6
## 5 -- -- -- 1267.4
## 6 3745.7 -- -- 3745.7
## 7 22315.7 -- -- 97941.5
## 8 653.5 -- -- 12007.7
## 9 -- -- -- 31766.7
## 10 -- -- -- 3745.7
## 11 19346.9 -- -- 25731.1
## 12 337.8 -- -- 31575
## 13 1569 -- -- 17128.7
## 14 -- -- -- 4800.7
## 15 7108.3 -- -- 25532.8
## 16 -- -- -- 1411.5
## 17 10300.1 -- -- 13487.4
## 18 -- -- -- 8744
## 19 -- -- -- 2304.4
## 20 5086.7 -- -- 8832.4
## 21 -- 3000 -- 4990.1
## 22 3745.7 936.4 -- 6624.9
## 23 -- -- 3347.5 3347.5
## 24 77097.8 3936.4 3347.5 361127.4We can also look at raw data and titles for estimate, as shown below. Note the change in titles.
output
## [1] "unit_totest" "totest" "unit_rowest" "rowest" "unit_colest"
## [6] "colest" "unit_grpest" "grpest" "domdat" "domdatqry"
## [11] "module" "esttype" "popType" "GBmethod" "rowvar"
## [16] "colvar" "areaunits"output
## ESTN_UNIT FORTYPCD Forest type STDSZCD
## 1 2 103 Eastern white pine 1
## 2 2 105 Eastern hemlock 1
## 3 2 167 Pitch pine 1
## 4 2 401 Eastern white pine / northern red oak / white ash 1
## 5 2 401 Eastern white pine / northern red oak / white ash 2
## 6 2 409 Other pine / hardwood 1
## Stand-size class nhat nhat.var NBRPLT.gt0 AREAUSED est
## 1 Large diameter 0.026662405 1.600966e-04 4 568453.6 15156.340
## 2 Large diameter 0.001786383 2.880391e-06 1 568453.6 1015.476
## 3 Large diameter 0.006389858 3.795914e-05 1 568453.6 3632.338
## 4 Large diameter 0.014878180 7.034373e-05 4 568453.6 8457.555
## 5 Medium diameter 0.005081007 1.297166e-05 2 568453.6 2888.317
## 6 Large diameter 0.002229531 2.996697e-06 2 568453.6 1267.385
## est.var est.se est.cv pse CI99left CI99right CI95left CI95right
## 1 51733547.1 7192.6036 0.4745607 47.45607 0 33683.259 1059.096 29253.584
## 2 930768.0 964.7632 0.9500603 95.00603 0 3500.541 0.000 2906.377
## 3 12266097.9 3502.2989 0.9641997 96.41997 0 12653.662 0.000 10496.717
## 4 22730838.2 4767.6869 0.5637193 56.37193 0 20738.302 0.000 17802.049
## 5 4191655.5 2047.3533 0.7088396 70.88396 0 8161.949 0.000 6901.056
## 6 968351.2 984.0484 0.7764399 77.64399 0 3802.126 0.000 3196.085
## CI68left CI68right
## 1 8003.59845 22309.081
## 2 56.05943 1974.892
## 3 149.44889 7115.226
## 4 3716.29112 13198.819
## 5 852.31018 4924.323
## 6 288.79044 2245.980output
## [1] "title.est" "title.pse" "title.unitvar" "title.ref"
## [5] "outfn.estpse" "outfn.rawdat" "outfn.param" "title.rowvar"
## [9] "title.row" "title.colvar" "title.col" "title.unit"output
## $title.est
## [1] "Area, in acres, on forest land by forest type and stand-size class"
##
## $title.pse
## [1] "Percent sampling error of area, in acres, on forest land by forest type and stand-size class"
##
## $title.unitvar
## [1] "ESTN_UNIT"
##
## $title.ref
## [1] "Rhode Island, 2013-2019"
##
## $outfn.estpse
## [1] "area_FORTYPCD_STDSZCD_forestland"
##
## $outfn.rawdat
## [1] "area_FORTYPCD_STDSZCD_forestland_rawdata"
##
## $outfn.param
## [1] "area_FORTYPCD_STDSZCD_forestland_parameters"
##
## $title.rowvar
## [1] "Forest type"
##
## $title.row
## [1] "Area, in acres, on forest land by forest type; Rhode Island, 2013-2019"
##
## $title.colvar
## [1] "Stand-size class"
##
## $title.col
## [1] "Area, in acres, on forest land by stand-size class; Rhode Island, 2013-2019"
##
## $title.unit
## [1] "acres"modGBtree
FIESTA‘s modGBtree function generates tree
estimates based Scott et al. 2005 (’the green-book’) for mapped forest
inventory plots. The non-ratio estimator for estimating tree attributes
by stratum and domain is used. Plots that are totally nonsampled are
excluded from estimation dataset. Next, an adjustment factor is
calculated by strata to adjust for nonsampled (nonresponse) conditions
that have proportion less than 1. Attributes adjusted to a per-acre
value are summed by plot, divided by the adjustment factor, and averaged
by stratum. Strata means are combined using the strata weights and then
expanded to using the total land area in the population.
If there are more than one estimation unit (i.e., subpopulation)
within the population, estimates are generated by estimation unit. If
sumunits = TRUE, the estimates and percent standard errors
returned are a sum combination of all estimation units. If
rawdata = TRUE, the raw data returned will include
estimates by estimation unit.
Parameters defined in the following examples are organized by category: population data (pop); estimation information (est); and output details (out).
The following reference table can be used for defining
estvar and estvar.filter:
output
## ESTTITLE
## 1 Area change
## 2 Area change
## 3 Area change
## 4 Area change
## 5 Area change
## 6 Basal area of saplings (timber species 1 to 5 inches d.b.h.)
## 7 Basal area of saplings (1 to 5 inches d.b.h./d.r.c.)
## 8 Basal area of saplings (woodland species 1 to 5 inches d.r.c.)
## 9 Basal area of live trees (timber species at least 1 inch d.b.h.)
## 10 Basal area of live trees (at least 1 inch d.b.h./d.r.c.)
## 11 Basal area of live trees (woodland species at least 1 inch d.r.c.)
## 12 Basal area of trees (timber species at least 1 inch d.b.h.)
## 13 Basal area of trees (at least 1 inch d.b.h./d.r.c.)
## 14 Basal area of trees (woodland species at least 1 inch d.r.c.)
## 15 Basal area of dead trees (timber species at least 5 inches d.b.h.)
## 16 Basal area of dead trees (at least 5 inches d.b.h./d.r.c.)
## 17 Basal area of dead trees (woodland species at least 5 inches d.r.c.)
## 18 Basal area of growing-stock trees (at least 5 inches d.b.h.)
## 19 Basal area of live trees (timber species at least 5 inches d.b.h.)
## 20 Basal area of live trees (at least 5 inches d.b.h./d.r.c.)
## 21 Basal area of live trees (woodland species at least 5 inches d.r.c.)
## 22 Aboveground biomass of standing-dead trees (timber species at least 1 inch d.b.h.)
## 23 Aboveground biomass of standing-dead trees (at least 1 inch d.b.h./d.r.c.)
## 24 Aboveground biomass of standing-dead trees (woodland species at least 1 inch d.r.c.)
## 25 Aboveground biomass of live trees (timber species at least 1 inch d.b.h.)
## 26 Aboveground biomass of live trees (at least 1 inch d.b.h./d.r.c.)
## 27 Aboveground biomass of live trees (woodland species at least 1 inch d.r.c.)
## 28 Aboveground biomass of trees (timber species at least 1 inch d.b.h.)
## 29 Aboveground biomass of live trees (at least 1 inch d.b.h./d.r.c.)
## 30 Aboveground biomass of live trees (woodland species at least 1 inch d.r.c.)
## 31 Aboveground biomass of standing-dead trees (timber species at least 5 inches d.b.h.)
## 32 Aboveground biomass of standing-dead trees (at least 5 inches d.b.h./d.r.c.)
## 33 Aboveground biomass of standing-dead trees (woodland species at least 5 inches d.r.c.)
## 34 Aboveground biomass of live saplings (timber species at least 1 and less than 5 inches d.b.h.)
## 35 Aboveground biomass of live saplings (at least 1 and less than 5 inches d.b.h./d.r.c.)
## 36 Aboveground biomass of live saplings (woodland species at least 1 and less than 5 inches d.r.c.)
## 37 Aboveground biomass of live trees (timber species at least 5 inches d.b.h.)
## 38 Aboveground biomass of live trees (at least 5 inches d.b.h./d.r.c.)
## 39 Aboveground biomass of live trees (woodland species at least 5 inches d.r.c.)
## 40 Belowground biomass of live saplings (timber species at least 1 and less than 5 inches d.b.h.)
## 41 Belowground biomass of live saplings (at least 1 and less than 5 inches d.b.h./d.r.c.)
## 42 Belowground biomass of live saplings (woodland species at least 1 and less than 5 inches d.r.c.)
## 43 Belowground biomass of live trees (timber species at least 1 inch d.b.h.)
## 44 Belowground biomass of live trees (at least 1 inch d.b.h./d.r.c.)
## 45 Belowground biomass of live trees (woodland species at least 1 inch d.r.c.)
## 46 Belowground biomass of trees (timber species at least 1 inch d.b.h.)
## 47 Belowground biomass of live trees (at least 1 inch d.b.h./d.r.c.)
## 48 Belowground biomass of trees (woodland species at least 1 inch d.r.c.)
## 49 Belowground biomass of standing-dead trees (timber species at least 5 inches d.b.h.)
## 50 Belowground biomass of standing-dead trees (at least 5 inches d.b.h./d.r.c.)
## 51 Belowground biomass of standing-dead trees (woodland species at least 5 inches d.r.c.)
## 52 Belowground biomass of live trees (timber species at least 5 inches d.b.h.)
## 53 Belowground biomass of live trees (at least 5 inch dia)
## 54 Belowground biomass of live trees (woodland species at least 5 inches d.r.c.)
## 55 Branch (excluding any part of the stem) biomass of live trees (timber species at least 1 inch d.b.h.)
## 56 Branch (excluding any part of the stem) biomass of live trees (timber species at least 5 inches d.b.h.)
## 57 Foliage biomass in live saplings (timber species at least 1 and less than 5 inches d.b.h.)
## 58 Foliage biomass in live saplings (at least 1 and less than 5 inches d.b.h./d.r.c.)
## 59 Foliage biomass in live saplings (woodland species at least 1 and less than 5 inches d.r.c.)
## 60 Foliage biomass of live trees (timber species at least 1 inch d.b.h.)
## 61 Foliage biomass of live trees (at least 1 inch d.b.h./d.r.c.)
## 62 Foliage biomass of live trees (woodland species at least 1 inch d.r.c.)
## 63 Foliage biomass in live trees (timber species at least 5 inches d.b.h.)
## 64 Foliage biomass of live trees (at least 5 inches d.b.h./d.r.c.)
## 65 Foliage biomass in live trees (woodland species at least 5 inches d.r.c.)
## 66 Merchantable bole bark biomass of live trees (timber species at least 5 inches d.b.h.)
## 67 Merchantable bole bark and wood biomass of live trees (timber species at least 5 inches d.b.h.)
## 68 Sawlog bark and wood biomass of sawtimber trees
## 69 Stump bark biomass of live trees (timber species at least 5 inches d.b.h.)
## 70 Stump bark and wood biomass of live trees (timber species at least 5 inches d.b.h.)
## 71 Top and limb bark and wood biomass of live trees (timber species at least 5 inches d.b.h.)
## 72 Total-stem (from ground line to tree tip) bark biomass of live trees (timber species at least 5 inches d.b.h.)
## 73 Total-stem (from ground line to tree tip) bark biomass of live trees (timber species at least 5 inches d.b.h.)
## 74 Total-stem (from ground line to tree tip) wood biomass of live trees (timber species at least 5 inches d.b.h.)
## 75 Total-stem (from ground line to tree tip) wood biomass of live trees (timber species at least 5 inches d.b.h.)
## 76 Aboveground biomass of live trees (at least 1 inch d.b.h./d.r.c.)
## 77 Aboveground biomass of live trees (woodland species at least 1 inch d.r.c.)
## 78 Merchantable bole bark and wood biomass of live trees (timber species at least 5 inches d.b.h.)
## 79 Sawlog bark and wood biomass of sawtimber trees
## 80 Stump bark and wood biomass of live trees (timber species at least 5 inches d.b.h.)
## 81 Aboveground biomass of live saplings (timber species at least 1 and less than 5 inches d.b.h.)
## 82 Top and limb bark and wood biomass of live trees (timber species at least 5 inches d.b.h.)
## 83 Aboveground carbon of live saplings (timber species at least 1 and less than 5 inches d.b.h.)
## 84 Aboveground carbon of live saplings (at least 1 and less than 5 inches d.b.h./d.r.c.)
## 85 Aboveground carbon of live saplings (woodland species at least 1 and less than 5 inches d.r.c.)
## 86 Aboveground carbon in standing-dead trees (at least 1 inch d.b.h./d.r.c.)
## 87 Aboveground carbon in trees (timber species at least 1 inch d.b.h.)
## 88 Aboveground carbon in trees (at least 1 inch d.b.h./d.r.c.)
## 89 Aboveground carbon in trees (woodland species at least 1 inch d.r.c.)
## 90 Aboveground carbon in live trees (timber species at least 1 inch d.b.h.)
## 91 Aboveground carbon in live trees (at least 1 inch d.b.h./d.r.c.)
## 92 Aboveground carbon in live trees (woodland species at least 1 inch d.r.c.)
## 93 Aboveground carbon in standing-dead trees (timber species at least 5 inches d.b.h.)
## 94 Aboveground carbon in standing-dead trees (at least 5 inches d.b.h.)
## 95 Aboveground carbon in standing-dead trees (woodland species at least 5 inches d.r.c.)
## 96 Aboveground carbon in live trees (timber species at least 5 inches d.b.h.)
## 97 Aboveground carbon in live trees (at least 5 inches d.b.h.)
## 98 Aboveground carbon in live trees (woodland species at least 5 inches d.r.c.)
## 99 Aboveground and belowground carbon in standing-dead trees (at least 1 inch d.b.h./d.r.c.)
## 100 Aboveground and belowground carbon in live trees (at least 1 inch d.b.h./d.r.c.)
## 101 Aboveground and belowground carbon in standing-dead trees (at least 5 inches d.b.h./d.r.c.)
## 102 Belowground carbon of live saplings (timber species at least 1 and less than 5 inches d.b.h.)
## 103 Belowground carbon of live saplings (at least 1 and less than 5 inches d.b.h./d.r.c.)
## 104 Belowground carbon of live saplings (woodland species at least 1 and less than 5 inches d.r.c.)
## 105 Belowground carbon in trees (timber species at least 1 inch d.b.h.)
## 106 Belowground carbon in trees (at least 1 inch d.b.h./d.r.c.)
## 107 Belowground carbon in trees (woodland species at least 1 inch d.r.c.)
## 108 Belowground carbon in live trees (timber species at least 1 inch d.b.h.)
## 109 Belowground carbon in live trees (at least 1 inch d.b.h./d.r.c.)
## 110 Belowground carbon in live trees (woodland species at least 1 inch d.r.c.)
## 111 Belowground carbon in standing-dead trees (timber species at least 5 inches d.b.h.)
## 112 Belowground carbon in standing-dead trees (at least 5 inches d.b.h.)
## 113 Belowground carbon in standing-dead trees (woodland species at least 5 inches d.r.c.)
## 114 Belowground carbon in live trees (timber species at least 5 inches d.b.h.)
## 115 Belowground carbon in live trees (at least 5 inches d.b.h./d.r.c.)
## 116 Belowground carbon in live trees (woodland species at least 5 inches d.r.c.)
## 117 Number of saplings (timber species 1 to 5 inches d.b.h.)
## 118 Number of saplings (1 to 5 inches d.b.h./d.r.c.)
## 119 Number of saplings (woodland species 1 to 5 inch d.r.c.)
## 120 Number of live trees (timber species at least 1 inch d.b.h.)
## 121 Number of live trees (at least 1 inch d.b.h./d.r.c.)
## 122 Number of live trees (woodland species at least 1 inch d.r.c.)
## 123 Number of standing-dead trees (timber species at least 1 inch d.b.h.)
## 124 Number of standing-dead trees (at least 1 inch d.b.h./d.r.c.)
## 125 Number of standing-dead trees (woodland species at least 1 inch d.b.h.)
## 126 Number of trees (timber species at least 1 inch d.b.h.)
## 127 Number of trees (at least 1 inch d.b.h./d.r.c.)
## 128 Number of trees (woodland species at least 1 inch d.r.c.)
## 129 Number of live trees (timber species at least 5 inches d.b.h.)
## 130 Number of live trees (at least 5 inches d.b.h./d.r.c.)
## 131 Number of live trees (woodland species at least 5 inches d.r.c.)
## 132 Number of standing-dead trees (timber species at least 5 inches d.b.h.)
## 133 Number of standing-dead trees (at least 5 inches d.b.h.)
## 134 Number of standing-dead trees (woodland species at least 5 inches d.r.c.)
## 135 Number of trees (timber species at least 5 inches d.b.h.)
## 136 Number of trees (at least 5 inches d.b.h./d.r.c.)
## 137 Number of trees (woodland species at least 5 inches d.r.c.)
## 138 Number of growing-stock trees (at least 5 inches d.b.h.)
## 139 Number of live trees (timber species including seedlings)
## 140 Number of live trees (including seedlings)
## 141 Number of live trees (woodland species including seedlings)
## 142 Number of seedlings (timber species less than 1 inch d.b.h.)
## 143 Number of live seedlings (less than 1 inch d.b.h./d.r.c.)
## 144 Number of seedlings (woodland species less than 1 inch d.r.c.)
## 145 Gross merchantable bole wood volume of trees (timber species at least 5 inches d.b.h.)
## 146 Gross merchantable bole wood volume of live trees (timber species at least 5 inches d.b.h.)
## 147 Gross merchantable bole wood volume of standing-dead trees (timber species at least 5 inches d.b.h.)
## 148 Gross merchantable bole wood volume of growing-stock trees (at least 5 inches dia)
## 149 Gross sawlog wood volume of sawtimber trees
## 150 Gross sawlog wood volume of sawtimber trees
## 151 Gross sawlog wood volume of sawtimber trees
## 152 Gross sawlog wood volume of sawtimber trees
## 153 Gross stem-top (above 4-inch top diameter) volume of live trees (timber species at least 5 inches d.b.h.)
## 154 Gross stem-top (above 4-inch top diameter) bark volume of live trees (timber species at least 5 inches d.b.h.)
## 155 Gross stump bark volume of live trees (timber species at least 5 inches d.b.h.)
## 156 Gross stump wood volume of live trees (timber species at least 5 inches d.b.h.)
## 157 Gross total-stem wood volume of live saplings (timber species at least 1 and less than 5 inches d.b.h. and woodland species at least 1.5 and less than 5 inches d.r.c.)
## 158 Gross total-stem bark volume of live saplings (timber species at least 1 and less than 5 inches d.b.h.)
## 159 Gross total-stem wood volume of live saplings (timber species at least 1 and less than 5 inches d.b.h.)
## 160 Gross total-stem wood volume of live saplings (woodland species at least 1.5 and less than 5 inches d.r.c)
## 161 Gross total-stem bark volume of live trees (timber species at least 1 inch d.b.h.)
## 162 Gross total-stem bark volume of standing-dead trees (timber species at least 1 inch d.b.h.)
## 163 Gross total-stem bark volume of live trees (timber species at least 1 inch d.b.h. and woodland species at least 1.5 inch d.r.c.)
## 164 Gross total-stem bark volume of standing-dead trees (timber species at least 1 inch d.b.h. and woodland species at least 1.5 inch d.r.c.)
## 165 Gross total-stem bark and wood volume of live trees (timber species at least 1 inch d.b.h. and woodland species at least 1.5 inches d.r.c.)
## 166 Gross total-stem wood volume (timber species at least 1 inch d.b.h.)
## 167 Gross total-stem wood volume of live trees (timber species at least 1 inch d.b.h.)
## 168 Gross total-stem wood volume (timber species at least 1 inch d.b.h. and woodland species at least 1.5 inch d.r.c.)
## 169 Gross total-stem wood volume of live trees (timber species at least 1 inch d.b.h. and woodland species at least 1.5 inch d.r.c.)
## 170 Gross total-stem bark volume of live trees (woodland species at least 1.5 inch d.r.c.)
## 171 Gross total-stem bark volume of standing-dead trees (woodland species at least 1.5 inch d.r.c.)
## 172 Gross total-stem bark and wood volume of live trees (at least 5 inches d.b.h./d.r.c.)
## 173 Gross total-stem wood volume (woodland species at least 1.5 inch d.r.c.)
## 174 Gross total-stem wood volume of live trees (woodland species at least 1.5 inch d.r.c.)
## 175 Gross total-stem bark volume of live trees (timber species at least 5 inches d.b.h.)
## 176 Gross total-stem bark and wood volume of live trees (woodland species at least 1.5 inches d.r.c.)
## 177 Gross total-stem bark and wood volume of live trees (woodland species at least 5 inches d.r.c.)
## 178 Gross total-stem wood volume of live trees (timber species at least 5 inches d.b.h.)
## 179 Gross total-stem wood volume of live trees (at least 5 inches d.b.h./d.r.c.)
## 180 Gross total-stem wood volume of live trees (woodland species at least 5 inches d.r.c.)
## 181 Gross total-stem wood volume of standing-dead trees (timber species at least 5 inches d.b.h.)
## 182 Gross total-stem wood volume of standing-dead trees (at least 5 inches d.b.h.)
## 183 Gross total-stem wood volume of standing-dead trees (woodland species at least 5 inches d.r.c.)
## 184 Net merchantable bole wood volume of trees (timber species at least 5 inches d.b.h.)
## 185 Net merchantable bole wood volume of live trees (timber species at least 5 inches d.b.h.)
## 186 Net merchantable bole wood volume of standing-dead trees (timber species at least 5 inches d.b.h.)
## 187 Net merchantable bole wood volume of growing-stock trees (at least 5 inches d.b.h.)
## 188 Net sawlog wood volume of sawtimber trees
## 189 Net sawlog wood volume of sawtimber trees
## 190 Net sawlog wood volume of sawtimber trees
## 191 Net sawlog wood volume of sawtimber trees
## 192 Sound bole bark volume of live trees (timber species at least 5 inches d.b.h.)
## 193 Sound bole wood volume of trees (timber species at least 5 inches d.b.h.)
## 194 Sound bole wood volume of live trees (timber species at least 5 inches d.b.h.)
## 195 Sound bole wood volume of standing-dead trees (timber species at least 5 inches dia)
## 196 Sound sawlog wood volume of sawtimber trees
## 197 Sound stem-top (above 4-inch top diameter) bark volume of live trees (timber species at least 5 inches d.b.h.)
## 198 Sound stem-top (above 4-inch top diameter) wood volume of live trees (timber species at least 5 inches d.b.h.)
## 199 Sound stump bark volume of live trees (timber species at least 5 inches d.b.h.)
## 200 Sound stump wood volume of live trees (timber species at least 5 inches d.b.h.)
## 201 Sound total-stem bark and wood volume of live trees (timber species at least 1 inch d.b.h. and woodland species at least 1.5 inches d.r.c.)
## 202 Sound total-stem wood volume of live saplings (timber species at least 1 and less than 5 inches d.b.h. and woodland species at least 1.5 and less than 5 inches d.r.c.)
## 203 Sound total-stem bark volume of live saplings (timber species at least 1 and less than 5 inches d.b.h.)
## 204 Sound total-stem wood volume of live saplings (timber species at least 1 and less than 5 inches d.b.h.)
## 205 Sound total-stem wood volume of live saplings (timber species at least 1 and less than 5 inches d.b.h.)
## 206 Sound total-stem wood volume of live saplings (woodland species at least 1.5 dia and less than 5 inch dia)
## 207 Sound total-stem bark volume of live trees (timber species at least 1 inch d.b.h.)
## 208 Sound total-stem wood volume of live trees (timber species at least 1 inch d.b.h.)
## 209 Sound total-stem wood volume of standing-dead trees (timber species at least 1 inch d.b.h.)
## 210 Sound total-stem wood volume (timber species at least 1 inch dia)
## 211 Sound total-stem wood volume of live trees (timber species at least 1 inch d.b.h.)
## 212 Sound total-stem wood volume of live trees (timber species at least 5 inch d.b.h.)
## 213 Sound total-stem wood volume (timber species at least 1 inch d.b.h. and woodland species at least 1.5 inch d.r.c.)
## 214 Sound total-stem wood volume of live trees (timber species at least 1 inch d.b.h. and woodland species at least 1.5 inch d.r.c.)
## 215 Sound total-stem wood volume (woodland species at least 1.5 inch d.r.c.)
## 216 Sound total-stem wood volume of live trees (woodland species at least 1.5 inch d.r.c.)
## 217 Sound total-stem bark and wood volume of live trees (woodland species at least 1.5 inches d.r.c.)
## 218 Sound total-stem bark and wood volume of live trees (woodland species at least 5 inches d.r.c.)
## 219 Sound total-stem bark and wood volume of standing-dead trees (woodland species at least 1.5 inches d.r.c.)
## 220 Sound total-stem bark and wood volume of live trees (at least 5 inches d.b.h./d.r.c.)
## 221 Sound total-stem bark volume of live trees (timber species at least 5 inches d.b.h.)
## 222 Sound total-stem wood volume of live trees (timber species at least 5 inches d.b.h.)
## 223 Sound total-stem wood volume of live trees (at least 5 inches d.b.h./d.r.c.)
## 224 Sound total-stem wood volume of live trees (woodland species at least 5 inches d.r.c.)
## 225 Sound total-stem wood volume of standing-dead trees (timber species at least 5 inches d.b.h.)
## 226 Sound total-stem wood volume of standing-dead trees (at least 5 inches d.b.h./d.r.c.)
## 227 Sound total-stem wood volume of standing-dead trees (woodland species at least 5 inches d.r.c.)
## ESTVAR
## 1
## 2
## 3
## 4
## 5
## 6 BA
## 7 BA
## 8 BA
## 9 BA
## 10 BA
## 11 BA
## 12 BA
## 13 BA
## 14 BA
## 15 BA
## 16 BA
## 17 BA
## 18 BA
## 19 BA
## 20 BA
## 21 BA
## 22 DRYBIO_AG
## 23 DRYBIO_AG
## 24 DRYBIO_AG
## 25 DRYBIO_AG
## 26 DRYBIO_AG
## 27 DRYBIO_AG
## 28 DRYBIO_AG
## 29 DRYBIO_AG
## 30 DRYBIO_AG
## 31 DRYBIO_AG
## 32 DRYBIO_AG
## 33 DRYBIO_AG
## 34 DRYBIO_AG
## 35 DRYBIO_AG
## 36 DRYBIO_AG
## 37 DRYBIO_AG
## 38 DRYBIO_AG
## 39 DRYBIO_AG
## 40 DRYBIO_BG
## 41 DRYBIO_BG
## 42 DRYBIO_BG
## 43 DRYBIO_BG
## 44 DRYBIO_BG
## 45 DRYBIO_BG
## 46 DRYBIO_BG
## 47 DRYBIO_BG
## 48 DRYBIO_BG
## 49 DRYBIO_BG
## 50 DRYBIO_BG
## 51 DRYBIO_BG
## 52 DRYBIO_BG
## 53 DRYBIO_BG
## 54 DRYBIO_BG
## 55 DRYBIO_BRANCH
## 56 DRYBIO_BRANCH
## 57 DRYBIO_FOLIAGE
## 58 DRYBIO_FOLIAGE
## 59 DRYBIO_FOLIAGE
## 60 DRYBIO_FOLIAGE
## 61 DRYBIO_FOLIAGE
## 62 DRYBIO_FOLIAGE
## 63 DRYBIO_FOLIAGE
## 64 DRYBIO_FOLIAGE
## 65 DRYBIO_FOLIAGE
## 66 DRYBIO_BOLE_BARK
## 67 DRYBIO_BOLE_WOOD_BARK
## 68 DRYBIO_SAW_BARK_WOOD
## 69 DRYBIO_STUMP_BARK
## 70 DRYBIO_STUMP_BARK_WOOD
## 71 DRYBIO_TOP_LIMB_BARK_WOOD
## 72 DRYBIO_STEM
## 73 DRYBIO_TOT_STEM_BARK
## 74 DRYBIO_STEM
## 75 DRYBIO_TOT_STEM_WOOD
## 76 GREENBIO_AG
## 77 GREENBIO_AG
## 78 GREENBIO_AG_BOLE_BARK_WOOD
## 79 GREENBIO_SAW_BARK_WOOD
## 80 GREENBIO_STUMP_BARK_WOOD
## 81 GREENBIO_AG
## 82 GREENBIO_TOP_LIMB_BARK_WOOD
## 83 CARBON_AG
## 84 CARBON_AG
## 85 CARBON_AG
## 86 CARBON_AG
## 87 CARBON_AG
## 88 CARBON_AG
## 89 CARBON_AG
## 90 CARBON_AG
## 91 CARBON_AG
## 92 CARBON_AG
## 93 CARBON_AG
## 94 CARBON_AG
## 95 CARBON_AG
## 96 CARBON_AG
## 97 CARBON_AG
## 98 CARBON_AG
## 99 CARBON_AG_BG
## 100 CARBON_AG_BG
## 101 CARBON_AG_BG
## 102 CARBON_BG
## 103 CARBON_BG
## 104 CARBON_BG
## 105 CARBON_BG
## 106 CARBON_BG
## 107 CARBON_BG
## 108 CARBON_BG
## 109 CARBON_BG
## 110 CARBON_BG
## 111 CARBON_BG
## 112 CARBON_BG
## 113 CARBON_BG
## 114 CARBON_BG
## 115 CARBON_BG
## 116 CARBON_BG
## 117 TPA_UNADJ
## 118 TPA_UNADJ
## 119 TPA_UNADJ
## 120 TPA_UNADJ
## 121 TPA_UNADJ
## 122 TPA_UNADJ
## 123 TPA_UNADJ
## 124 TPA_UNADJ
## 125 TPA_UNADJ
## 126 TPA_UNADJ
## 127 TPA_UNADJ
## 128 TPA_UNADJ
## 129 TPA_UNADJ
## 130 TPA_UNADJ
## 131 TPA_UNADJ
## 132 TPA_UNADJ
## 133 TPA_UNADJ
## 134 TPA_UNADJ
## 135 TPA_UNADJ
## 136 TPA_UNADJ
## 137 TPA_UNADJ
## 138 TPA_UNADJ
## 139 TPA_UNADJ
## 140 TPA_UNADJ
## 141 TPA_UNADJ
## 142 TPA_UNADJ
## 143 TPA_UNADJ
## 144 TPA_UNADJ
## 145 VOLCFGRS
## 146 VOLCFGRS
## 147 VOLCFGRS
## 148 VOLCFGRS
## 149 VOLCSGRS
## 150 VOLBFGRS
## 151 VOLBFGRS
## 152 VOLBSGRS
## 153 VOLCFGRS_TOP
## 154 VOLCFGRS_TOP_BARK
## 155 VOLTSGRS_STMP_BARK
## 156 VOLTSGRS_STMP_WOOD
## 157 VOLTSGRS
## 158 VOLTSGRS_BARK
## 159 VOLTSGRS
## 160 VOLTSGRS
## 161 VOLTSGRS_BARK
## 162 VOLTSGRS_BARK
## 163 VOLTSGRS_BARK
## 164 VOLTSGRS_BARK
## 165 VOLTSGRS_BARK_WOOD
## 166 VOLTSGRS
## 167 VOLTSGRS
## 168 VOLTSGRS
## 169 VOLTSGRS
## 170 VOLTSGRS_BARK
## 171 VOLTSGRS_BARK
## 172 VOLTSGRS_BARK_WOOD
## 173 VOLTSGRS
## 174 VOLTSGRS
## 175 VOLTSGRS_BARK
## 176 VOLTSGRS_BARK_WOOD
## 177 VOLTSGRS_BARK_WOOD
## 178 VOLTSGRS
## 179 VOLTSGRS
## 180 VOLTSGRS
## 181 VOLTSGRS
## 182 VOLTSGRS
## 183 VOLTSGRS
## 184 VOLCFNET
## 185 VOLCFNET
## 186 VOLCFNET
## 187 VOLCFNET
## 188 VOLCSNET
## 189 VOLBFNET
## 190 VOLBSNET
## 191 VOLBDNET
## 192 VOLCFSND_BARK
## 193 VOLCFSND
## 194 VOLCFSND
## 195 VOLCFSND
## 196 VOLCFSND_SWLOG
## 197 VOLCFSND_TOP_BARK
## 198 VOLCFSND_TOP_WOOD
## 199 VOLCFSND_STMP_BARK
## 200 VOLCFSND_STMP_WOOD
## 201 VOLCFSND_TOT_BARK_WOOD
## 202 VOLTSSND
## 203 VOLCFSND_TOT_BARK
## 204 VOLCFSND_TOT_WOOD
## 205 VOLTSSND
## 206 VOLTSSND
## 207 VOLCFSND_TOT_BARK
## 208 VOLCFSND_TOT_WOOD
## 209 VOLCFSND_TOT_WOOD
## 210 VOLTSSND
## 211 VOLTSSND
## 212 VOLTSSND
## 213 VOLTSSND
## 214 VOLTSSND
## 215 VOLTSSND
## 216 VOLTSSND
## 217 VOLCFSND_TOT_BARK_WOOD
## 218 VOLCFSND_TOT_BARK_WOOD
## 219 VOLCFSND_TOT_BARK_WOOD
## 220 VOLCFSND_TOT_BARK_WOOD
## 221 VOLCFSND_TOT_BARK
## 222 VOLCFSND_TOT_WOOD
## 223 VOLTSSND
## 224 VOLTSSND
## 225 VOLTSSND
## 226 VOLTSSND
## 227 VOLTSSND
## ESTFILTER
## 1
## 2
## 3
## 4
## 5
## 6 t.DIA < 5.0
## 7 t.DIA < 5.0
## 8 t.DIA < 5.0
## 9 t.STATUSCD == 1 & t.DIA >= 1.0
## 10 t.STATUSCD == 1 & t.DIA >= 1.0
## 11 t.STATUSCD == 1 & t.DIA >= 1.0
## 12
## 13
## 14
## 15 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 5.0
## 16 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 5.0
## 17 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 5.0
## 18 t.TREECLCD == 2 & t.DIA >= 5.0
## 19 t.STATUSCD == 1 & t.DIA >= 5.0
## 20 t.STATUSCD == 1 & t.DIA >= 5.0
## 21 t.STATUSCD == 1 & t.DIA >= 5.0
## 22 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 1.0
## 23 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 1.0
## 24 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 1.0
## 25 t.STATUSCD == 1 & t.DIA >= 1.0
## 26 t.STATUSCD == 1 & t.DIA >= 1.0
## 27 t.STATUSCD == 1 & t.DIA >= 1.0
## 28 t.DIA >= 1.0
## 29 t.STATUSCD == 1 & t.DIA >= 1.0
## 30 t.STATUSCD == 1 & t.DIA >= 1.0
## 31 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 5.0
## 32 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 5.0
## 33 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 5.0
## 34 t.STATUSCD == 1 & t.DIA < 5.0
## 35 t.STATUSCD == 1 & t.DIA < 5.0
## 36 t.STATUSCD == 1 & t.DIA < 5.0
## 37 t.STATUSCD == 1 & t.DIA >= 5.0
## 38 t.STATUSCD == 1 & t.DIA >= 5.0
## 39 t.STATUSCD == 1 & t.DIA >= 5.0
## 40 t.DIA < 5.0
## 41 t.DIA < 5.0
## 42 t.DIA < 5.0
## 43 t.STATUSCD == 1
## 44 t.STATUSCD == 1
## 45 t.STATUSCD == 1
## 46 t.DIA >= 1.0
## 47 t.DIA >= 1.0
## 48 t.DIA >= 1.0
## 49 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 5.0
## 50 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 5.0
## 51 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 5.0
## 52 t.STATUSCD == 1 & t.DIA >= 5.0
## 53 t.STATUSCD == 1 & t.DIA >= 5.0
## 54 t.STATUSCD == 1 & t.DIA >= 5.0
## 55 t.STATUSCD == 1
## 56 t.STATUSCD == 1 & t.DIA >= 5.0
## 57 t.STATUSCD == 1 & t.DIA < 5.0
## 58 t.STATUSCD == 1 & t.DIA < 5.0
## 59 t.STATUSCD == 1 & t.DIA < 5.0
## 60 t.STATUSCD == 1
## 61 t.STATUSCD == 1
## 62 t.STATUSCD == 1
## 63 t.STATUSCD == 1 & t.DIA >= 5.0
## 64 t.STATUSCD == 1 & t.DIA >= 5.0
## 65 t.STATUSCD == 1 & t.DIA >= 5.0
## 66 t.STATUSCD == 1 & t.DIA >= 5.0
## 67 t.STATUSCD == 1 & t.DIA >= 5.0
## 68 t.TREECLCD == 2 & t.STATUSCD == 1
## 69 t.STATUSCD == 1 & t.DIA >= 5.0
## 70 t.STATUSCD == 1 & t.DIA >= 5.0
## 71 t.STATUSCD == 1 & t.DIA >= 5.0
## 72 t.STATUSCD == 1 & t.DIA >= 5.0
## 73 t.STATUSCD == 1 & t.DIA >= 5.0
## 74 t.STATUSCD == 1
## 75 t.STATUSCD == 1 & t.DIA >= 5.0
## 76 t.STATUSCD == 1 & t.DIA >= 1.0
## 77 t.STATUSCD == 1 & t.DIA >= 1.0
## 78 t.STATUSCD == 1 & t.DIA >= 5.0
## 79 t.TREECLCD == 2 & t.STATUSCD == 1
## 80 t.STATUSCD == 1 & t.DIA >= 5.0
## 81 t.STATUSCD == 1 & t.DIA < 5
## 82 t.STATUSCD == 1 & t.DIA >= 5.0
## 83 t.DIA < 5.0
## 84 t.DIA < 5.0
## 85 t.DIA < 5.0
## 86 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 1.0
## 87 t.DIA >= 1.0
## 88 t.DIA >= 1.0
## 89 t.DIA >= 1.0
## 90 t.STATUSCD == 1
## 91 t.STATUSCD == 1
## 92 t.STATUSCD == 1
## 93 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 5.0
## 94 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 5.0
## 95 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 5.0
## 96 t.STATUSCD == 1 & t.DIA >= 5.0
## 97 t.STATUSCD == 1 & t.DIA >= 5.0
## 98 t.STATUSCD == 1 & t.DIA >= 5.0
## 99 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 1.0
## 100 t.STATUSCD == 1 & t.DIA >= 1.0
## 101 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 5.0
## 102 t.DIA < 5.0
## 103 t.DIA < 5.0
## 104 t.DIA < 5.0
## 105 t.DIA >= 1.0
## 106 t.DIA >= 1.0
## 107 t.DIA >= 1.0
## 108 t.STATUSCD == 1
## 109 t.STATUSCD == 1
## 110 t.STATUSCD == 1
## 111 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 5.0
## 112 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 5.0
## 113 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 5.0
## 114 t.STATUSCD == 1 & t.DIA >= 5.0
## 115 t.STATUSCD == 1 & t.DIA >= 5.0
## 116 t.STATUSCD == 1 & t.DIA >= 5.0
## 117 t.DIA < 5.0
## 118 t.DIA < 5.0
## 119 t.DIA < 5.0
## 120 t.STATUSCD == 1 & t.DIA >= 1.0
## 121 t.STATUSCD == 1 & t.DIA >= 1.0
## 122 t.STATUSCD == 1 & t.DIA >= 1.0
## 123 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 1.0
## 124 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 1.0
## 125 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 1.0
## 126
## 127
## 128
## 129 t.STATUSCD == 1 & t.DIA >= 5.0
## 130 t.STATUSCD == 1 & t.DIA >= 5.0
## 131 t.STATUSCD == 1 & t.DIA >= 5.0
## 132 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 5.0
## 133 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 5.0
## 134 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 5.0
## 135
## 136
## 137
## 138 t.TREECLCD == 2 & t.DIA >= 5.0
## 139 t.STATUSCD == 1
## 140 t.STATUSCD == 1
## 141 t.STATUSCD == 1
## 142
## 143
## 144
## 145 t.DIA >= 5.0
## 146 t.STATUSCD == 1 & t.DIA >= 5.0
## 147 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 5.0
## 148 t.TREECLCD == 2 & t.DIA >= 5.0
## 149 t.STATUSCD == 1
## 150 t.TREECLCD == 2 & t.STATUSCD == 1
## 151 t.TREECLCD == 2 & t.STATUSCD == 1
## 152 t.TREECLCD == 2 & t.STATUSCD == 1
## 153 t.STATUSCD == 1 & t.DIA >= 5.0
## 154 t.STATUSCD == 1 & t.DIA >= 5.0
## 155 t.STATUSCD == 1 & t.DIA >= 5.0
## 156 t.STATUSCD == 1 & t.DIA >= 5.0
## 157 t.DIA < 5
## 158 t.STATUSCD == 1 & t.DIA < 5
## 159 t.DIA < 5
## 160 t.DIA < 5
## 161 t.STATUSCD == 1 & t.DIA >= 1.0
## 162 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 1.0
## 163 t.STATUSCD == 1 & t.DIA >= 1.0
## 164 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 1.0
## 165 t.STATUSCD ==1
## 166
## 167 t.STATUSCD == 1
## 168
## 169 t.STATUSCD == 1
## 170 t.STATUSCD == 1 & t.DIA >= 1.0
## 171 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 1.0
## 172 t.STATUSCD == 1 & t.DIA >= 5.0
## 173
## 174 t.STATUSCD == 1
## 175 t.STATUSCD == 1 & t.DIA >= 5.0
## 176 t.STATUSCD == 1 & t.DIA >= 1.5
## 177 t.STATUSCD == 1 & t.DIA >= 5.0
## 178 t.STATUSCD == 1 & t.DIA >= 5.0
## 179 t.STATUSCD == 1 & t.DIA >= 5.0
## 180 t.STATUSCD == 1 & t.DIA >= 5.0
## 181 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 5.0
## 182 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 5.0
## 183 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 5.0
## 184 t.DIA >= 5.0
## 185 t.STATUSCD == 1 & t.DIA >= 5.0
## 186 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 5.0
## 187 t.TREECLCD == 2 & t.DIA >= 5.0
## 188 t.STATUSCD == 1
## 189 t.TREECLCD == 2 & t.STATUSCD == 1
## 190 t.TREECLCD == 2 & t.STATUSCD == 1
## 191 t.TREECLCD == 2 & t.STATUSCD == 1
## 192 t.STATUSCD == 1 & t.DIA >= 5.0
## 193 t.DIA >= 5.0
## 194 t.STATUSCD == 1 & t.DIA >= 5.0
## 195 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 5.0
## 196 t.STATUSCD == 1 & t.DIA >= 5.0
## 197 t.STATUSCD == 1 & t.DIA >= 5.0
## 198 t.STATUSCD == 1 & t.DIA >= 5.0
## 199 t.STATUSCD == 1 & t.DIA >= 5.0
## 200 t.STATUSCD == 1 & t.DIA >= 5.0
## 201 t.STATUSCD == 1 & TIMBER >= 1.0 & WOODLAND >= 1.5
## 202 t.STATUSCD == 1 & t.DIA < 5
## 203 t.STATUSCD == 1 & t.DIA < 5
## 204 t.STATUSCD == 1 & t.DIA < 5
## 205 t.STATUSCD == 1 & t.DIA < 5
## 206 t.STATUSCD == 1 & t.DIA < 5
## 207 t.STATUSCD == 1 & t.DIA >= 1.0
## 208 t.STATUSCD == 1 & t.DIA >= 1.0
## 209 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 1.0
## 210
## 211 t.STATUSCD == 1
## 212 t.STATUSCD == 1 & t.DIA >= 5.0
## 213
## 214 t.STATUSCD == 1
## 215
## 216 t.STATUSCD == 1
## 217 t.STATUSCD == 1 & t.DIA >= 1.5
## 218 t.STATUSCD == 1 & t.DIA >= 5.0
## 219 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 1.5
## 220 t.STATUSCD == 1 & t.DIA >= 5.0
## 221 t.STATUSCD == 1 & t.DIA >= 5.0
## 222 t.STATUSCD == 1 & t.DIA >= 5.0
## 223 t.STATUSCD == 1 & t.DIA >= 5.0
## 224 t.STATUSCD == 1 & t.DIA >= 5.0
## 225 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 5.0
## 226 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 5.0
## 227 t.STATUSCD == 2 & t.STANDING_DEAD_CD == 1 & t.DIA >= 5.0
## ESTUNITS
## 1
## 2
## 3
## 4
## 5
## 6 square feet
## 7 square feet
## 8 square feet
## 9 square feet
## 10 square feet
## 11 square feet
## 12 square feet
## 13 square feet
## 14 square feet
## 15 square feet
## 16 square feet
## 17 square feet
## 18 square feet
## 19 square feet
## 20 square feet
## 21 square feet
## 22 dry short tons
## 23 dry short tons
## 24 dry short tons
## 25 dry short tons
## 26 dry short tons
## 27 dry short tons
## 28 dry short tons
## 29 dry short tons
## 30 dry short tons
## 31 dry short tons
## 32 dry short tons
## 33 dry short tons
## 34 dry short tons
## 35 dry short tons
## 36 dry short tons
## 37 dry short tons
## 38 dry short tons
## 39 dry short tons
## 40 dry short tons
## 41 dry short tons
## 42 dry short tons
## 43 dry short tons
## 44 dry short tons
## 45 dry short tons
## 46 dry short tons
## 47 dry short tons
## 48 dry short tons
## 49 dry short tons
## 50 dry short tons
## 51 dry short tons
## 52 dry short tons
## 53 dry short tons
## 54 dry short tons
## 55 dry short tons
## 56 dry short tons
## 57 dry short tons
## 58 dry short tons
## 59 dry short tons
## 60 dry short tons
## 61 dry short tons
## 62 dry short tons
## 63 dry short tons
## 64 dry short tons
## 65 dry short tons
## 66 dry short tons
## 67 dry short tons
## 68 dry short tons
## 69 dry short tons
## 70 dry short tons
## 71 dry short tons
## 72 dry short tons
## 73 dry short tons
## 74 dry short tons
## 75 dry short tons
## 76 green short tons
## 77 green short tons
## 78 green short tons
## 79 green short tons
## 80 green short tons
## 81 green short tons
## 82 green short tons
## 83 short tons
## 84 short tons
## 85 short tons
## 86 short tons
## 87 short tons
## 88 short tons
## 89 short tons
## 90 short tons
## 91 short tons
## 92 short tons
## 93 short tons
## 94 short tons
## 95 short tons
## 96 short tons
## 97 short tons
## 98 short tons
## 99 short tons
## 100 short tons
## 101 short tons
## 102 short tons
## 103 short tons
## 104 short tons
## 105 short tons
## 106 short tons
## 107 short tons
## 108 short tons
## 109 short tons
## 110 short tons
## 111 short tons
## 112 short tons
## 113 short tons
## 114 short tons
## 115 short tons
## 116 short tons
## 117 trees
## 118 trees
## 119 trees
## 120 trees
## 121 trees
## 122 trees
## 123 trees
## 124 trees
## 125 trees
## 126 trees
## 127 trees
## 128 trees
## 129 trees
## 130 trees
## 131 trees
## 132 trees
## 133 trees
## 134 trees
## 135 trees
## 136 trees
## 137 trees
## 138 trees
## 139 trees
## 140 trees
## 141 trees
## 142 seedlings
## 143 seedlings
## 144 seedlings
## 145 cubic feet
## 146 cubic feet
## 147 cubic feet
## 148 cubic feet
## 149 cubic feet
## 150 board feet (International 1/4-inch rule)
## 151 board feet (International 1/4-inch rule)
## 152 board feet (Scribner rule)
## 153 cubic feet
## 154 cubic feet
## 155 cubic feet
## 156 cubic feet
## 157 cubic feet
## 158 cubic feet
## 159 cubic feet
## 160 cubic feet
## 161 cubic feet
## 162 cubic feet
## 163 cubic feet
## 164 cubic feet
## 165 cubic feet
## 166 cubic feet
## 167 cubic feet
## 168 cubic feet
## 169 cubic feet
## 170 cubic feet
## 171 cubic feet
## 172 cubic feet
## 173 cubic feet
## 174 cubic feet
## 175 cubic feet
## 176 cubic feet
## 177 cubic feet
## 178 cubic feet
## 179 cubic feet
## 180 cubic feet
## 181 cubic feet
## 182 cubic feet
## 183 cubic feet
## 184 cubic feet
## 185 cubic feet
## 186 cubic feet
## 187 cubic feet
## 188 cubic feet
## 189 board feet (International 1/4-inch rule)
## 190 board feet (Scribner rule)
## 191 board feet (Doyle rule)
## 192 cubic feet
## 193 cubic feet
## 194 cubic feet
## 195 cubic feet
## 196 cubic feet
## 197 cubic feet
## 198 cubic feet
## 199 cubic feet
## 200 cubic feet
## 201 cubic feet
## 202 cubic feet
## 203 cubic feet
## 204 cubic feet
## 205 cubic feet
## 206 cubic feet
## 207 cubic feet
## 208 cubic feet
## 209 cubic feet
## 210 cubic feet
## 211 cubic feet
## 212 cubic feet
## 213 cubic feet
## 214 cubic feet
## 215 cubic feet
## 216 cubic feet
## 217 cubic feet
## 218 cubic feet
## 219 cubic feet
## 220 cubic feet
## 221 cubic feet
## 222 cubic feet
## 223 cubic feet
## 224 cubic feet
## 225 cubic feet
## 226 cubic feet
## 227 cubic feetPOP1: 1.1 Net cubic-foot volume of live trees, Wyoming, 2011-2013
View Example
Now, we can generate estimates by estimation unit (i.e., ESTN_UNIT)
and sum to population (i.e., WY) with modGBtree:
tree1.1 <-
modGBtree(GBpopdat = GBpopdat, # pop - population calculations
landarea = "FOREST", # est - forest land filter
sumunits = TRUE, # est - sum estimation units to population
estvar = "VOLCFNET", # est - net cubic-foot volume
estvar.filter = "STATUSCD == 1", # est - live trees only
returntitle = TRUE) # out - return title informationWe can now take a look at the output list, estimates and percent sampling errors, raw data, and titles:
output
## [1] "est" "titlelst" "raw" "statecd" "states" "invyr"output
## TOTAL Estimate Percent Sampling Error
## 1 Total 13516579068 4.7# Raw data (list object) for estimate
raw1.1 <- tree1.1$raw # extract raw data list object from output
names(raw1.1)output
## [1] "unit_totest" "totest" "domdat" "domdatqry"
## [5] "estvar" "estvar.filter" "module" "esttype"
## [9] "GBmethod" "rowvar" "colvar" "areaunits"
## [13] "estunits"output
## ESTN_UNIT nhat nhat.var NBRPLT.gt0 AREAUSED est est.var
## 1 1 182.99248 570.5481 23 2757613 504622439 4.338693e+15
## 12 3 227.15520 4219.9381 9 2021729 459246247 1.724853e+16
## 21 5 22.29478 137.4299 12 3072988 68511597 1.297785e+15
## 22 7 229.36665 618.5487 34 5096959 1169072435 1.606927e+16
## 23 9 61.10384 488.5526 14 2729653 166792289 3.640208e+15
## 2 11 332.82332 3942.7626 26 1837124 611437715 1.330692e+16
## est.se est.cv pse CI99left CI99right CI95left CI95right
## 1 65868753 0.1305308 13.05308 334955776 674289103 375522056 633722823
## 12 131333641 0.2859765 28.59765 120953208 797539287 201837042 716655453
## 21 36024789 0.5258203 52.58203 0 161305304 0 139118886
## 22 126764628 0.1084318 10.84318 842548393 1495596478 920618331 1417526540
## 23 60334138 0.3617322 36.17322 11381849 322202730 48539552 285045027
## 2 115355627 0.1886629 18.86629 314301311 908574118 385344841 837530588
## CI68left CI68right NBRPLT
## 1 439118739 570126140 133
## 12 328640473 589852022 98
## 21 32686462 104336733 152
## 22 1043010352 1295134519 245
## 23 106792530 226792049 133
## 2 496721402 726154027 85output
## TOTAL est est.var NBRPLT.gt0 AREAUSED est.se est.cv
## 1 1 13516579068 4.027576e+17 470 62600430 634631854 0.04695211
## pse CI99left CI99right CI95left CI95right CI68left
## 1 4.695211 11881875741 15151282396 12272723490 14760434646 12885464418
## CI68right NBRPLT
## 1 14147693719 3047output
## [1] "title.estpse" "title.yvar" "title.estvar" "title.unitvar"
## [5] "title.ref" "outfn.estpse" "outfn.rawdat" "outfn.param"
## [9] "title.tot" "title.unit"output
## $title.estpse
## [1] "VOLCFNET_TPA_ADJ_LIVE, in cubic feet, and percent sampling error on forest land"
##
## $title.yvar
## [1] ", in cubic feet"
##
## $title.estvar
## [1] "VOLCFNET_TPA_ADJ_LIVE"
##
## $title.unitvar
## [1] "ESTN_UNIT"
##
## $title.ref
## [1] "Wyoming, 2011-2013"
##
## $outfn.estpse
## [1] "tree_VOLCFNET_TPA_ADJ_LIVE_forestland"
##
## $outfn.rawdat
## [1] "tree_VOLCFNET_TPA_ADJ_LIVE_forestland_rawdata"
##
## $outfn.param
## [1] "tree_VOLCFNET_TPA_ADJ_LIVE_forestland_parameters"
##
## $title.tot
## [1] "VOLCFNET_TPA_ADJ_LIVE, in cubic feet, on forest land; Wyoming, 2011-2013"
##
## $title.unit
## [1] "cubic feet"POP1: 1.2 Net cubic-foot volume of live trees by forest type, Wyoming, 2011-2013
View Example
This example adds rows to the output for net cubic-foot volume of
live trees (at least 5 inches diameter) by forest type, Wyoming,
2011-2013. We also choose to return titles with
returntitle = TRUE.
tree1.2 <- modGBtree(GBpopdat = GBpopdat, # pop - population calculations
landarea = "FOREST", # est - forest land filter
sumunits = TRUE, # est - sum estimation units to population
estvar = "VOLCFNET", # est - net cubic-foot volume
estvar.filter = "STATUSCD == 1", # est - live trees only
rowvar = "FORTYPCD", # est - row domain
returntitle = TRUE) # out - return title informationAgain, we investigate the output of the returned list:
output
## [1] "est" "titlelst" "raw" "statecd" "states" "invyr"output
## Forest type Estimate Percent Sampling Error
## 1 182 103705329.9 42.43
## 2 184 7591934.5 86.68
## 3 185 -- --
## 4 201 1279391473.1 20.05
## 5 221 1134539402 15.44
## 6 265 1318783735.9 27.1
## 7 266 3197965334.6 12.53
## 8 268 1543226579.4 16.43
## 9 269 54704348.4 101.99
## 10 281 3899090965.5 10.64
## 11 366 52426047.4 49.94
## 12 367 242115077.6 27.2
## 13 509 32834363.6 63.49
## 14 517 2578979.3 107.34
## 15 703 169546392.1 58.21
## 16 706 4455857.7 100
## 17 901 420518373.4 27.81
## 18 999 53104873.9 42.69
## 19 <NA> -- --
## 20 Total 13600351582.3 4.66# Raw data (list object) for estimate
raw1.2 <- tree1.2$raw # extract raw data list object from output
names(raw1.2)output
## [1] "unit_totest" "totest" "unit_rowest" "rowest"
## [5] "domdat" "domdatqry" "estvar" "estvar.filter"
## [9] "module" "esttype" "GBmethod" "rowvar"
## [13] "colvar" "areaunits" "estunits"output
## ESTN_UNIT nhat nhat.var NBRPLT.gt0 AREAUSED est est.var
## 1 1 185.93460 572.7965 25 2757613 512735671 4.355790e+15
## 12 3 227.71035 4200.1335 10 2021729 460368609 1.716758e+16
## 21 5 22.29478 137.4299 12 3072988 68511597 1.297785e+15
## 22 7 229.36665 618.5487 34 5096959 1169072435 1.606927e+16
## 23 9 61.74409 480.7225 15 2729653 168539934 3.581866e+15
## 2 11 333.03647 3936.8016 27 1837124 611829284 1.328680e+16
## est.se est.cv pse CI99left CI99right CI95left CI95right
## 1 65998412 0.1287182 12.87182 342735028 682736315 383381161 642090182
## 12 131025097 0.2846091 28.46091 122870326 797866892 203564138 717173079
## 21 36024789 0.5258203 52.58203 0 161305304 0 139118886
## 22 126764628 0.1084318 10.84318 842548393 1495596478 920618331 1417526540
## 23 59848693 0.3551010 35.51010 14379918 322699950 51238652 285841216
## 2 115268392 0.1883996 18.83996 314917581 908740986 385907386 837751181
## CI68left CI68right NBRPLT
## 1 447103030 578368312 133
## 12 330069669 590667549 98
## 21 32686462 104336733 152
## 22 1043010352 1295134519 245
## 23 109022930 228056938 133
## 2 497199722 726458845 85output
## TOTAL est est.var NBRPLT.gt0 AREAUSED est.se est.cv
## 1 1 13600351582 4.013324e+17 487 62600430 633508003 0.04658027
## pse CI99left CI99right CI95left CI95right CI68left
## 1 4.658027 11968543103 15232160061 12358698712 1.4842e+10 12970354554
## CI68right NBRPLT
## 1 14230348610 3047output
## ESTN_UNIT Forest type nhat nhat.var NBRPLT.gt0 AREAUSED est
## 1 1 182 0.4333135 0.1979394 1 2757613 1194911
## 2 1 201 15.9927786 197.6889704 1 2757613 44101894
## 3 1 221 33.6483513 248.1857429 4 2757613 92789131
## 4 1 266 66.8269701 727.3782450 4 2757613 184282921
## 5 1 268 8.7794104 59.5751697 1 2757613 24210216
## 6 1 281 44.1639244 440.8727504 4 2757613 121787012
## est.var est.se est.cv pse CI99left CI99right CI95left
## 1 1.505216e+12 1226873 1.0267481 102.67481 0 4355125 0
## 2 1.503312e+15 38772565 0.8791587 87.91587 0 143973404 0
## 3 1.887311e+15 43443192 0.4681927 46.81927 0 204691379 7642038
## 4 5.531297e+15 74372687 0.4035788 40.35788 0 375854268 38515134
## 5 4.530352e+14 21284623 0.8791587 87.91587 0 79035772 0
## 6 3.352586e+15 57901518 0.4754326 47.54326 0 270931438 8302123
## CI95right CI68left CI68right
## 1 3599537 0 2414984
## 2 120094726 5544211 82659577
## 3 177936224 49586706 135991556
## 4 330050709 110322417 258243426
## 5 65927311 3043555 45376877
## 6 235271901 64206392 179367633output
## Forest type est est.var NBRPLT.gt0 est.se est.cv pse
## 1 182 103705330 1.936588e+15 22 44006682 0.4243435 42.43435
## 2 184 7591935 4.330587e+13 4 6580719 0.8668040 86.68040
## 3 185 0 0.000000e+00 0 0 NaN NaN
## 4 201 1279391473 6.583002e+16 47 256573611 0.2005435 20.05435
## 5 221 1134539402 3.068444e+16 51 175169736 0.1543972 15.43972
## 6 265 1318783736 1.277336e+17 26 357398338 0.2710060 27.10060
## CI99left CI99right CI95left CI95right CI68left CI68right
## 1 0 217059031 17453818 189956841 59942538 147468122
## 2 0 24542744 0 20489908 1047686 14136183
## 3 0 0 0 0 0 0
## 4 618501647 1940281299 776516436 1782266510 1024239823 1534543123
## 5 683332063 1585746741 791213028 1477865776 960340477 1308738327
## 6 398186623 2239380848 618295865 2019271607 963366141 1674201331output
## [1] "title.estpse" "title.yvar" "title.estvar" "title.unitvar"
## [5] "title.ref" "outfn.estpse" "outfn.rawdat" "outfn.param"
## [9] "title.rowvar" "title.row" "title.unit"output
## $title.estpse
## [1] "VOLCFNET_TPA_ADJ_LIVE, in cubic feet, and percent sampling error on forest land by forest type"
##
## $title.yvar
## [1] ", in cubic feet"
##
## $title.estvar
## [1] "VOLCFNET_TPA_ADJ_LIVE"
##
## $title.unitvar
## [1] "ESTN_UNIT"
##
## $title.ref
## [1] "Wyoming, 2011-2013"
##
## $outfn.estpse
## [1] "tree_VOLCFNET_TPA_ADJ_LIVE_FORTYPCD_forestland"
##
## $outfn.rawdat
## [1] "tree_VOLCFNET_TPA_ADJ_LIVE_FORTYPCD_forestland_rawdata"
##
## $outfn.param
## [1] "tree_VOLCFNET_TPA_ADJ_LIVE_FORTYPCD_forestland_parameters"
##
## $title.rowvar
## [1] "Forest type"
##
## $title.row
## [1] "VOLCFNET_TPA_ADJ_LIVE, in cubic feet, on forest land by forest type; Wyoming, 2011-2013"
##
## $title.unit
## [1] "cubic feet"We can also create a simple barplot from the output:
plot
POP1: 1.3 Net cubic-foot volume of live trees by forest type and stand-size class, Wyoming, 2011-2013
View Example
This examples adds rows and columns to the output, including FIA
names, for net cubic-foot volume of live trees (at least 5 inches
diameter) by forest type and stand-size class, Wyoming, 2011-2013. We
also use the *_options functions to return output with
estimates (est) and percent standard error (pse) in same cell - est(pse)
with allin1 = TRUE and save data to an outfolder with
savedata = TRUE and outfolder = outfolder.
tree1.3 <-
modGBtree(GBpopdat = GBpopdat, # pop - population calculations
landarea = "FOREST", # est - forest land filter
sumunits = TRUE, # est - sum estimation units to population
estvar = "VOLCFNET", # est - net cubic-foot volume
estvar.filter = "STATUSCD == 1", # est - live trees only
rowvar = "FORTYPCD", # est - row domain
colvar = "STDSZCD", # est - column domain
returntitle = TRUE, # out - return title information
savedata = TRUE, # out - save data to outfolder
table_opts = table_options(row.FIAname = TRUE, # est - row domain names
col.FIAname = TRUE, # est - column domain names
allin1 = TRUE), # out - return output with est(pse)
savedata_opts = savedata_options(
outfolder = outfolder, # out - outfolder for saving data
outfn.pre = "WY") # out - prefix for output files
)Again, we investigate the output of the returned list:
output
## [1] "est" "titlelst" "raw" "statecd" "states" "invyr"output
## Forest type Large diameter
## 1 Rocky Mountain juniper 85,055,988.6 ( 49.82)
## 2 Juniper woodland 7,591,934.5 ( 86.68)
## 3 Pinyon / juniper woodland -- ( --)
## 4 Douglas-fir 1,140,205,175.8 ( 22.15)
## 5 Ponderosa pine 1,074,972,177.1 ( 16.31)
## 6 Engelmann spruce 1,148,600,635.6 ( 30.12)
## 7 Engelmann spruce / subalpine fir 2,595,233,199.9 ( 14.80)
## 8 Subalpine fir 1,245,621,714.4 ( 19.26)
## 9 Blue spruce 54,704,348.4 (101.99)
## 10 Lodgepole pine 2,307,223,821.3 ( 15.56)
## 11 Limber pine 37,629,737.1 ( 67.46)
## 12 Whitebark pine 118,870,056.2 ( 45.01)
## 13 Bur oak 18,577,479.5 (107.34)
## 14 Elm / ash / black locust -- ( --)
## 15 Cottonwood 164,843,686.0 ( 59.83)
## 16 Sugarberry / hackberry / elm / green ash -- ( --)
## 17 Aspen 70,340,496.6 ( 49.87)
## 18 Nonstocked -- ( --)
## 19 Other -- ( --)
## 20 Total 10,069,470,451.1 ( 6.36)
## Medium diameter Small diameter Nonstocked
## 1 16,736,394.2 ( 70.48) 1,912,947.0 ( 89.45) -- ( --)
## 2 -- ( --) -- ( --) -- ( --)
## 3 -- ( --) -- ( --) -- ( --)
## 4 94,302,692.8 ( 46.03) 44,883,604.5 ( 51.47) -- ( --)
## 5 52,603,087.3 ( 66.66) 6,964,137.6 ( 84.92) -- ( --)
## 6 137,667,904.0 ( 65.78) 32,515,196.4 ( 69.63) -- ( --)
## 7 454,333,764.9 ( 28.34) 148,398,369.8 ( 37.24) -- ( --)
## 8 236,873,679.2 ( 38.35) 60,731,185.8 ( 40.74) -- ( --)
## 9 -- ( --) -- ( --) -- ( --)
## 10 1,414,909,655.2 ( 16.23) 176,957,489.0 ( 29.11) -- ( --)
## 11 -- ( --) 14,796,310.4 ( 44.11) -- ( --)
## 12 83,010,320.7 ( 43.06) 40,234,700.7 ( 49.07) -- ( --)
## 13 7,750,865.8 ( 72.26) 6,506,018.4 ( 74.53) -- ( --)
## 14 -- ( --) 2,578,979.3 (107.34) -- ( --)
## 15 2,057,215.9 (102.34) 2,645,490.2 (102.13) -- ( --)
## 16 4,455,857.7 (100.00) -- ( --) -- ( --)
## 17 240,712,660.9 ( 44.47) 109,465,215.8 ( 32.21) -- ( --)
## 18 -- ( --) -- ( --) 53,104,873.9 ( 42.69)
## 19 -- ( --) -- ( --) -- ( --)
## 20 2,745,414,098.6 ( 11.08) 53,104,873.9 ( 42.69) -- ( --)
## Other Total
## 1 -- ( --) 420,518,373.4 ( 27.81)
## 2 -- ( --) 54,704,348.4 (101.99)
## 3 -- ( --) 32,834,363.6 ( 63.49)
## 4 -- ( --) 169,546,392.1 ( 58.21)
## 5 -- ( --) 1,279,391,473.1 ( 20.05)
## 6 -- ( --) 2,578,979.3 (107.34)
## 7 -- ( --) 1,318,783,735.9 ( 27.10)
## 8 -- ( --) 3,197,965,334.6 ( 12.53)
## 9 -- ( --) 7,591,934.5 ( 86.68)
## 10 -- ( --) 52,426,047.4 ( 49.94)
## 11 -- ( --) 3,899,090,965.5 ( 10.64)
## 12 -- ( --) 53,104,873.9 ( 42.69)
## 13 -- ( --) -- ( --)
## 14 -- ( --) -- ( --)
## 15 -- ( --) 1,134,539,402.0 ( 15.44)
## 16 -- ( --) 103,705,329.9 ( 42.43)
## 17 -- ( --) 1,543,226,579.4 ( 16.43)
## 18 -- ( --) 4,455,857.7 (100.00)
## 19 -- ( --) 242,115,077.6 ( 27.20)
## 20 648,589,644.9 ( 14.26) 13,600,351,582.3 ( 4.66)# Raw data (list object) for estimate
raw1.3 <- tree1.3$raw # extract raw data list object from output
names(raw1.3)output
## [1] "unit_totest" "totest" "unit_rowest" "rowest"
## [5] "unit_colest" "colest" "unit_grpest" "grpest"
## [9] "domdat" "domdatqry" "estvar" "estvar.filter"
## [13] "module" "esttype" "GBmethod" "rowvar"
## [17] "colvar" "areaunits" "estunits"output
## ESTN_UNIT nhat nhat.var NBRPLT.gt0 AREAUSED est est.var
## 1 1 185.93460 572.7965 25 2757613 512735671 4.355790e+15
## 12 3 227.71035 4200.1335 10 2021729 460368609 1.716758e+16
## 21 5 22.29478 137.4299 12 3072988 68511597 1.297785e+15
## 22 7 229.36665 618.5487 34 5096959 1169072435 1.606927e+16
## 23 9 61.74409 480.7225 15 2729653 168539934 3.581866e+15
## 2 11 333.03647 3936.8016 27 1837124 611829284 1.328680e+16
## est.se est.cv pse CI99left CI99right CI95left CI95right
## 1 65998412 0.1287182 12.87182 342735028 682736315 383381161 642090182
## 12 131025097 0.2846091 28.46091 122870326 797866892 203564138 717173079
## 21 36024789 0.5258203 52.58203 0 161305304 0 139118886
## 22 126764628 0.1084318 10.84318 842548393 1495596478 920618331 1417526540
## 23 59848693 0.3551010 35.51010 14379918 322699950 51238652 285841216
## 2 115268392 0.1883996 18.83996 314917581 908740986 385907386 837751181
## CI68left CI68right NBRPLT
## 1 447103030 578368312 133
## 12 330069669 590667549 98
## 21 32686462 104336733 152
## 22 1043010352 1295134519 245
## 23 109022930 228056938 133
## 2 497199722 726458845 85output
## TOTAL est est.var NBRPLT.gt0 AREAUSED est.se est.cv
## 1 1 13600351582 4.013324e+17 487 62600430 633508003 0.04658027
## pse CI99left CI99right CI95left CI95right CI68left
## 1 4.658027 11968543103 15232160061 12358698712 1.4842e+10 12970354554
## CI68right NBRPLT
## 1 14230348610 3047output
## ESTN_UNIT FORTYPCD Forest type nhat nhat.var
## 1 1 182 Rocky Mountain juniper 0.4333135 0.1979394
## 2 1 201 Douglas-fir 15.9927786 197.6889704
## 3 1 221 Ponderosa pine 33.6483513 248.1857429
## 4 1 266 Engelmann spruce / subalpine fir 66.8269701 727.3782450
## 5 1 268 Subalpine fir 8.7794104 59.5751697
## 6 1 281 Lodgepole pine 44.1639244 440.8727504
## NBRPLT.gt0 AREAUSED est est.var est.se est.cv pse
## 1 1 2757613 1194911 1.505216e+12 1226873 1.0267481 102.67481
## 2 1 2757613 44101894 1.503312e+15 38772565 0.8791587 87.91587
## 3 4 2757613 92789131 1.887311e+15 43443192 0.4681927 46.81927
## 4 4 2757613 184282921 5.531297e+15 74372687 0.4035788 40.35788
## 5 1 2757613 24210216 4.530352e+14 21284623 0.8791587 87.91587
## 6 4 2757613 121787012 3.352586e+15 57901518 0.4754326 47.54326
## CI99left CI99right CI95left CI95right CI68left CI68right
## 1 0 4355125 0 3599537 0 2414984
## 2 0 143973404 0 120094726 5544211 82659577
## 3 0 204691379 7642038 177936224 49586706 135991556
## 4 0 375854268 38515134 330050709 110322417 258243426
## 5 0 79035772 0 65927311 3043555 45376877
## 6 0 270931438 8302123 235271901 64206392 179367633output
## Forest type FORTYPCD est est.var NBRPLT.gt0
## 1 Rocky Mountain juniper 182 103705330 1.936588e+15 22
## 2 Juniper woodland 184 7591935 4.330587e+13 4
## 3 Pinyon / juniper woodland 185 0 0.000000e+00 0
## 4 Douglas-fir 201 1279391473 6.583002e+16 47
## 5 Ponderosa pine 221 1134539402 3.068444e+16 51
## 6 Engelmann spruce 265 1318783736 1.277336e+17 26
## est.se est.cv pse CI99left CI99right CI95left CI95right
## 1 44006682 0.4243435 42.43435 0 217059031 17453818 189956841
## 2 6580719 0.8668040 86.68040 0 24542744 0 20489908
## 3 0 NaN NaN 0 0 0 0
## 4 256573611 0.2005435 20.05435 618501647 1940281299 776516436 1782266510
## 5 175169736 0.1543972 15.43972 683332063 1585746741 791213028 1477865776
## 6 357398338 0.2710060 27.10060 398186623 2239380848 618295865 2019271607
## CI68left CI68right
## 1 59942538 147468122
## 2 1047686 14136183
## 3 0 0
## 4 1024239823 1534543123
## 5 960340477 1308738327
## 6 963366141 1674201331output
## ESTN_UNIT STDSZCD Stand-size class nhat nhat.var NBRPLT.gt0 AREAUSED
## 1 1 1 Large diameter 88.530660 752.979451 9 2757613
## 2 1 2 Medium diameter 81.400543 618.813946 6 2757613
## 3 1 3 Small diameter 10.541634 24.150550 6 2757613
## 4 1 5 Nonstocked 2.519642 5.926747 2 2757613
## 5 3 1 Large diameter 221.138071 4188.940622 8 2021729
## 6 3 2 Medium diameter 6.017125 36.215800 1 2021729
## est est.var est.se est.cv pse CI99left CI99right
## 1 244133298 5.725979e+15 75670200 0.3099544 30.99544 49219780 439046816
## 2 224471197 4.705727e+15 68598302 0.3055996 30.55996 47773681 401168713
## 3 29069746 1.836512e+14 13551795 0.4661821 46.61821 0 63976857
## 4 6948198 4.506953e+13 6713384 0.9662050 96.62050 0 24240730
## 5 447081251 1.712183e+16 130850396 0.2926770 29.26770 110032965 784129537
## 6 12164996 1.480280e+14 12166677 1.0001382 100.01382 0 43504280
## CI95left CI95right CI68left CI68right
## 1 95822432 392444164 168882471.4 319384125
## 2 90020996 358921398 156253074.9 292689319
## 3 2508715 55630777 15593056.4 42546436
## 4 0 20106190 272020.7 13624376
## 5 190619187 703543316 316956042.8 577206459
## 6 0 36011246 65748.4 24264244output
## Stand-size class STDSZCD est est.var NBRPLT.gt0 est.se
## 1 Large diameter 1 10069470451 4.096126e+17 272 640009849
## 2 Medium diameter 2 2745414099 9.257240e+16 102 304257131
## 3 Small diameter 3 648589645 8.557190e+15 95 92505081
## 4 Nonstocked 5 53104874 5.140209e+14 17 22672028
## est.cv pse CI99left CI99right CI95left CI95right CI68left
## 1 0.06355943 6.355943 8420914327 11718026575 8815074197 11323866705 9433007611
## 2 0.11082377 11.082377 1961699664 3529128533 2149081079 3341747118 2442843196
## 3 0.14262497 14.262497 410312346 886866944 467283017 829896273 556597238
## 4 0.42692933 42.692933 0 111504149 8668515 97541233 30558497
## CI68right
## 1 10705933291
## 2 3047985001
## 3 740582052
## 4 75651251output
## ESTN_UNIT FORTYPCD Forest type STDSZCD Stand-size class
## 1 1 182 Rocky Mountain juniper 1 Large diameter
## 2 1 201 Douglas-fir 1 Large diameter
## 3 1 221 Ponderosa pine 1 Large diameter
## 4 1 266 Engelmann spruce / subalpine fir 1 Large diameter
## 5 1 266 Engelmann spruce / subalpine fir 2 Medium diameter
## 6 1 268 Subalpine fir 2 Medium diameter
## nhat nhat.var NBRPLT.gt0 AREAUSED est est.var est.se
## 1 0.4333135 0.1979394 1 2757613 1194911 1.505216e+12 1226873
## 2 15.9927786 197.6889704 1 2757613 44101894 1.503312e+15 38772565
## 3 33.6483513 248.1857429 4 2757613 92789131 1.887311e+15 43443192
## 4 38.1576244 532.2301642 2 2757613 105223961 4.047307e+15 63618447
## 5 28.6693457 300.8404694 2 2757613 79058960 2.287720e+15 47830117
## 6 8.7794104 59.5751697 1 2757613 24210216 4.530352e+14 21284623
## est.cv pse CI99left CI99right CI95left CI95right CI68left CI68right
## 1 1.0267481 102.67481 0 4355125 0 3599537 0 2414984
## 2 0.8791587 87.91587 0 143973404 0 120094726 5544211 82659577
## 3 0.4681927 46.81927 0 204691379 7642038 177936224 49586706 135991556
## 4 0.6046004 60.46004 0 269094220 0 229913825 41958095 168489827
## 5 0.6049930 60.49930 0 202261178 0 172804268 31493923 126623998
## 6 0.8791587 87.91587 0 79035772 0 65927311 3043555 45376877output
## Forest type Stand-size class FORTYPCD STDSZCD est
## 1 Rocky Mountain juniper Large diameter 182 1 85055989
## 2 Rocky Mountain juniper Medium diameter 182 2 16736394
## 3 Rocky Mountain juniper Small diameter 182 3 1912947
## 4 Juniper woodland Large diameter 184 1 7591935
## 5 Juniper woodland Small diameter 184 3 0
## 6 Pinyon / juniper woodland Large diameter 185 1 0
## est.var NBRPLT.gt0 est.se est.cv pse CI99left CI99right
## 1 1.795608e+15 17 42374616 0.4981967 49.81967 0 194205767
## 2 1.391279e+14 3 11795249 0.7047664 70.47664 0 47118942
## 3 2.927804e+12 2 1711083 0.8944747 89.44747 0 6320404
## 4 4.330587e+13 4 6580719 0.8668040 86.68040 0 24542744
## 5 0.000000e+00 0 0 NaN NaN 0 0
## 6 0.000000e+00 0 0 NaN NaN 0 0
## CI95left CI95right CI68left CI68right
## 1 2003267 168108710 42916217.5 127195760
## 2 0 39854658 5006515.8 28466273
## 3 0 5266607 211347.4 3614547
## 4 0 20489908 1047686.2 14136183
## 5 0 0 0.0 0
## 6 0 0 0.0 0output
## [1] "title.estpse" "title.yvar" "title.estvar" "title.unitvar"
## [5] "title.ref" "outfn.estpse" "outfn.rawdat" "outfn.param"
## [9] "title.rowvar" "title.row" "title.colvar" "title.col"
## [13] "title.unit"output
## $title.estpse
## [1] "VOLCFNET_TPA_ADJ_LIVE, in cubic feet (percent sampling error), by forest type and stand-size class on forest land"
##
## $title.yvar
## [1] ", in cubic feet"
##
## $title.estvar
## [1] "VOLCFNET_TPA_ADJ_LIVE"
##
## $title.unitvar
## [1] "ESTN_UNIT"
##
## $title.ref
## [1] "Wyoming, 2011-2013"
##
## $outfn.estpse
## [1] "WY_tree_VOLCFNET_TPA_ADJ_LIVE_FORTYPCD_STDSZCD_forestland"
##
## $outfn.rawdat
## [1] "WY_tree_VOLCFNET_TPA_ADJ_LIVE_FORTYPCD_STDSZCD_forestland_rawdata"
##
## $outfn.param
## [1] "WY_tree_VOLCFNET_TPA_ADJ_LIVE_FORTYPCD_STDSZCD_forestland_parameters"
##
## $title.rowvar
## [1] "Forest type"
##
## $title.row
## [1] "VOLCFNET_TPA_ADJ_LIVE, in cubic feet (percent sampling error), by forest type on forest land; Wyoming, 2011-2013"
##
## $title.colvar
## [1] "Stand-size class"
##
## $title.col
## [1] "VOLCFNET_TPA_ADJ_LIVE, in cubic feet (percent sampling error), by stand-size class on forest land; Wyoming, 2011-2013"
##
## $title.unit
## [1] "cubic feet"output
## [1] "WY_tree_VOLCFNET_TPA_ADJ_LIVE_FORTYPCD_STDSZCD_forestland.csv"output
## [1] "WY_WY_tree_VOLCFNET_TPA_ADJ_LIVE_FORTYPCD_STDSZCD_forestland_rawdata_colest.csv"
## [2] "WY_WY_tree_VOLCFNET_TPA_ADJ_LIVE_FORTYPCD_STDSZCD_forestland_rawdata_domdat.csv"
## [3] "WY_WY_tree_VOLCFNET_TPA_ADJ_LIVE_FORTYPCD_STDSZCD_forestland_rawdata_grpest.csv"
## [4] "WY_WY_tree_VOLCFNET_TPA_ADJ_LIVE_FORTYPCD_STDSZCD_forestland_rawdata_rowest.csv"
## [5] "WY_WY_tree_VOLCFNET_TPA_ADJ_LIVE_FORTYPCD_STDSZCD_forestland_rawdata_totest.csv"
## [6] "WY_WY_tree_VOLCFNET_TPA_ADJ_LIVE_FORTYPCD_STDSZCD_forestland_rawdata_unit_colest.csv"
## [7] "WY_WY_tree_VOLCFNET_TPA_ADJ_LIVE_FORTYPCD_STDSZCD_forestland_rawdata_unit_grpest.csv"
## [8] "WY_WY_tree_VOLCFNET_TPA_ADJ_LIVE_FORTYPCD_STDSZCD_forestland_rawdata_unit_rowest.csv"
## [9] "WY_WY_tree_VOLCFNET_TPA_ADJ_LIVE_FORTYPCD_STDSZCD_forestland_rawdata_unit_totest.csv"POP1: 1.4 Number of live trees by species, Wyoming, 2011-2013
View Example
tree1.4 <- modGBtree(GBpopdat = GBpopdat, # pop - population calculations
landarea = "FOREST", # est - forest land filter
sumunits = TRUE, # est - sum estimation units to population
estvar = "TPA_UNADJ", # est - number of trees per acre
estvar.filter = "STATUSCD == 1", # est - live trees only
rowvar = "SPCD", # est - row domain
returntitle = TRUE, # out - return title information
table_opts = table_options(
row.FIAname = TRUE, # est - row domain names
allin1 = FALSE # out - return output with est and pse
))We can also look at the output list and estimates again:
output
## [1] "est" "titlelst" "raw" "statecd" "states" "invyr"output
## Species Estimate Percent Sampling Error
## 1 19 1175619052 8.41
## 2 65 45255337.2 27.67
## 3 66 108687132.4 19.62
## 4 93 475123944.8 11.85
## 5 96 6731266.5 63.82
## 6 101 237604255.6 15.55
## 7 106 119195 100
## 8 108 1465048754.5 11.32
## 9 113 99305952.7 19.53
## 10 122 262836098.3 15.59
## 11 202 207053203.4 19.39
## 12 313 1126869.5 81.93
## 13 375 1445853.5 107.34
## 14 475 538260.9 69.47
## 15 544 1288927.3 91.98
## 16 745 2027267.7 82.62
## 17 746 253999612.4 18.87
## 18 749 4585746.2 57.8
## 19 823 23604682.5 38.4
## 20 Total 4372001412.4 4.79POP1: 1.5 Number of live trees (including seedlings) by species, Wyoming, 2011-2013
View Example
We can also add seedlings.
Note: seedling data are only available for estimating number of trees (estvar = TPA_UNADJ).
Note: must include seedling data in population data calculations.
tree1.5 <-
modGBtree(GBpopdat = GBpopdat, # pop - population calculations
estseed = "add", # est - add seedling data
landarea = "FOREST", # est - forest land filter
sumunits = TRUE, # est - sum estimation units to population
estvar = "TPA_UNADJ", # est - number of trees per acre
estvar.filter = "STATUSCD == 1", # est - live trees only
rowvar = "SPCD", # est - row domain
returntitle = TRUE, # out - return title information
table_opts = table_options(row.FIAname = TRUE, # est - row domain names
allin1 = FALSE) # out - return output with est and pse
)And again we can look at our outputs and compare estimates:
output
## [1] "est" "titlelst" "raw" "statecd" "states" "invyr"output
## Species Estimate Percent Sampling Error
## 1 19 7622496575.2 8.09
## 2 65 51536534.9 27.08
## 3 66 157822816.9 19.77
## 4 93 1656118117.6 10.39
## 5 96 9597932.4 72.35
## 6 101 1409480053.3 14.49
## 7 106 119195 100
## 8 108 4424197831.1 14.07
## 9 113 471644111.9 18.93
## 10 122 629884743.8 21.66
## 11 202 548747133.5 24.18
## 12 313 5891677.2 96.11
## 13 375 10120975 75.3
## 14 475 538260.9 69.47
## 15 544 4180634.3 79.48
## 16 745 2027267.7 82.62
## 17 746 1870551395.2 16.35
## 18 749 51593597.3 61.75
## 19 823 367717832.4 50.87
## 20 Total 19294266685.6 5.19output
## Species Estimate Percent Sampling Error
## 1 19 1175619052 8.41
## 2 65 45255337.2 27.67
## 3 66 108687132.4 19.62
## 4 93 475123944.8 11.85
## 5 96 6731266.5 63.82
## 6 101 237604255.6 15.55output
## Species Estimate Percent Sampling Error
## 1 19 7622496575.2 8.09
## 2 65 51536534.9 27.08
## 3 66 157822816.9 19.77
## 4 93 1656118117.6 10.39
## 5 96 9597932.4 72.35
## 6 101 1409480053.3 14.49POP1: 1.6 Number of seedlings by species, Wyoming, 2011-2013
View Example
Of course, we can also look at only seedlings.
tree1.6 <- modGBtree(GBpopdat = GBpopdat, # pop - population calculations
estseed = "only", # est - add seedling data
landarea = "FOREST", # est - forest land filter
sumunits = TRUE, # est - sum estimation units to population
estvar = "TPA_UNADJ", # est - number of trees per acre
rowvar = "SPCD", # est - row domain
returntitle = TRUE, # out - return title information
table_opts = table_options(
row.FIAname = TRUE, # est - row domain names
allin1 = FALSE # out - return output with est and pse
))And again we can look at our outputs and compare estimates:
output
## [1] "est" "titlelst" "raw" "statecd" "states" "invyr"output
## Species Estimate Percent Sampling Error
## 1 19 6446877524.5 8.72
## 2 65 6281197.2 49.99
## 3 66 49135684.6 32.32
## 4 93 1180994171.7 11.58
## 5 96 2866665.9 101.99
## 6 101 1171875796.9 15.95
## 7 108 2959149075.2 17.66
## 8 113 372338158.8 20.34
## 9 122 367048644.9 32.58
## 10 202 341693928.8 33.54
## 11 313 4764807.8 100
## 12 375 8675121.5 74.48
## 13 544 2891707 107.34
## 14 746 1616551782.8 17.32
## 15 749 47007851 64.53
## 16 823 344113149.7 53
## 17 Total 14922265268.5 5.99output
## Species Estimate Percent Sampling Error
## 1 19 1175619052 8.41
## 2 65 45255337.2 27.67
## 3 66 108687132.4 19.62
## 4 93 475123944.8 11.85
## 5 96 6731266.5 63.82
## 6 101 237604255.6 15.55output
## Species Estimate Percent Sampling Error
## 1 19 7622496575.2 8.09
## 2 65 51536534.9 27.08
## 3 66 157822816.9 19.77
## 4 93 1656118117.6 10.39
## 5 96 9597932.4 72.35
## 6 101 1409480053.3 14.49output
## Species Estimate Percent Sampling Error
## 1 19 6446877524.5 8.72
## 2 65 6281197.2 49.99
## 3 66 49135684.6 32.32
## 4 93 1180994171.7 11.58
## 5 96 2866665.9 101.99
## 6 101 1171875796.9 15.95POP2: 2.1 Number of live trees by forest type and species on forest land, Bighorn National Forest
View Example
tree2.1 <- modGBtree(GBpopdat = GBpopdat.bh, # pop - population calculations
landarea = "FOREST", # est - forest land filter
sumunits = TRUE, # est - sum estimation units to population
estvar = "TPA_UNADJ", # est - number of trees per acre
estvar.filter = "STATUSCD == 1", # est - live trees only
rowvar = "FORTYPCD", # est - row domain
colvar = "SPCD", # est - column domain
returntitle = TRUE, # out - return title information
table_opts = table_options(
row.FIAname = TRUE, # est - row domain names
col.FIAname = TRUE, # est - column domain names
allin1 = TRUE # out - return output with est(pse)
))And we can see our output:
output
## [1] "est" "titlelst" "raw" "statecd" "states" "invyr"output
## Forest type 19 66
## 1 Douglas-fir -- ( --) -- ( --)
## 2 Engelmann spruce 5,748,668.0 ( 77.02) -- ( --)
## 3 Engelmann spruce / subalpine fir 27,057,507.4 ( 64.52) -- ( --)
## 4 Subalpine fir 11,180,825.6 ( 86.24) -- ( --)
## 5 Lodgepole pine 27,362,519.2 ( 36.76) -- ( --)
## 6 Aspen -- ( --) -- ( --)
## 93 108 113
## 1 -- ( --) -- ( --) 4,283,555.1 ( 97.92)
## 2 13,619,359.8 ( 52.63) 4,641,377.9 ( 98.14) -- ( --)
## 3 12,145,337.2 ( 60.75) -- ( --) 357,822.7 (100.76)
## 4 119,274.3 (100.76) 2,504,759.0 ( 79.85) -- ( --)
## 5 28,612,774.3 ( 44.96) 158,998,728.3 ( 22.59) -- ( --)
## 6 -- ( --) 11,886,153.3 (100.76) -- ( --)
## 202 746 Total
## 1 21,223,387.2 ( 89.14) -- ( --) 11,886,153.3 (100.76)
## 2 3,513,431.2 (100.76) -- ( --) 25,506,942.3 ( 90.53)
## 3 1,431,290.9 ( 79.06) -- ( --) 27,522,836.9 ( 50.80)
## 4 -- ( --) -- ( --) 40,991,958.3 ( 55.71)
## 5 238,548.4 (100.76) 10,052,879.2 ( 84.38) 225,265,449.4 ( 19.47)
## 6 -- ( --) -- ( --) -- ( --)POP2: 2.2 Net cubic-foot volume of standing dead trees by species and cause of death on forest land, Bighorn National Forest
View Example
We can also examine dead trees with the filter
estvar.filter = "STATUSCD == 2 & STANDING_DEAD_CD == 1".
deadtree.filter <- "STATUSCD == 2 & STANDING_DEAD_CD == 1"
tree2.2 <- modGBtree(GBpopdat = GBpopdat.bh, # pop - population calculations
landarea = "FOREST", # est - forest land filter
sumunits = TRUE, # est - sum estimation units to population
estvar = "VOLCFNET", # est - number of trees per acre
estvar.filter = deadtree.filter, # est - standing dead trees only
rowvar = "SPCD", # est - row domain
colvar = "AGENTCD", # est - column domain
returntitle = TRUE, # out - return title information
table_opts = table_options(
row.FIAname = TRUE, # est - row domain names
col.FIAname = TRUE, # est - column domain names
allin1 = TRUE # out - return output with est(pse)
))And we can see our output of dead trees:
output
## [1] "est" "titlelst" "raw" "statecd" "states" "invyr"output
## Species Insect Disease Fire
## 1 19 2,982,393.6 (100.76) 28,505,537.5 ( 62.63) 2,629,756.0 (101.19)
## 2 66 -- ( --) -- ( --) -- ( --)
## 3 93 47,430,545.1 ( 97.66) 3,821,319.6 ( 75.96) 29,761,541.2 (101.19)
## 4 108 3,819,221.4 ( 62.70) 1,334,682.8 (100.76) -- ( --)
## 5 113 -- ( --) -- ( --) 2,363,965.1 (100.76)
## 6 202 -- ( --) -- ( --) -- ( --)
## Unidentified animal Weather Vegetation (e.g., suppression)
## 1 -- ( --) 573,086.4 (101.19) 293,076.1 (100.76)
## 2 -- ( --) -- ( --) -- ( --)
## 3 -- ( --) 937,611.0 (100.76) -- ( --)
## 4 2,740,770.5 ( 84.11) 904,673.0 ( 77.35) -- ( --)
## 5 -- ( --) -- ( --) -- ( --)
## 6 -- ( --) -- ( --) -- ( --)
## Unidentified Other Total
## 1 9,225,808.8 ( 66.35) -- ( --) 2,505,330.2 ( 95.10)
## 2 -- ( --) -- ( --) -- ( --)
## 3 7,016,945.1 ( 75.36) -- ( --) 44,209,658.3 ( 49.92)
## 4 12,381,170.2 ( 55.63) -- ( --) -- ( --)
## 5 141,365.1 (100.76) -- ( --) 88,967,962.0 ( 63.07)
## 6 -- ( --) -- ( --) -- ( --)Adding diameter classes to population tree data (for
modGBtree and modGBratio examples 7-9)
View Example
output
## Key: <PLT_CN, CONDID, SUBP, TREE>
## PLT_CN CONDID SUBP TREE STATUSCD SPCD SPGRPCD DIA HT
## <char> <num> <num> <num> <num> <num> <num> <num> <num>
## 1: 40404876010690 1 1 2 1 108 21 10.2 81
## 2: 40404876010690 1 1 3 1 108 21 9.1 49
## 3: 40404876010690 1 1 5 1 108 21 10.0 61
## 4: 40404876010690 1 1 7 1 108 21 12.9 71
## 5: 40404876010690 1 1 9 1 19 12 12.1 64
## 6: 40404876010690 1 1 14 1 108 21 6.3 29
## TREECLCD AGENTCD STANDING_DEAD_CD VOLCFNET VOLCFGRS VOLBFNET TPA_UNADJ
## <num> <num> <num> <num> <num> <num> <num>
## 1: 2 NA NA 19.676475 19.676475 100.93822 6.018046
## 2: 2 NA NA 8.852893 8.852893 34.97113 6.018046
## 3: 2 NA NA 13.668155 13.668155 63.82976 6.018046
## 4: 2 NA NA 26.086436 26.086436 149.04320 6.018046
## 5: 2 NA NA 19.055442 19.055442 104.72982 6.018046
## 6: 2 NA NA 2.197854 2.197854 NA 6.018046
## DRYBIO_AG CARBON_AG tadjfac
## <num> <num> <num>
## 1: 688.6915 346.41183 1.006135
## 2: 366.9639 184.58284 1.006135
## 3: 529.3556 266.26586 1.006135
## 4: 1008.6610 507.35649 1.006135
## 5: 675.8936 325.78072 1.006135
## 6: 113.8587 57.27094 1.006135output
## MIN MAX DIACL2IN
## 1 1 2.9 1.0-2.9
## 2 3 4.9 3.0-4.9
## 3 5 6.9 5.0-6.9
## 4 7 8.9 7.0-8.9
## 5 9 10.9 9.0-10.9
## 6 11 12.9 11.0-12.9# Appends a new column to GBpopdat$treex classifying the DIA variable based on MIN and MAX columns in ref_diacl2in
dat <- datLUTclass(x = GBpopdat.bh$treex,
xvar = "DIA",
LUT = FIESTAutils::ref_diacl2in,
LUTclassnm = "DIACL2IN")
GBpopdat.bh$treex <- dat$xLUT
# Look at tree data, with new column (DIACL2IN)
head(GBpopdat.bh$treex)output
## PLT_CN CONDID SUBP TREE STATUSCD SPCD SPGRPCD DIA HT TREECLCD
## 1 40404876010690 1 1 2 1 108 21 10.2 81 2
## 2 40404876010690 1 1 3 1 108 21 9.1 49 2
## 3 40404876010690 1 1 5 1 108 21 10.0 61 2
## 4 40404876010690 1 1 7 1 108 21 12.9 71 2
## 5 40404876010690 1 1 9 1 19 12 12.1 64 2
## 6 40404876010690 1 1 14 1 108 21 6.3 29 2
## AGENTCD STANDING_DEAD_CD VOLCFNET VOLCFGRS VOLBFNET TPA_UNADJ DRYBIO_AG
## 1 NA NA 19.676475 19.676475 100.93822 6.018046 688.6915
## 2 NA NA 8.852893 8.852893 34.97113 6.018046 366.9639
## 3 NA NA 13.668155 13.668155 63.82976 6.018046 529.3556
## 4 NA NA 26.086436 26.086436 149.04320 6.018046 1008.6610
## 5 NA NA 19.055442 19.055442 104.72982 6.018046 675.8936
## 6 NA NA 2.197854 2.197854 NA 6.018046 113.8587
## CARBON_AG tadjfac DIACL2IN
## 1 346.41183 1.006135 9.0-10.9
## 2 184.58284 1.006135 9.0-10.9
## 3 266.26586 1.006135 9.0-10.9
## 4 507.35649 1.006135 11.0-12.9
## 5 325.78072 1.006135 11.0-12.9
## 6 57.27094 1.006135 5.0-6.9output
##
## 1.0-2.9 3.0-4.9 5.0-6.9 7.0-8.9 9.0-10.9 11.0-12.9 13.0-14.9 15.0-16.9
## 82 49 602 450 222 121 62 29
## 17.0-18.9 19.0-20.9 21.0-22.9 23.0-24.9 25.0-26.9 27.0-28.9 29.0-30.9 31.0-32.9
## 25 17 7 5 1 1 0 0
## 33.0-34.9 35.0-36.9 37.0-38.9 39.0-40.9 41.0-42.9 43.0-44.9 45.0-46.9 47.0-48.9
## 0 0 0 0 0 0 0 0
## 49.0-50.9 51.0-52.9 53.0-54.9 55.0-56.9 57.0-58.9 59.0-60.9 61.0-62.9 63.0-64.9
## 0 0 0 0 0 0 0 0
## 65.0-66.9 67.0-68.9 69.0-70.9 71.0-72.9 73.0-74.9 75.0-76.9 77.0-78.9 79.0-80.9
## 0 0 0 0 0 0 0 0# Another way to append diameter classes
# First, create a new variable using cut function to define 4 diameter classes
dat <- datLUTclass(x = GBpopdat.bh$treex,
xvar = "DIA",
cutbreaks = c(0, 5, 10, 20, 100))
GBpopdat.bh$treex <- dat$xLUT
# Look at tree data, with new column (DIACL2IN)
head(GBpopdat.bh$treex)output
## PLT_CN CONDID SUBP TREE STATUSCD SPCD SPGRPCD DIA HT TREECLCD
## 1 40404876010690 1 1 2 1 108 21 10.2 81 2
## 2 40404876010690 1 1 3 1 108 21 9.1 49 2
## 3 40404876010690 1 1 5 1 108 21 10.0 61 2
## 4 40404876010690 1 1 7 1 108 21 12.9 71 2
## 5 40404876010690 1 1 9 1 19 12 12.1 64 2
## 6 40404876010690 1 1 14 1 108 21 6.3 29 2
## AGENTCD STANDING_DEAD_CD VOLCFNET VOLCFGRS VOLBFNET TPA_UNADJ DRYBIO_AG
## 1 NA NA 19.676475 19.676475 100.93822 6.018046 688.6915
## 2 NA NA 8.852893 8.852893 34.97113 6.018046 366.9639
## 3 NA NA 13.668155 13.668155 63.82976 6.018046 529.3556
## 4 NA NA 26.086436 26.086436 149.04320 6.018046 1008.6610
## 5 NA NA 19.055442 19.055442 104.72982 6.018046 675.8936
## 6 NA NA 2.197854 2.197854 NA 6.018046 113.8587
## CARBON_AG tadjfac DIACL2IN DIACL
## 1 346.41183 1.006135 9.0-10.9 10-19.9
## 2 184.58284 1.006135 9.0-10.9 5-9.9
## 3 266.26586 1.006135 9.0-10.9 10-19.9
## 4 507.35649 1.006135 11.0-12.9 10-19.9
## 5 325.78072 1.006135 11.0-12.9 10-19.9
## 6 57.27094 1.006135 5.0-6.9 5-9.9output
##
## 0-4.9 5-9.9 10-19.9 20-99.9 100+
## 131 1177 344 21 0POP2: 2.3 Number of Live Trees by Species Groups and Diameter Class on forest land, Bighorn National Forest
View Example
We can also look at the number of live trees by species group and diameter class (DIACL2IN):
tree2.3 <- modGBtree(GBpopdat = GBpopdat.bh, # pop - population calculations
landarea = "FOREST", # est - forest land filter
sumunits = TRUE, # est - sum estimation units to population
estvar = "TPA_UNADJ", # est - number of trees per acre
estvar.filter = "STATUSCD == 1", # est - live trees only
rowvar = "SPGRPCD", # est - row domain
colvar = "DIACL2IN", # est - column domain
returntitle = TRUE, # out - return title information
table_opts = table_options(
row.FIAname = TRUE, # est - row domain names
allin1 = TRUE # out - return output with est(pse)
))Outputs:
output
## [1] "est" "titlelst" "raw" "statecd" "states" "invyr"output
## Species group 1.0-2.9 11.0-12.9
## 1 Douglas-fir 14,857,691.8 (100.76) 119,274.3 (100.76)
## 2 True fir 35,733,107.9 ( 34.02) 1,318,009.6 ( 44.43)
## 3 Engelmann and other spruces 19,538,942.7 ( 52.05) 4,067,309.8 ( 28.16)
## 4 Lodgepole pine 43,087,305.9 ( 36.30) 7,168,439.9 ( 22.35)
## 5 Woodland softwoods -- ( --) -- ( --)
## 6 Other western softwoods 2,971,538.3 (100.76) -- ( --)
## 13.0-14.9 15.0-16.9 17.0-18.9
## 1 357,822.7 ( 74.35) 357,822.7 (100.76) -- ( --)
## 2 119,274.3 (100.76) 122,270.6 (101.19) 119,274.3 (100.76)
## 3 2,045,640.1 ( 39.54) 834,919.8 ( 64.85) 957,190.4 ( 55.17)
## 4 3,226,397.2 ( 30.61) 1,076,464.5 ( 41.49) 834,919.8 ( 74.03)
## 5 -- ( --) -- ( --) -- ( --)
## 6 -- ( --) -- ( --) -- ( --)
## 19.0-20.9 21.0-22.9 23.0-24.9 25.0-26.9
## 1 119,274.3 (100.76) 119,274.3 (100.76) 119,274.3 (100.76) -- ( --)
## 2 -- ( --) -- ( --) -- ( --) -- ( --)
## 3 1,079,460.8 ( 42.09) 119,274.3 (100.76) 244,541.0 (101.19) -- ( --)
## 4 357,822.7 ( 74.35) -- ( --) 119,274.3 (100.76) -- ( --)
## 5 -- ( --) -- ( --) -- ( --) -- ( --)
## 6 -- ( --) -- ( --) -- ( --) -- ( --)
## 27.0-28.9 3.0-4.9 5.0-6.9 7.0-8.9
## 1 -- ( --) 5,943,076.6 ( 60.40) 2,146,936.4 ( 46.77) 1,550,565.3 ( 60.21)
## 2 -- ( --) 23,772,306.9 ( 41.20) 6,461,783.1 ( 32.38) 2,862,582.3 ( 36.05)
## 3 -- ( --) 7,428,845.7 ( 59.10) 8,247,900.7 ( 29.96) 6,458,787.2 ( 34.84)
## 4 -- ( --) 34,284,662.9 ( 34.68) 37,267,497.1 ( 24.24) 32,818,394.4 ( 21.39)
## 5 -- ( --) -- ( --) -- ( --) -- ( --)
## 6 -- ( --) -- ( --) 1,192,742.3 ( 82.60) 357,822.7 ( 74.35)
## 9.0-10.9 Total
## 1 715,645.7 ( 56.70) -- ( --)
## 2 840,912.8 ( 36.35) 26,406,658.4 ( 72.43)
## 3 3,473,934.7 ( 36.36) 54,496,747.2 ( 28.35)
## 4 17,909,114.6 ( 20.24) 178,150,293.3 ( 20.41)
## 5 -- ( --) 10,172,153.7 ( 83.36)
## 6 119,274.3 (100.76) 71,349,521.8 ( 30.27)POP2: 2.4 Number of Live Trees by Species Groups and a Different Diameter Class on forest land, Bighorn National Forest
View Example
Next, we can look at number of live trees by species group and diameter class (DIACL):
tree2.4 <- modGBtree(GBpopdat = GBpopdat.bh, # pop - population calculations
landarea = "FOREST", # est - forest land filter
sumunits = TRUE, # est - sum estimation units to population
estvar = "TPA_UNADJ", # est - number of trees per acre
estvar.filter = "STATUSCD == 1", # est - live trees only
rowvar = "SPGRPCD", # est - row domain
colvar = "DIACL", # est - column domain
returntitle = TRUE, # out - return title information
table_opts = table_options(
row.FIAname = TRUE, # est - row domain names
allin1 = TRUE # out - return output with est(pse)
))Outputs:
output
## [1] "est" "titlelst" "raw" "statecd" "states" "invyr"output
## Species group 0-4.9 10-19.9
## 1 Douglas-fir 20,800,768.4 ( 86.59) 1,192,742.5 ( 47.37)
## 2 True fir 59,505,414.9 ( 31.91) 1,798,103.0 ( 38.15)
## 3 Engelmann and other spruces 26,967,788.8 ( 45.56) 10,415,811.0 ( 29.66)
## 4 Lodgepole pine 77,371,969.0 ( 30.20) 19,823,495.2 ( 20.78)
## 5 Woodland softwoods -- ( --) -- ( --)
## 6 Other western softwoods 2,971,538.3 (100.76) 119,274.3 (100.76)
## 20-99.9 5-9.9 Total
## 1 357,822.7 ( 74.35) 4,055,324.4 ( 51.25) -- ( --)
## 2 -- ( --) 10,046,003.3 ( 31.06) 26,406,658.0 ( 72.43)
## 3 727,630.6 ( 71.82) 16,385,515.6 ( 32.40) 54,496,746.0 ( 28.35)
## 4 238,548.6 ( 70.35) 80,716,281.0 ( 21.10) 178,150,293.7 ( 20.41)
## 5 -- ( --) -- ( --) 10,172,153.5 ( 83.36)
## 6 -- ( --) 1,550,565.3 ( 80.36) 71,349,521.2 ( 30.27)POP2: 2.5 Number of Live Trees (+ seedlings) by Species Groups and a Different Diameter Class on forest land, Bighorn National Forest
View Example
Finally, we add seedlings to Example 8:
tree2.5 <-
modGBtree(GBpopdat = GBpopdat.bh, # pop - population calculations
estseed = "add", # est - add seedling data
landarea = "FOREST", # est - forest land filter
sumunits = TRUE, # est - sum estimation units to population
estvar = "TPA_UNADJ", # est - number of trees per acre
estvar.filter = "STATUSCD == 1", # est - live trees only
rowvar = "SPGRPCD", # est - row domain
colvar = "DIACL", # est - column domain
returntitle = TRUE, # out - return title information
table_opts = table_options(row.FIAname = TRUE, # est - row domain names
allin1 = TRUE) # out - return output with est(pse)
)And look at the outputs:
output
## [1] "est" "titlelst" "raw" "statecd" "states" "invyr"output
## Species group 0-4.9 10-19.9
## 1 Douglas-fir 20,800,768.4 ( 86.59) 1,192,742.5 ( 47.37)
## 2 True fir 59,505,414.9 ( 31.91) 1,798,103.0 ( 38.15)
## 3 Engelmann and other spruces 26,967,788.8 ( 45.56) 10,415,811.0 ( 29.66)
## 4 Lodgepole pine 77,371,969.0 ( 30.20) 19,823,495.2 ( 20.78)
## 5 Woodland softwoods -- ( --) -- ( --)
## 6 Other western softwoods 2,971,538.3 (100.76) 119,274.3 (100.76)
## 20-99.9 5-9.9 Total
## 1 357,822.7 ( 74.35) 4,055,324.4 ( 51.25) -- ( --)
## 2 -- ( --) 10,046,003.3 ( 31.06) 51,664,734.0 ( 80.14)
## 3 727,630.6 ( 71.82) 16,385,515.6 ( 32.40) 124,925,080.4 ( 31.82)
## 4 238,548.6 ( 70.35) 80,716,281.0 ( 21.10) 251,027,631.3 ( 19.11)
## 5 -- ( --) -- ( --) 87,432,150.8 ( 76.13)
## 6 -- ( --) 1,550,565.3 ( 80.36) 410,709,267.1 ( 24.79)POP3: 3.1 Volume of Dead Trees by Forest Type Group and Primary Disturbance on forest land, Bighorn National Forest Districts
View Example
deadtree.filter <- "STATUSCD == 2 & STANDING_DEAD_CD == 1"
tree3.1 <- modGBtree(GBpopdat = GBpopdat.bhdist, # pop - population calculations
landarea = "FOREST", # est - forest land filter
sumunits = FALSE, # est - sum estimation units to population
estvar = "VOLCFNET", # est - number of trees per acre
estvar.filter = deadtree.filter, # est - only dead trees
rowvar = "FORTYPGRPCD", # est - row domain
returntitle = TRUE, # out - return title information
table_opts = table_options(
row.FIAname = TRUE, # est - row domain names
allin1 = TRUE # out - return output with est(pse)
))Outputs:
output
## [1] "est" "titlelst" "raw" "statecd" "states" "invyr"output
## Forest-type group Medicine Wheel Ranger District
## 1 Douglas-fir group 182,083.8 ( 97.68)
## 2 Fir / spruce / mountain hemlock group 148,461,368.7 ( 48.08)
## 3 Lodgepole pine group 33,776,650.8 ( 54.79)
## 4 Aspen / birch / group -- ( --)
## 5 Nonstocked -- ( --)
## 6 Total 182,420,103.3 ( 37.56)
## Powder River Ranger District Tongue Ranger District
## 1 -- ( --) -- ( --)
## 2 64,537,347.3 ( 81.37) 436,728.7 (104.01)
## 3 11,612,957.3 ( 70.00) 28,663,666.9 ( 28.27)
## 4 8,948,775.3 ( 99.63) -- ( --)
## 5 -- ( --) 2,327,938.3 (104.01)
## 6 100,144,561.6 ( 53.89) 31,428,333.9 ( 25.75)output
## DISTRICTNA FORTYPGRPCD
## 1 Medicine Wheel Ranger District 200
## 2 Medicine Wheel Ranger District 260
## 3 Medicine Wheel Ranger District 280
## 4 Powder River Ranger District 260
## 5 Powder River Ranger District 280
## 6 Powder River Ranger District 900
## 7 Tongue Ranger District 260
## 8 Tongue Ranger District 280
## 9 Tongue Ranger District 999
## Forest-type group nhat nhat.var NBRPLT.gt0
## 1 Douglas-fir group 0.4995129 2.380862e-01 1
## 2 Fir / spruce / mountain hemlock group 407.2759306 3.834984e+04 5
## 3 Lodgepole pine group 92.6599088 2.577884e+03 5
## 4 Fir / spruce / mountain hemlock group 193.0327470 2.467329e+04 3
## 5 Lodgepole pine group 34.7346328 5.911544e+02 3
## 6 Aspen / birch / group 26.7660006 7.111824e+02 1
## 7 Fir / spruce / mountain hemlock group 1.0554742 1.205070e+00 1
## 8 Lodgepole pine group 69.2735787 3.834289e+02 13
## 9 Nonstocked 5.6260987 3.423984e+01 1
## AREAUSED est est.var est.se est.cv pse CI99left
## 1 364522.8 182083.8 3.163615e+10 177865.5 0.9768332 97.68332 0
## 2 364522.8 148461368.7 5.095808e+15 71384926.4 0.4808317 48.08317 0
## 3 364522.8 33776650.8 3.425413e+14 18507870.1 0.5479486 54.79486 0
## 4 334333.7 64537347.3 2.757956e+15 52516242.6 0.8137341 81.37341 0
## 5 334333.7 11612957.3 6.607865e+13 8128877.3 0.6999834 69.99834 0
## 6 334333.7 8948775.3 7.949526e+13 8916011.3 0.9963387 99.63387 0
## 7 413774.9 436728.7 2.063196e+11 454224.2 1.0400602 104.00602 0
## 8 413774.9 28663666.9 6.564674e+13 8102267.3 0.2826668 28.26668 7793609
## 9 413774.9 2327938.3 5.862191e+12 2421196.1 1.0400602 104.00602 0
## CI99right CI95left CI95right CI68left CI68right
## 1 640235.1 0 530693.9 5204.047 358963.6
## 2 332336753.8 8549484 288373253.4 77472065.888 219450671.4
## 3 81449764.8 0 70051409.5 15371353.487 52181948.0
## 4 199810223.8 0 167467291.3 12312155.867 116762538.7
## 5 32551557.7 0 27545264.1 3529131.211 19696783.5
## 6 31914898.4 0 26423836.3 82177.566 17815373.0
## 7 1606732.6 0 1326991.7 0.000 888435.5
## 8 49533724.4 12783515 44543819.0 20606303.257 36721030.5
## 9 8564526.2 0 7073395.5 0.000 4735715.9POP4: 4.1 Net cubic-foot volume of live trees by forest type group and stand-size class, Rhode Island, 2019
View Example
tree4.1 <-
modGBtree(GBpopdat = GBpopdat.RI, # pop - population calculations
landarea = "FOREST", # est - forest land filter
sumunits = TRUE, # est - sum estimation units to population
estvar = "VOLCFNET", # est - net cubic-foot volume estimate
estvar.filter = "STATUSCD == 1", # est - live trees only
rowvar = "FORTYPCD", # est - row domain
colvar = "STDSZCD", # est - column domain
returntitle = TRUE, # out - return title information
table_opts = table_options(row.FIAname = TRUE, # est - row domain names
col.FIAname = TRUE, # est - column domain names
allin1 = TRUE) # out - return output with est(pse)
)Outputs:
output
## [1] "est" "titlelst" "raw" "statecd" "states" "invyr"output
## Forest type Large diameter
## 1 Eastern white pine 111,564,015.5 ( 34.27)
## 2 Eastern hemlock 3,935,773.9 ( 95.01)
## 3 Pitch pine 29,414,660.9 ( 56.42)
## 4 Eastern white pine / northern red oak / white ash 44,820,940.9 ( 51.95)
## 5 Other pine / hardwood 1,692,470.3 ( 94.75)
## 6 Chestnut oak -- ( --)
## Medium diameter Small diameter Nonstocked Total
## 1 -- ( --) -- ( --) -- ( --) 111,564,015.5 ( 34.27)
## 2 -- ( --) -- ( --) -- ( --) 3,935,773.9 ( 95.01)
## 3 -- ( --) -- ( --) -- ( --) 29,414,660.9 ( 56.42)
## 4 1,921,936.2 ( 69.09) -- ( --) -- ( --) 46,742,877.1 ( 50.82)
## 5 -- ( --) -- ( --) -- ( --) 1,692,470.3 ( 94.75)
## 6 5,958,482.8 ( 96.42) -- ( --) -- ( --) 5,958,482.8 ( 96.42)modGBratio
FIESTA‘s modGBratio function generates
per-acre and per-tree estimates based on Scott et al. 2005 (’the
green-book’) for mapped forest inventory plots. The ratio estimator for
estimating per-acre or per-tree by stratum and domain is used, referred
to as Ratio of Means (ROM).
If there are more than one estimation unit (i.e., subpopulation) within the population, estimates are generated by estimation unit. If sumunits = TRUE, the estimates and percent standard errors returned are a sum combination of all estimation units. If rawdata = TRUE, the raw data returned will include estimates by estimation unit.
Parameters defined in the following examples are organized by category: population data (pop); estimation information (est); and output details (out).
POP1: 1.1 Net cubic-foot volume per acre of live trees on timberland, Wyoming, 2011-2013
View Example
We generate estimates by estimation unit (i.e., ESTN_UNIT) and sum to population (i.e., WY):
ratio1.1 <-
modGBratio(GBpopdat = GBpopdat, # pop - population calculations
landarea = "TIMBERLAND", # est - forest land filter
sumunits = TRUE, # est - sum estimation units to population
estvarn = "VOLCFNET", # est - net cubic-foot volume, numerator
estvarn.filter = "STATUSCD == 1", # est - live trees only, numerator
returntitle = TRUE) # out - return title informationAnd we can look at our output:
output
## [1] "est" "titlelst" "raw"output
## TOTAL Estimate Percent Sampling Error
## 1 Total 1580 4.83# Raw data (list object) for estimate
raw1.1 <- ratio1.1$raw # extract raw data list object from output
names(raw1.1)output
## [1] "unit_totest" "totest" "domdatn" "domdatd"
## [5] "domdatnqry" "domdatdqry" "estvarn" "estvarn.filter"
## [9] "estvard" "module" "esttype" "GBmethod"
## [13] "rowvar" "colvar" "areaunits" "estunitsn"output
## ESTN_UNIT nhat nhat.var dhat dhat.var covar NBRPLT.gt0
## 1 1 180.53243 595.2094 0.16708433 3.208604e-04 0.2137592 18
## 12 3 194.14631 4655.9080 0.07623130 5.037465e-04 1.2514308 7
## 21 5 20.13921 136.5325 0.04111842 2.311568e-04 0.1144213 8
## 22 7 207.93507 670.3878 0.12439229 8.557688e-05 0.1352108 30
## 23 9 59.27104 497.7183 0.06862512 1.925392e-04 0.1316325 11
## 2 11 330.89121 3992.6523 0.24597749 6.412162e-04 0.7076197 25
## AREAUSED estn estd estn.var estn.se estn.cv estn.pse
## 1 2757613 497838569 460753.9 4.526228e+15 67277249 0.1351387 13.51387
## 12 2021729 392511234 154119.0 1.903050e+16 137951090 0.3514577 35.14577
## 21 3072988 61887538 126356.4 1.289311e+15 35906982 0.5801973 58.01973
## 22 5096959 1059836526 634022.4 1.741600e+16 131969693 0.1245189 12.45189
## 23 2729653 161789382 187322.8 3.708502e+15 60897470 0.3763997 37.63997
## 2 1837124 607888182 451891.1 1.347530e+16 116083159 0.1909614 19.09614
## estd.var estd.se estd.cv estd.pse est.covar rhat rhat.var
## 1 2439960647 49395.96 0.10720681 10.720681 1.625517e+12 1080.4869 18192.04
## 12 2059007401 45376.29 0.29442363 29.442363 5.115083e+12 2546.8057 266556.49
## 21 2182872251 46721.22 0.36975739 36.975739 1.080510e+12 489.7855 47258.36
## 22 2223200929 47150.83 0.07436777 7.436777 3.512641e+12 1671.6073 29565.11
## 23 1434610660 37876.25 0.20219781 20.219781 9.807947e+11 863.6931 87901.88
## 2 2164120339 46520.11 0.10294538 10.294538 2.388234e+12 1345.2093 53701.35
## rhat.se rhat.cv pse CI99left CI99right CI95left CI95right
## 1 134.8779 0.1248307 12.48307 733.0645 1427.909 816.13106 1344.8427
## 12 516.2911 0.2027210 20.27210 1216.9279 3876.683 1534.89371 3558.7176
## 21 217.3899 0.4438471 44.38471 0.0000 1049.745 63.70917 915.8618
## 22 171.9451 0.1028621 10.28621 1228.7062 2114.509 1334.60116 2008.6135
## 23 296.4825 0.3432730 34.32730 100.0047 1627.381 282.59804 1444.7881
## 2 231.7355 0.1722673 17.22673 748.2982 1942.120 891.01604 1799.4026
## CI68left CI68right NBRPLT
## 1 946.3565 1214.6172 133
## 12 2033.3759 3060.2354 98
## 21 273.6004 705.9706 152
## 22 1500.6152 1842.5995 245
## 23 568.8537 1158.5324 133
## 2 1114.7581 1575.6605 85output
## TOTAL estn estn.var NBRPLT.gt0 AREAUSED estd estd.var
## 1 1 8828144235 3.047333e+17 280 54457532 5587398 54138597407
## est.covar rhat rhat.var rhat.se rhat.cv pse CI99left CI99right
## 1 8.177073e+13 1580.01 5813.426 76.24582 0.04825655 4.825655 1383.614 1776.406
## CI95left CI95right CI68left CI68right NBRPLT
## 1 1430.571 1729.449 1504.187 1655.833 3047output
## [1] "title.estpse" "title.yvar" "title.estvar" "title.yvard"
## [5] "title.unitvar" "title.ref" "outfn.estpse" "outfn.rawdat"
## [9] "outfn.param" "title.tot" "title.unitsn" "title.unitsd"output
## $title.estpse
## [1] "VOLCFNET_TPA_ADJ_LIVE per acre, in cubic feet, and percent sampling error on timberland"
##
## $title.yvar
## [1] ", in cubic feet"
##
## $title.estvar
## [1] "VOLCFNET_TPA_ADJ_LIVE per acre"
##
## $title.yvard
## [1] "Acres"
##
## $title.unitvar
## [1] "ESTN_UNIT"
##
## $title.ref
## [1] "Wyoming, 2011-2013"
##
## $outfn.estpse
## [1] "ratio_VOLCFNET_TPA_ADJ_LIVE_ESTIMATED_VALUE_timberland"
##
## $outfn.rawdat
## [1] "ratio_VOLCFNET_TPA_ADJ_LIVE_ESTIMATED_VALUE_timberland_rawdata"
##
## $outfn.param
## [1] "ratio_VOLCFNET_TPA_ADJ_LIVE_ESTIMATED_VALUE_timberland_parameters"
##
## $title.tot
## [1] "VOLCFNET_TPA_ADJ_LIVE per acre, in cubic feet, on timberland; Wyoming, 2011-2013"
##
## $title.unitsn
## [1] "cubic feet"
##
## $title.unitsd
## [1] "acres"POP1: 1.2 Net cubic-foot volume per acre of live trees by forest type on timberland, Wyoming, 2011-2013
View Example
ratio1.2 <-
modGBratio(GBpopdat = GBpopdat, # pop - population calculations
landarea = "TIMBERLAND", # est - forest land filter
sumunits = TRUE, # est - sum estimation units to population
estvarn = "VOLCFNET", # est - net cubic-foot volume
estvarn.filter = "STATUSCD == 1", # est - live trees only
rowvar = "FORTYPCD", # est - row domain
returntitle = TRUE) # out - return title informationAnd of course view our outputs:
output
## [1] "est" "titlelst" "raw"output
## Forest type Estimate Percent Sampling Error
## 1 201 1492.1 12.74
## 2 221 1275.4 10.25
## 3 265 2912.6 16.69
## 4 266 2456.7 8.5
## 5 268 1916.1 10.32
## 6 269 2861.1 0# Raw data (list object) for estimate
raw1.2 <- ratio1.2$raw # extract raw data list object from output
names(raw1.2)output
## [1] "unit_totest" "totest" "unit_rowest" "rowest"
## [5] "domdatn" "domdatd" "domdatnqry" "domdatdqry"
## [9] "estvarn" "estvarn.filter" "estvard" "module"
## [13] "esttype" "GBmethod" "rowvar" "colvar"
## [17] "areaunits" "estunitsn"output
## ESTN_UNIT nhat nhat.var dhat dhat.var covar NBRPLT.gt0
## 1 1 180.53243 595.2094 0.16708433 3.208604e-04 0.2137592 18
## 12 3 194.14631 4655.9080 0.07623130 5.037465e-04 1.2514308 7
## 21 5 20.13921 136.5325 0.04111842 2.311568e-04 0.1144213 8
## 22 7 207.93507 670.3878 0.12439229 8.557688e-05 0.1352108 30
## 23 9 59.27104 497.7183 0.06862512 1.925392e-04 0.1316325 11
## 2 11 330.89121 3992.6523 0.24597749 6.412162e-04 0.7076197 25
## AREAUSED estn estd estn.var estn.se estn.cv estn.pse
## 1 2757613 497838569 460753.9 4.526228e+15 67277249 0.1351387 13.51387
## 12 2021729 392511234 154119.0 1.903050e+16 137951090 0.3514577 35.14577
## 21 3072988 61887538 126356.4 1.289311e+15 35906982 0.5801973 58.01973
## 22 5096959 1059836526 634022.4 1.741600e+16 131969693 0.1245189 12.45189
## 23 2729653 161789382 187322.8 3.708502e+15 60897470 0.3763997 37.63997
## 2 1837124 607888182 451891.1 1.347530e+16 116083159 0.1909614 19.09614
## estd.var estd.se estd.cv estd.pse est.covar rhat rhat.var
## 1 2439960647 49395.96 0.10720681 10.720681 1.625517e+12 1080.4869 18192.04
## 12 2059007401 45376.29 0.29442363 29.442363 5.115083e+12 2546.8057 266556.49
## 21 2182872251 46721.22 0.36975739 36.975739 1.080510e+12 489.7855 47258.36
## 22 2223200929 47150.83 0.07436777 7.436777 3.512641e+12 1671.6073 29565.11
## 23 1434610660 37876.25 0.20219781 20.219781 9.807947e+11 863.6931 87901.88
## 2 2164120339 46520.11 0.10294538 10.294538 2.388234e+12 1345.2093 53701.35
## rhat.se rhat.cv pse CI99left CI99right CI95left CI95right
## 1 134.8779 0.1248307 12.48307 733.0645 1427.909 816.13106 1344.8427
## 12 516.2911 0.2027210 20.27210 1216.9279 3876.683 1534.89371 3558.7176
## 21 217.3899 0.4438471 44.38471 0.0000 1049.745 63.70917 915.8618
## 22 171.9451 0.1028621 10.28621 1228.7062 2114.509 1334.60116 2008.6135
## 23 296.4825 0.3432730 34.32730 100.0047 1627.381 282.59804 1444.7881
## 2 231.7355 0.1722673 17.22673 748.2982 1942.120 891.01604 1799.4026
## CI68left CI68right NBRPLT
## 1 946.3565 1214.6172 133
## 12 2033.3759 3060.2354 98
## 21 273.6004 705.9706 152
## 22 1500.6152 1842.5995 245
## 23 568.8537 1158.5324 133
## 2 1114.7581 1575.6605 85output
## TOTAL estn estn.var NBRPLT.gt0 AREAUSED estd estd.var
## 1 1 8828144235 3.047333e+17 280 54457532 5587398 54138597407
## est.covar rhat rhat.var rhat.se rhat.cv pse CI99left CI99right
## 1 8.177073e+13 1580.01 5813.426 76.24582 0.04825655 4.825655 1383.614 1776.406
## CI95left CI95right CI68left CI68right NBRPLT
## 1 1430.571 1729.449 1504.187 1655.833 3047output
## ESTN_UNIT Forest type nhat nhat.var dhat dhat.var covar
## 1 1 201 15.992779 197.68897 0.01023188 0.0000809180 0.12647765
## 2 1 221 33.648351 248.18574 0.03239380 0.0002137597 0.17875130
## 3 1 266 66.826970 727.37825 0.04092751 0.0002629835 0.42940294
## 4 1 268 8.779410 59.57517 0.01023188 0.0000809180 0.06943129
## 5 1 281 44.163924 440.87275 0.03854903 0.0002367898 0.28843941
## 6 1 901 8.753505 23.80886 0.02760699 0.0002055134 0.06500960
## NBRPLT.gt0 AREAUSED estn estd estn.var estn.se estn.cv
## 1 1 2757613 44101894 28215.56 1.503312e+15 38772565 0.8791587
## 2 4 2757613 92789131 89329.58 1.887311e+15 43443192 0.4681927
## 3 4 2757613 184282921 112862.22 5.531297e+15 74372687 0.4035788
## 4 1 2757613 24210216 28215.56 4.530352e+14 21284623 0.8791587
## 5 4 2757613 121787012 106303.32 3.352586e+15 57901518 0.4754326
## 6 3 2757613 24138781 76129.41 1.810528e+14 13455587 0.5574261
## estn.pse estd.var estd.se estd.cv estd.pse est.covar rhat
## 1 87.91587 615335251 24805.95 0.8791587 87.91587 9.617904e+11 1563.0348
## 2 46.81927 1625520387 40317.74 0.4513370 45.13370 1.359302e+12 1038.7280
## 3 40.35788 1999839565 44719.57 0.3962315 39.62315 3.265364e+12 1632.8132
## 4 87.91587 615335251 24805.95 0.8791587 87.91587 5.279853e+11 858.0450
## 5 47.54326 1800651626 42434.09 0.3991793 39.91793 2.193417e+12 1145.6558
## 6 55.74261 1562811900 39532.42 0.5192792 51.92792 4.943609e+11 317.0756
## rhat.var rhat.se rhat.cv pse CI99left CI99right
## 1 6.280479e-10 2.506088e-05 1.603348e-08 1.603348e-06 1563.0347 1563.035
## 2 1.024197e+05 3.200309e+02 3.080988e-01 3.080988e+01 214.3831 1863.073
## 3 1.566717e+04 1.251686e+02 7.665824e-02 7.665824e+00 1310.4003 1955.226
## 4 1.570120e-10 1.253044e-05 1.460348e-08 1.460348e-06 858.0450 858.045
## 5 6.107643e+04 2.471365e+02 2.157162e-01 2.157162e+01 509.0744 1782.237
## 6 4.257232e+03 6.524746e+01 2.057789e-01 2.057789e+01 149.0093 485.142
## CI95left CI95right CI68left CI68right
## 1 1563.0347 1563.0348 1563.0347 1563.0348
## 2 411.4791 1665.9769 720.4708 1356.9852
## 3 1387.4873 1878.1391 1508.3383 1757.2881
## 4 858.0450 858.0450 858.0450 858.0450
## 5 661.2772 1630.0344 899.8890 1391.4226
## 6 189.1930 444.9583 252.1898 381.9615output
## Forest type estn estn.var NBRPLT.gt0 estd estd.var
## 1 201 987424288 4.415994e+16 36 661754.69 12118625799
## 2 221 1134539402 3.068444e+16 51 889542.77 13008784420
## 3 265 811749127 6.669341e+16 16 278701.09 5375334483
## 4 266 2213290055 1.285690e+17 45 900929.05 15512198557
## 5 268 1193505511 5.405617e+16 33 622891.26 10860191917
## 6 269 54704348 3.112642e+15 1 19119.96 380241334
## est.covar rhat rhat.var rhat.se rhat.cv pse
## 1 1.853821e+13 1492.130 3.612229e+04 1.900586e+02 1.273740e-01 1.273740e+01
## 2 1.502013e+13 1275.419 1.710105e+04 1.307710e+02 1.025318e-01 1.025318e+01
## 3 1.612603e+13 2912.616 2.363236e+05 4.861312e+02 1.669054e-01 1.669054e+01
## 4 3.801428e+13 2456.675 4.362790e+04 2.088729e+02 8.502261e-02 8.502261e+00
## 5 2.055507e+13 1916.074 3.906647e+04 1.976524e+02 1.031549e-01 1.031549e+01
## 6 1.087913e+12 2861.112 2.735433e-09 5.230137e-05 1.828008e-08 1.828008e-06
## CI99left CI99right CI95left CI95right CI68left CI68right
## 1 1002.5718 1981.689 1119.622 1864.638 1303.125 1681.136
## 2 938.5749 1612.262 1019.112 1531.725 1145.372 1405.465
## 3 1660.4245 4164.807 1959.816 3865.415 2429.179 3396.053
## 4 1918.6542 2994.696 2047.292 2866.059 2248.960 2664.391
## 5 1406.9548 2425.192 1528.682 2303.465 1719.517 2112.631
## 6 2861.1123 2861.113 2861.112 2861.113 2861.112 2861.113output
## [1] "title.estpse" "title.yvar" "title.estvar" "title.yvard"
## [5] "title.unitvar" "title.ref" "outfn.estpse" "outfn.rawdat"
## [9] "outfn.param" "title.rowvar" "title.row" "title.unitsn"
## [13] "title.unitsd"output
## $title.estpse
## [1] "VOLCFNET_TPA_ADJ_LIVE per acre, in cubic feet, and percent sampling error on timberland by forest type"
##
## $title.yvar
## [1] ", in cubic feet"
##
## $title.estvar
## [1] "VOLCFNET_TPA_ADJ_LIVE per acre"
##
## $title.yvard
## [1] "Acres"
##
## $title.unitvar
## [1] "ESTN_UNIT"
##
## $title.ref
## [1] "Wyoming, 2011-2013"
##
## $outfn.estpse
## [1] "ratio_VOLCFNET_TPA_ADJ_LIVE_ESTIMATED_VALUE_FORTYPCD_timberland"
##
## $outfn.rawdat
## [1] "ratio_VOLCFNET_TPA_ADJ_LIVE_ESTIMATED_VALUE_FORTYPCD_timberland_rawdata"
##
## $outfn.param
## [1] "ratio_VOLCFNET_TPA_ADJ_LIVE_ESTIMATED_VALUE_FORTYPCD_timberland_parameters"
##
## $title.rowvar
## [1] "Forest type"
##
## $title.row
## [1] "VOLCFNET_TPA_ADJ_LIVE per acre, in cubic feet, on timberland by forest type; Wyoming, 2011-2013"
##
## $title.unitsn
## [1] "cubic feet"
##
## $title.unitsd
## [1] "acres"POP1: 1.3 Net cubic-foot volume per acre of live trees by forest type and stand-size class on timberland, Wyoming, 2011-2013
View Example
ratio1.3 <-
modGBratio(GBpopdat = GBpopdat, # pop - population calculations
landarea = "TIMBERLAND", # est - forest land filter
sumunits = TRUE, # est - sum estimation units to population
estvarn = "VOLCFNET", # est - net cubic-foot volume, numerator
estvarn.filter = "STATUSCD == 1", # est - live trees only, numerator
rowvar = "FORTYPCD", # est - row domain
colvar = "STDSZCD", # est - column domain
returntitle = TRUE, # out - return title information
savedata = TRUE, # out - save data to outfolder
table_opts = table_options(row.FIAname = TRUE, # est - row domain names
col.FIAname = TRUE, # est - column domain names
allin1 = TRUE), # out - return output with est(pse)
savedata_opts = savedata_options(outfolder = outfolder, # out - outfolder for saving data
outfn.pre = "WY") # out - prefix for output files
)And look at our output again:
output
## [1] "est" "titlelst" "raw"output
## Forest type Large diameter Medium diameter
## 1 Douglas-fir 1,923.1 (11.46) 845.2 (20.96)
## 2 Ponderosa pine 1,366.3 (10.11) 1,125.9 (42.63)
## 3 Engelmann spruce 3,274.7 (18.15) 2,482.5 (25.35)
## 4 Engelmann spruce / subalpine fir 2,967.4 ( 9.05) 1,854.2 ( 8.26)
## 5 Subalpine fir 2,360.2 ( 8.83) 1,463.4 (23.89)
## 6 Blue spruce 2,861.1 ( --) -- ( --)
## Small diameter Nonstocked Other Total
## 1 268.0 (56.76) -- ( --) -- ( --) 760.5 (26.16)
## 2 124.2 (57.16) -- ( --) -- ( --) 2,861.1 ( --)
## 3 728.8 (25.59) -- ( --) -- ( --) 363.3 (49.34)
## 4 859.0 (23.21) -- ( --) -- ( --) 2,836.3 (20.59)
## 5 410.8 (31.20) -- ( --) -- ( --) 1,492.1 (12.74)
## 6 -- ( --) -- ( --) -- ( --) 133.7 ( --)# Raw data (list object) for estimate
raw1.3 <- ratio1.3$raw # extract raw data list object from output
names(raw1.3)output
## [1] "unit_totest" "totest" "unit_rowest" "rowest"
## [5] "unit_colest" "colest" "unit_grpest" "grpest"
## [9] "domdatn" "domdatd" "domdatnqry" "domdatdqry"
## [13] "estvarn" "estvarn.filter" "estvard" "module"
## [17] "esttype" "GBmethod" "rowvar" "colvar"
## [21] "areaunits" "estunitsn"output
## ESTN_UNIT nhat nhat.var dhat dhat.var covar NBRPLT.gt0
## 1 1 180.53243 595.2094 0.16708433 3.208604e-04 0.2137592 18
## 12 3 194.14631 4655.9080 0.07623130 5.037465e-04 1.2514308 7
## 21 5 20.13921 136.5325 0.04111842 2.311568e-04 0.1144213 8
## 22 7 207.93507 670.3878 0.12439229 8.557688e-05 0.1352108 30
## 23 9 59.27104 497.7183 0.06862512 1.925392e-04 0.1316325 11
## 2 11 330.89121 3992.6523 0.24597749 6.412162e-04 0.7076197 25
## AREAUSED estn estd estn.var estn.se estn.cv estn.pse
## 1 2757613 497838569 460753.9 4.526228e+15 67277249 0.1351387 13.51387
## 12 2021729 392511234 154119.0 1.903050e+16 137951090 0.3514577 35.14577
## 21 3072988 61887538 126356.4 1.289311e+15 35906982 0.5801973 58.01973
## 22 5096959 1059836526 634022.4 1.741600e+16 131969693 0.1245189 12.45189
## 23 2729653 161789382 187322.8 3.708502e+15 60897470 0.3763997 37.63997
## 2 1837124 607888182 451891.1 1.347530e+16 116083159 0.1909614 19.09614
## estd.var estd.se estd.cv estd.pse est.covar rhat rhat.var
## 1 2439960647 49395.96 0.10720681 10.720681 1.625517e+12 1080.4869 18192.04
## 12 2059007401 45376.29 0.29442363 29.442363 5.115083e+12 2546.8057 266556.49
## 21 2182872251 46721.22 0.36975739 36.975739 1.080510e+12 489.7855 47258.36
## 22 2223200929 47150.83 0.07436777 7.436777 3.512641e+12 1671.6073 29565.11
## 23 1434610660 37876.25 0.20219781 20.219781 9.807947e+11 863.6931 87901.88
## 2 2164120339 46520.11 0.10294538 10.294538 2.388234e+12 1345.2093 53701.35
## rhat.se rhat.cv pse CI99left CI99right CI95left CI95right
## 1 134.8779 0.1248307 12.48307 733.0645 1427.909 816.13106 1344.8427
## 12 516.2911 0.2027210 20.27210 1216.9279 3876.683 1534.89371 3558.7176
## 21 217.3899 0.4438471 44.38471 0.0000 1049.745 63.70917 915.8618
## 22 171.9451 0.1028621 10.28621 1228.7062 2114.509 1334.60116 2008.6135
## 23 296.4825 0.3432730 34.32730 100.0047 1627.381 282.59804 1444.7881
## 2 231.7355 0.1722673 17.22673 748.2982 1942.120 891.01604 1799.4026
## CI68left CI68right NBRPLT
## 1 946.3565 1214.6172 133
## 12 2033.3759 3060.2354 98
## 21 273.6004 705.9706 152
## 22 1500.6152 1842.5995 245
## 23 568.8537 1158.5324 133
## 2 1114.7581 1575.6605 85output
## TOTAL estn estn.var NBRPLT.gt0 AREAUSED estd estd.var
## 1 1 8828144235 3.047333e+17 280 54457532 5587398 54138597407
## est.covar rhat rhat.var rhat.se rhat.cv pse CI99left CI99right
## 1 8.177073e+13 1580.01 5813.426 76.24582 0.04825655 4.825655 1383.614 1776.406
## CI95left CI95right CI68left CI68right NBRPLT
## 1 1430.571 1729.449 1504.187 1655.833 3047output
## ESTN_UNIT FORTYPCD Forest type nhat nhat.var
## 1 1 201 Douglas-fir 15.992779 197.68897
## 2 1 221 Ponderosa pine 33.648351 248.18574
## 3 1 266 Engelmann spruce / subalpine fir 66.826970 727.37825
## 4 1 268 Subalpine fir 8.779410 59.57517
## 5 1 281 Lodgepole pine 44.163924 440.87275
## 6 1 901 Aspen 8.753505 23.80886
## dhat dhat.var covar NBRPLT.gt0 AREAUSED estn estd
## 1 0.01023188 0.0000809180 0.12647765 1 2757613 44101894 28215.56
## 2 0.03239380 0.0002137597 0.17875130 4 2757613 92789131 89329.58
## 3 0.04092751 0.0002629835 0.42940294 4 2757613 184282921 112862.22
## 4 0.01023188 0.0000809180 0.06943129 1 2757613 24210216 28215.56
## 5 0.03854903 0.0002367898 0.28843941 4 2757613 121787012 106303.32
## 6 0.02760699 0.0002055134 0.06500960 3 2757613 24138781 76129.41
## estn.var estn.se estn.cv estn.pse estd.var estd.se estd.cv
## 1 1.503312e+15 38772565 0.8791587 87.91587 615335251 24805.95 0.8791587
## 2 1.887311e+15 43443192 0.4681927 46.81927 1625520387 40317.74 0.4513370
## 3 5.531297e+15 74372687 0.4035788 40.35788 1999839565 44719.57 0.3962315
## 4 4.530352e+14 21284623 0.8791587 87.91587 615335251 24805.95 0.8791587
## 5 3.352586e+15 57901518 0.4754326 47.54326 1800651626 42434.09 0.3991793
## 6 1.810528e+14 13455587 0.5574261 55.74261 1562811900 39532.42 0.5192792
## estd.pse est.covar rhat rhat.var rhat.se rhat.cv
## 1 87.91587 9.617904e+11 1563.0348 6.280479e-10 2.506088e-05 1.603348e-08
## 2 45.13370 1.359302e+12 1038.7280 1.024197e+05 3.200309e+02 3.080988e-01
## 3 39.62315 3.265364e+12 1632.8132 1.566717e+04 1.251686e+02 7.665824e-02
## 4 87.91587 5.279853e+11 858.0450 1.570120e-10 1.253044e-05 1.460348e-08
## 5 39.91793 2.193417e+12 1145.6558 6.107643e+04 2.471365e+02 2.157162e-01
## 6 51.92792 4.943609e+11 317.0756 4.257232e+03 6.524746e+01 2.057789e-01
## pse CI99left CI99right CI95left CI95right CI68left CI68right
## 1 1.603348e-06 1563.0347 1563.035 1563.0347 1563.0348 1563.0347 1563.0348
## 2 3.080988e+01 214.3831 1863.073 411.4791 1665.9769 720.4708 1356.9852
## 3 7.665824e+00 1310.4003 1955.226 1387.4873 1878.1391 1508.3383 1757.2881
## 4 1.460348e-06 858.0450 858.045 858.0450 858.0450 858.0450 858.0450
## 5 2.157162e+01 509.0744 1782.237 661.2772 1630.0344 899.8890 1391.4226
## 6 2.057789e+01 149.0093 485.142 189.1930 444.9583 252.1898 381.9615output
## Forest type FORTYPCD estn estn.var NBRPLT.gt0
## 1 Douglas-fir 201 987424288 4.415994e+16 36
## 2 Ponderosa pine 221 1134539402 3.068444e+16 51
## 3 Engelmann spruce 265 811749127 6.669341e+16 16
## 4 Engelmann spruce / subalpine fir 266 2213290055 1.285690e+17 45
## 5 Subalpine fir 268 1193505511 5.405617e+16 33
## 6 Blue spruce 269 54704348 3.112642e+15 1
## estd estd.var est.covar rhat rhat.var rhat.se
## 1 661754.69 12118625799 1.853821e+13 1492.130 3.612229e+04 1.900586e+02
## 2 889542.77 13008784420 1.502013e+13 1275.419 1.710105e+04 1.307710e+02
## 3 278701.09 5375334483 1.612603e+13 2912.616 2.363236e+05 4.861312e+02
## 4 900929.05 15512198557 3.801428e+13 2456.675 4.362790e+04 2.088729e+02
## 5 622891.26 10860191917 2.055507e+13 1916.074 3.906647e+04 1.976524e+02
## 6 19119.96 380241334 1.087913e+12 2861.112 2.735433e-09 5.230137e-05
## rhat.cv pse CI99left CI99right CI95left CI95right CI68left
## 1 1.273740e-01 1.273740e+01 1002.5718 1981.689 1119.622 1864.638 1303.125
## 2 1.025318e-01 1.025318e+01 938.5749 1612.262 1019.112 1531.725 1145.372
## 3 1.669054e-01 1.669054e+01 1660.4245 4164.807 1959.816 3865.415 2429.179
## 4 8.502261e-02 8.502261e+00 1918.6542 2994.696 2047.292 2866.059 2248.960
## 5 1.031549e-01 1.031549e+01 1406.9548 2425.192 1528.682 2303.465 1719.517
## 6 1.828008e-08 1.828008e-06 2861.1123 2861.113 2861.112 2861.113 2861.112
## CI68right
## 1 1681.136
## 2 1405.465
## 3 3396.053
## 4 2664.391
## 5 2112.631
## 6 2861.113output
## ESTN_UNIT STDSZCD Stand-size class nhat nhat.var dhat
## 1 1 1 Large diameter 87.798754 752.714537 0.063089433
## 2 1 2 Medium diameter 81.400543 618.813946 0.061391258
## 3 1 3 Small diameter 8.965642 23.683588 0.035460400
## 4 1 5 Nonstocked 2.367487 5.908853 0.007143242
## 5 3 1 Large diameter 188.129189 4624.910510 0.058381005
## 6 3 2 Medium diameter 6.017125 36.215800 0.007729145
## dhat.var covar NBRPLT.gt0 AREAUSED estn estd estn.var
## 1 3.512849e-04 0.44024129 7 2757613 242114986 173976.24 5.723965e+15
## 2 3.337868e-04 0.44257806 6 2757613 224471197 169293.33 4.705727e+15
## 3 2.376570e-04 0.06312483 4 2757613 24723772 97786.06 1.801002e+14
## 4 5.379211e-05 0.01782834 1 2757613 6528614 19698.30 4.493345e+13
## 5 4.307422e-04 1.35968590 6 2021729 380346238 118030.57 1.890380e+16
## 6 5.975619e-05 0.04652009 1 2021729 12164996 15626.24 1.480280e+14
## estn.se estn.cv estn.pse estd.var estd.se estd.cv estd.pse
## 1 75656887 0.3124833 31.24833 2671321181 51684.83 0.2970798 29.70798
## 2 68598302 0.3055996 30.55996 2538257910 50381.13 0.2975966 29.75966
## 3 13420141 0.5428031 54.28031 1807245526 42511.71 0.4347420 43.47420
## 4 6703242 1.0267481 102.67481 409058305 20225.19 1.0267481 102.67481
## 5 137491107 0.3614893 36.14893 1760610740 41959.63 0.3554980 35.54980
## 6 12166677 1.0001382 100.01382 244246754 15628.40 1.0001382 100.01382
## est.covar rhat rhat.var rhat.se rhat.cv pse CI99left
## 1 3.347784e+12 1391.6555 52187.659 228.44618 0.16415427 16.415427 803.21708
## 2 3.365554e+12 1325.9305 8486.906 92.12440 0.06947906 6.947906 1088.63379
## 3 4.800283e+11 252.8353 5531.559 74.37445 0.29416160 29.416160 61.25946
## 4 1.355743e+11 331.4304 0.000 0.00000 0.00000000 0.000000 331.43036
## 5 5.557564e+12 3222.4383 98222.803 313.40517 0.09725715 9.725715 2415.16011
## 6 1.901456e+11 778.4981 0.000 0.00000 0.00000000 0.000000 778.49815
## CI99right CI95left CI95right CI68left CI68right
## 1 1980.0938 943.9092 1839.4017 1164.4754 1618.8356
## 2 1563.2273 1145.3700 1506.4910 1234.3167 1417.5444
## 3 444.4112 107.0641 398.6066 178.8731 326.7976
## 4 331.4304 331.4304 331.4304 331.4304 331.4304
## 5 4029.7166 2608.1755 3836.7012 2910.7701 3534.1066
## 6 778.4981 778.4981 778.4981 778.4981 778.4981output
## Stand-size class STDSZCD estn estn.var NBRPLT.gt0 estd
## 1 Large diameter 1 6342911970 2.846140e+17 161 2857890.7
## 2 Medium diameter 2 2048714141 7.281225e+16 71 1345938.0
## 3 Small diameter 3 405193762 6.047804e+15 51 1095815.5
## 4 Nonstocked 5 31324363 2.180017e+14 10 287753.9
## estd.var est.covar rhat rhat.var rhat.se rhat.cv pse
## 1 38575741797 8.498903e+13 2219.4383 11922.651 109.19089 0.04919754 4.919754
## 2 22537912872 3.478499e+13 1522.1460 10562.957 102.77625 0.06752062 6.752062
## 3 19643622069 7.399220e+12 369.7646 2716.209 52.11726 0.14094715 14.094715
## 4 5235434732 5.971702e+11 108.8582 1811.887 42.56626 0.39102502 39.102502
## CI99left CI99right CI95left CI95right CI68left CI68right
## 1 1938.1812 2500.6954 2005.42806 2433.4485 2110.8525 2328.0240
## 2 1257.4120 1786.8801 1320.70829 1723.5838 1419.9394 1624.3527
## 3 235.5194 504.0097 267.61661 471.9125 317.9361 421.5930
## 4 0.0000 218.5016 25.42981 192.2865 66.5278 151.1885output
## ESTN_UNIT FORTYPCD Forest type STDSZCD Stand-size class
## 1 1 201 Douglas-fir 1 Large diameter
## 2 1 221 Ponderosa pine 1 Large diameter
## 3 1 266 Engelmann spruce / subalpine fir 1 Large diameter
## 4 1 266 Engelmann spruce / subalpine fir 2 Medium diameter
## 5 1 268 Subalpine fir 2 Medium diameter
## 6 1 281 Lodgepole pine 2 Medium diameter
## nhat nhat.var dhat dhat.var covar NBRPLT.gt0 AREAUSED
## 1 15.99278 197.68897 0.01023188 0.0000809180 0.12647765 1 2757613
## 2 33.64835 248.18574 0.03239380 0.0002137597 0.17875130 4 2757613
## 3 38.15762 532.23016 0.02046375 0.0001517213 0.28290621 2 2757613
## 4 28.66935 300.84047 0.02046375 0.0001517213 0.21255872 2 2757613
## 5 8.77941 59.57517 0.01023188 0.0000809180 0.06943129 1 2757613
## 6 43.95179 441.73879 0.03069563 0.0002124098 0.30414065 3 2757613
## estn estd estn.var estn.se estn.cv estn.pse estd.var
## 1 44101894 28215.56 1.503312e+15 38772565 0.8791587 87.91587 615335251
## 2 92789131 89329.58 1.887311e+15 43443192 0.4681927 46.81927 1625520387
## 3 105223961 56431.11 4.047307e+15 63618447 0.6046004 60.46004 1153753595
## 4 79058960 56431.11 2.287720e+15 47830117 0.6049930 60.49930 1153753595
## 5 24210216 28215.56 4.530352e+14 21284623 0.8791587 87.91587 615335251
## 6 121202020 84646.67 3.359171e+15 57958360 0.4781963 47.81963 1615255033
## estd.se estd.cv estd.pse est.covar rhat rhat.var rhat.se
## 1 24805.95 0.8791587 87.91587 9.617904e+11 1563.035 6.280479e-10 2.506088e-05
## 2 40317.74 0.4513370 45.13370 1.359302e+12 1038.728 1.024197e+05 3.200309e+02
## 3 33966.95 0.6019188 60.19188 2.151340e+12 1864.645 1.124891e+04 1.060609e+02
## 4 33966.95 0.6019188 60.19188 1.616388e+12 1400.982 7.282272e+03 8.533623e+01
## 5 24805.95 0.8791587 87.91587 5.279853e+11 858.045 1.570120e-10 1.253044e-05
## 6 40190.24 0.4748000 47.48000 2.312816e+12 1431.858 6.635926e+03 8.146119e+01
## rhat.cv pse CI99left CI99right CI95left CI95right CI68left
## 1 1.603348e-08 1.603348e-06 1563.0347 1563.035 1563.0347 1563.035 1563.0347
## 2 3.080988e-01 3.080988e+01 214.3831 1863.073 411.4791 1665.977 720.4708
## 3 5.687995e-02 5.687995e+00 1591.4498 2137.839 1656.7690 2072.520 1759.1714
## 4 6.091173e-02 6.091173e+00 1181.1703 1620.793 1233.7259 1568.238 1316.1185
## 5 1.460348e-08 1.460348e-06 858.0450 858.045 858.0450 858.045 858.0450
## 6 5.689194e-02 5.689194e+00 1222.0280 1641.688 1272.1972 1591.519 1350.8484
## CI68right
## 1 1563.035
## 2 1356.985
## 3 1970.118
## 4 1485.845
## 5 858.045
## 6 1512.868output
## Forest type Stand-size class FORTYPCD STDSZCD estn estn.var
## 1 Douglas-fir Large diameter 201 1 866420241 4.205526e+16
## 2 Douglas-fir Medium diameter 201 2 94302693 1.884137e+15
## 3 Douglas-fir Small diameter 201 3 26701354 3.817770e+14
## 4 Ponderosa pine Large diameter 221 1 1074972177 3.072296e+16
## 5 Ponderosa pine Medium diameter 221 2 52603087 1.229672e+15
## 6 Ponderosa pine Small diameter 221 3 6964138 3.497604e+13
## NBRPLT.gt0 estd estd.var est.covar rhat rhat.var rhat.se
## 1 26 450541.00 8124659016 1.618515e+13 1923.0664 48532.613 220.30119
## 2 6 111576.95 2129966306 1.783583e+12 845.1808 31385.970 177.16086
## 3 6 99636.75 1792776867 5.239277e+11 267.9870 23139.530 152.11683
## 4 46 786751.82 11316613869 1.464803e+13 1366.3422 19098.261 138.19646
## 5 3 46720.27 799177795 7.726167e+11 1125.9158 230428.920 480.03012
## 6 3 56070.68 1071721490 1.435580e+11 124.2028 5040.888 70.99921
## rhat.cv pse CI99left CI99right CI95left CI95right CI68left
## 1 0.1145572 11.45572 1355.6081 2490.5246 1491.2840 2354.8488 1703.98612
## 2 0.2096130 20.96130 388.8447 1301.5169 497.9519 1192.4097 669.00177
## 3 0.5676276 56.76276 0.0000 659.8140 0.0000 566.1305 116.71323
## 4 0.1011434 10.11434 1010.3717 1722.3126 1095.4821 1637.2022 1228.91159
## 5 0.4263464 42.63464 0.0000 2362.3915 185.0741 2066.7576 648.54607
## 6 0.5716392 57.16392 0.0000 307.0847 0.0000 263.3587 53.59711
## CI68right
## 1 2142.1466
## 2 1021.3598
## 3 419.2608
## 4 1503.7727
## 5 1603.2855
## 6 194.8086output
## [1] "title.estpse" "title.yvar" "title.estvar" "title.yvard"
## [5] "title.unitvar" "title.ref" "outfn.estpse" "outfn.rawdat"
## [9] "outfn.param" "title.rowvar" "title.row" "title.colvar"
## [13] "title.col" "title.unitsn" "title.unitsd"output
## $title.estpse
## [1] "VOLCFNET_TPA_ADJ_LIVE per acre, in cubic feet (percent sampling error), by forest type and stand-size class on timberland"
##
## $title.yvar
## [1] ", in cubic feet"
##
## $title.estvar
## [1] "VOLCFNET_TPA_ADJ_LIVE per acre"
##
## $title.yvard
## [1] "Acres"
##
## $title.unitvar
## [1] "ESTN_UNIT"
##
## $title.ref
## [1] "Wyoming, 2011-2013"
##
## $outfn.estpse
## [1] "WY_ratio_VOLCFNET_TPA_ADJ_LIVE_ESTIMATED_VALUE_FORTYPCD_STDSZCD_timberland"
##
## $outfn.rawdat
## [1] "WY_ratio_VOLCFNET_TPA_ADJ_LIVE_ESTIMATED_VALUE_FORTYPCD_STDSZCD_timberland_rawdata"
##
## $outfn.param
## [1] "WY_ratio_VOLCFNET_TPA_ADJ_LIVE_ESTIMATED_VALUE_FORTYPCD_STDSZCD_timberland_parameters"
##
## $title.rowvar
## [1] "Forest type"
##
## $title.row
## [1] "VOLCFNET_TPA_ADJ_LIVE per acre, in cubic feet (percent sampling error), by forest type on timberland; Wyoming, 2011-2013"
##
## $title.colvar
## [1] "Stand-size class"
##
## $title.col
## [1] "VOLCFNET_TPA_ADJ_LIVE per acre, in cubic feet (percent sampling error), by stand-size class on timberland; Wyoming, 2011-2013"
##
## $title.unitsn
## [1] "cubic feet"
##
## $title.unitsd
## [1] "acres"POP2: 2.1 Number of live trees per acre by species, Bighorn National Forest
View Example
ratio2.1 <-
modGBratio(GBpopdat = GBpopdat.bh, # pop - population calculations
landarea = "FOREST", # est - forest land filter
sumunits = TRUE, # est - sum estimation units to population
estvarn = "TPA_UNADJ", # est - number of trees per acre, numerator
estvarn.filter = "STATUSCD == 1", # est - live trees only, numerator
rowvar = "SPCD", # est - row domain
returntitle = TRUE, # out - return title information
table_opts = table_options(row.FIAname = TRUE, # est - row domain names
allin1 = FALSE), # out - return output with est and pse
title_opts = title_options(title.ref = "Bighorn National Forest")
)And we can look at our output:
output
## [1] "est" "titlelst" "raw"output
## Species Estimate Percent Sampling Error
## 1 19 107.1 29.07
## 2 66 -- --
## 3 93 81.8 26.99
## 4 108 267.3 18.32
## 5 113 7 90.07
## 6 202 39.7 71.92POP2: 2.2 Number of live trees (including seedlings) per acre by species, Bighorn National Forest
View Example
ratio2.2 <-
modGBratio(GBpopdat = GBpopdat.bh, # pop - population calculations
estseed = "add", # est - add seedling data
landarea = "FOREST", # est - forest land filter
sumunits = TRUE, # est - sum estimation units to population
estvarn = "TPA_UNADJ", # est - number of trees per acre, numerator
estvarn.filter = "STATUSCD == 1", # est - live trees only, numerator
rowvar = "SPCD", # est - row domain
returntitle = TRUE, # out - return title information
table_opts = table_options(row.FIAname = TRUE, # est - row domain names
allin1 = FALSE), # out - return output with est and pse
title_opts = title_options(title.ref = "Bighorn National Forest")
)Output and comparison:
output
## [1] "est" "titlelst" "raw"output
## Species Estimate Percent Sampling Error
## 1 19 616.7 22.55
## 2 66 -- --
## 3 93 187.6 30.53
## 4 108 376.8 17.35
## 5 113 58.3 95.2
## 6 202 77.6 79.66output
## Species Estimate Percent Sampling Error
## 1 19 107.1 29.07
## 2 66 -- --
## 3 93 81.8 26.99
## 4 108 267.3 18.32
## 5 113 7 90.07
## 6 202 39.7 71.92output
## Species Estimate Percent Sampling Error
## 1 19 616.7 22.55
## 2 66 -- --
## 3 93 187.6 30.53
## 4 108 376.8 17.35
## 5 113 58.3 95.2
## 6 202 77.6 79.66POP2: 2.3 Number of live seedlings per acre by species, Bighorn National Forest
View Example
ratio2.3 <-
modGBratio(GBpopdat = GBpopdat.bh, # pop - population calculations
estseed = "only", # est - add seedling data
landarea = "FOREST", # est - forest land filter
sumunits = TRUE, # est - sum estimation units to population
estvarn = "TPA_UNADJ", # est - number of trees per acre, numerator
rowvar = "SPCD", # est - row domain
returntitle = TRUE, # out - return title information
table_opts = table_options(row.FIAname = TRUE, # est - row domain names
allin1 = FALSE) # out - return output with est and pse
)Output and comparisons:
output
## [1] "est" "titlelst" "raw"output
## Species Estimate Percent Sampling Error
## 1 19 509.6 23.22
## 2 93 105.8 38.19
## 3 108 109.4 26.47
## 4 113 51.3 95.96
## 5 202 37.9 88.55
## 6 746 116 83.54output
## Species Estimate Percent Sampling Error
## 1 19 107.1 29.07
## 2 66 -- --
## 3 93 81.8 26.99
## 4 108 267.3 18.32
## 5 113 7 90.07
## 6 202 39.7 71.92output
## Species Estimate Percent Sampling Error
## 1 19 616.7 22.55
## 2 66 -- --
## 3 93 187.6 30.53
## 4 108 376.8 17.35
## 5 113 58.3 95.2
## 6 202 77.6 79.66output
## Species Estimate Percent Sampling Error
## 1 19 509.6 23.22
## 2 93 105.8 38.19
## 3 108 109.4 26.47
## 4 113 51.3 95.96
## 5 202 37.9 88.55
## 6 746 116 83.54POP2: 2.4 Number of live trees by forest type and species, Bighorn National Forest
View Example
ratio2.4 <-
modGBratio(GBpopdat = GBpopdat.bh, # pop - population calculations
landarea = "FOREST", # est - forest land filter
sumunits = TRUE, # est - sum estimation units to population
estvarn = "TPA_UNADJ", # est - number of trees per acre, numerator
estvarn.filter = "STATUSCD == 1", # est - live trees only, numerator
rowvar = "FORTYPCD", # est - row domain
colvar = "SPCD", # est - column domain
returntitle = TRUE, # out - return title information
table_opts = table_options(row.FIAname = TRUE, # est - row domain names
col.FIAname = TRUE, # est - column domain names
allin1 = TRUE) # out - return output with est(pse)
)And view our output:
output
## [1] "est" "titlelst" "raw"output
## Forest type 19 66 93
## 1 Douglas-fir -- ( --) -- ( --) -- ( --)
## 2 Engelmann spruce 88.6 ( 62.90) -- ( --) 209.8 ( 22.86)
## 3 Engelmann spruce / subalpine fir 390.1 ( 36.28) -- ( --) 175.1 ( 47.50)
## 4 Subalpine fir 248.0 ( 61.36) -- ( --) 2.6 ( 73.63)
## 5 Lodgepole pine 67.2 ( 34.42) -- ( --) 70.3 ( 40.77)
## 6 Aspen -- ( --) -- ( --) -- ( --)
## 108 113 202 746 Total
## 1 -- ( --) 108.1 ( 68.11) 535.4 ( 54.74) -- ( --) 643.5 ( 56.98)
## 2 71.5 ( 81.44) -- ( --) 54.1 ( 83.85) -- ( --) 424.0 ( 12.33)
## 3 -- ( --) 5.2 ( 82.44) 20.6 ( 60.31) -- ( --) 590.9 ( 26.06)
## 4 55.5 ( 57.27) -- ( --) -- ( --) -- ( --) 306.2 ( 60.54)
## 5 390.4 ( 15.86) -- ( --) 0.6 (100.61) 24.7 ( 82.69) 553.1 ( 10.85)
## 6 599.7 ( --) -- ( --) -- ( --) -- ( --) 599.7 ( --)POP2: 2.5 Number of standing dead trees by species and cause of death, Bighorn National Forest
View Example
Next, we look at dead trees:
deadtree.filter <- "STATUSCD == 2 & STANDING_DEAD_CD == 1"
ratio2.5 <-
modGBratio(GBpopdat = GBpopdat.bh, # pop - population calculations
landarea = "FOREST", # est - forest land filter
sumunits = TRUE, # est - sum estimation units to population
estvarn = "VOLCFNET", # est - number of trees per acre, numerator
estvarn.filter = deadtree.filter, # est - standing dead trees only, numerator
rowvar = "SPCD", # est - row domain
colvar = "AGENTCD", # est - column domain
returntitle = TRUE, # out - return title information
table_opts = table_options(row.FIAname = TRUE, # est - row domain names
col.FIAname = TRUE, # est - column domain names
allin1 = TRUE) # out - return output with est(pse)
)And we can see our output:
output
## [1] "est" "titlelst" "raw"output
## Species Insect Disease Fire Unidentified animal
## 1 19 4.5 (100.36) 42.8 ( 61.21) 3.9 ( 99.21) -- ( --)
## 2 66 -- ( --) -- ( --) -- ( --) -- ( --)
## 3 93 71.2 ( 97.20) 5.7 ( 73.96) 44.7 ( 99.21) -- ( --)
## 4 108 5.7 ( 62.75) 2.0 (100.36) -- ( --) 4.1 ( 82.09)
## 5 113 -- ( --) -- ( --) 3.5 (100.36) -- ( --)
## 6 202 -- ( --) -- ( --) -- ( --) -- ( --)
## Weather Vegetation (e.g., suppression) Unidentified Other
## 1 0.9 ( 99.21) 0.4 (100.36) 13.9 ( 64.63) -- ( --)
## 2 -- ( --) -- ( --) -- ( --) -- ( --)
## 3 1.4 (100.36) -- ( --) 10.5 ( 77.07) -- ( --)
## 4 1.4 ( 76.84) -- ( --) 18.6 ( 53.90) -- ( --)
## 5 -- ( --) -- ( --) 0.2 (100.36) -- ( --)
## 6 -- ( --) -- ( --) -- ( --) -- ( --)
## Total
## 1 3.8 ( 94.68)
## 2 -- ( --)
## 3 66.4 ( 47.93)
## 4 -- ( --)
## 5 133.6 ( 61.68)
## 6 -- ( --)POP3.1: 3.1 Number of live trees by species group and diameter class (DIACL2IN), Bighorn National Forest
View Example
ratio2.6 <-
modGBratio(GBpopdat = GBpopdat.bh, # pop - population calculations
landarea = "FOREST", # est - forest land filter
sumunits = TRUE, # est - sum estimation units to population
estvarn = "TPA_UNADJ", # est - number of trees per acre, numerator
estvarn.filter = "STATUSCD == 1", # est - live trees only, numerator
rowvar = "SPGRPCD", # est - row domain
colvar = "DIACL2IN", # est - column domain
returntitle = TRUE, # out - return title information
table_opts = list(row.FIAname = TRUE, # est - row domain names
allin1 = TRUE), # out - return output with est(pse)
title_opts = list(title.ref = "Bighorn National Forest")
)And examine our output:
output
## [1] "est" "titlelst" "raw"output
## Species group 1.0-2.9 11.0-12.9 13.0-14.9
## 1 Douglas-fir 22.3 (100.36) 0.2 (100.36) 0.5 ( 73.81)
## 2 True fir 53.7 ( 32.92) 2.0 ( 42.85) 0.2 (101.90)
## 3 Engelmann and other spruces 29.3 ( 50.99) 6.1 ( 27.02) 3.1 ( 37.39)
## 4 Lodgepole pine 64.7 ( 35.42) 10.8 ( 20.67) 4.8 ( 29.27)
## 5 Woodland softwoods -- ( --) -- ( --) -- ( --)
## 6 Other western softwoods 4.5 (100.36) -- ( --) -- ( --)
## 15.0-16.9 17.0-18.9 19.0-20.9 21.0-22.9 23.0-24.9 25.0-26.9
## 1 0.5 (100.36) -- ( --) 0.2 (100.36) 0.2 (100.36) 0.2 (100.36) -- ( --)
## 2 0.2 ( 99.21) 0.2 (100.36) -- ( --) -- ( --) -- ( --) -- ( --)
## 3 1.3 ( 64.24) 1.4 ( 54.08) 1.6 ( 41.09) 0.2 (100.36) 0.4 ( 99.21) -- ( --)
## 4 1.6 ( 40.50) 1.3 ( 73.49) 0.5 ( 74.51) -- ( --) 0.2 (100.36) -- ( --)
## 5 -- ( --) -- ( --) -- ( --) -- ( --) -- ( --) -- ( --)
## 6 -- ( --) -- ( --) -- ( --) -- ( --) -- ( --) -- ( --)
## 27.0-28.9 3.0-4.9 5.0-6.9 7.0-8.9 9.0-10.9
## 1 -- ( --) 8.9 ( 59.74) 3.2 ( 46.01) 2.3 ( 59.95) 1.1 ( 56.69)
## 2 -- ( --) 35.7 ( 40.47) 9.7 ( 31.02) 4.3 ( 35.49) 1.3 ( 33.91)
## 3 -- ( --) 11.2 ( 59.47) 12.4 ( 28.93) 9.7 ( 33.61) 5.2 ( 35.15)
## 4 -- ( --) 51.5 ( 32.89) 56.0 ( 22.45) 49.3 ( 19.64) 26.7 ( 18.62)
## 5 -- ( --) -- ( --) -- ( --) -- ( --) -- ( --)
## 6 -- ( --) -- ( --) 1.8 ( 82.12) 0.5 ( 73.81) 0.2 (100.36)
## Total
## 1 -- ( --)
## 2 39.7 ( 71.92)
## 3 81.8 ( 26.99)
## 4 267.3 ( 18.32)
## 5 15.1 ( 83.91)
## 6 107.1 ( 29.07)POP3: 3.2 Number of Live Trees per acre by Species Group and Diameter Class, Bighorn National Forest Districts
View Example
ratio3.2 <-
modGBratio(GBpopdat = GBpopdat.bhdist, # pop - population calculations
landarea = "FOREST", # est - forest land filter
sumunits = TRUE, # est - sum estimation units to population
estvarn = "TPA_UNADJ", # est - number of trees per acre, numerator
estvarn.filter = "STATUSCD == 1", # est - live trees only, numerator
rowvar = "SPGRPCD", # est - row domain
returntitle = TRUE, # out - return title information
table_opts = table_options(row.FIAname = TRUE, # est - row domain names
allin1 = TRUE), # out - return output with est(pse)
title_opts = title_options(title.ref="Bighorn National Forest Districts")
)And of course examine our output:
output
## [1] "est" "titlelst" "raw"output
## Species group Estimate (% Sampling Error)
## 1 Woodland softwoods -- ( --)
## 2 Douglas-fir 46.4 (73.91)
## 3 Engelmann and other spruces 79.6 (29.34)
## 4 Lodgepole pine 261.7 (18.16)
## 5 Cottonwood and aspen 13.6 (81.98)
## 6 True fir 110.3 (28.06)POP1: 1.4 Net cubic-foot volume of live trees (at least 5 inches diameter) divided by net cubic-foot volume of all trees by forest type, Wyoming, 2011-2013
View Example
ratio1.4 <-
modGBratio(GBpopdat = GBpopdat, # pop - population calculations for WY, post-stratification
landarea = "FOREST", # est - forest land filter
sumunits = TRUE, # est - sum estimation units to population
estvarn = "VOLCFNET", # est - net cubic-foot volume, numerator
estvarn.filter = "STATUSCD == 1", # est - live trees only
estvard = "VOLCFNET", # est - net cubic-foot volume, numerator
rowvar = "FORTYPCD", # est - row domain
returntitle = TRUE, # out - return title information
table_opts = table_options(row.FIAname = TRUE, # est - row domain names
allin1 = TRUE) # out - return output with est(pse)
)And examine the output:
output
## [1] "est" "titlelst" "raw"output
## Forest type Estimate (% Sampling Error)
## 1 Aspen 681.5 (22.93)
## 2 Blue spruce 2,861.1 ( --)
## 3 Bur oak 345.3 (44.36)
## 4 Cottonwood 1,926.8 (34.50)
## 5 Douglas-fir 1,451.9 (13.70)
## 6 Elm / ash / black locust 133.7 ( --)No strata
If you want to exclude post-stratification (i.e., simple random
sample, Horvitz-Thompson), you must generate a new population dataset
using the modGBpop function by setting
strata = FALSE.
View Code
## Get population data for Wyoming estimates, with post-stratification (for comparison)
GBpopdat.strat <-
modGBpop(popTabs = popTables(cond = WYcond, # FIA plot/condition data
tree = WYtree, # FIA tree data
seed = WYseed), # FIA seedling data
pltassgn = WYpltassgn, # plot assignments
pltassgnid = "CN", # uniqueid of plots
unitarea = WYunitarea, # area by estimation units
unitvar = "ESTN_UNIT", # name of estimation unit
strata = TRUE, # if using post-stratification
stratalut = WYstratalut, # strata classes and pixels counts
strata_opts = strata_options(
getwt=TRUE, # calculate strata weights
getwtvar="P1POINTCNT") # use P1POINTCNT in stratalut to calculate weights
)
## Get population data for Wyoming estimates, with no post-stratification
GBpopdat.nostrat <-
modGBpop(popTabs = popTables(cond = WYcond, # FIA plot/condition data
tree = WYtree, # FIA tree data
seed = WYseed), # FIA seedling data
pltassgn = WYpltassgn, # plot assignments
pltassgnid = "CN", # uniqueid of plots
unitarea = WYunitarea, # area by estimation units
unitvar = "ESTN_UNIT", # name of estimation unit
strata = FALSE) # if using post-stratification## Area of forest land by forest type and stand-size class, Wyoming, 2011-2013, with post-stratification
area.strat <- modGBarea(GBpopdat = GBpopdat.strat, # pop - population calculations for WY, post-stratification
landarea = "FOREST", # est - forest land filter
sumunits = TRUE, # est - sum estimation units to population
rowvar = "FORTYPCD", # est - row domain
table_opts = table_options(
row.FIAname = TRUE, # est - row domain names
allin1 = FALSE # out - return output with est(pse)
))
## Area of forest land by forest type and stand-size class, Wyoming, 2011-2013, no post-stratification
area.nostrat <- modGBarea(GBpopdat = GBpopdat.nostrat, # pop - population calculations for WY, no post-stratification
landarea = "FOREST", # est - forest land filter
sumunits = TRUE, # est - sum estimation units to population
rowvar = "FORTYPCD", # est - row domain
table_opts = table_options(
row.FIAname = TRUE, # est - row domain names
allin1 = FALSE # out - return output with est(pse)
)) # Compare estimates and percent standard errors with and without post-stratification
head(area.strat$est)output
## Forest type Estimate Percent Sampling Error
## 1 Rocky Mountain juniper 632481.7 17.28
## 2 Juniper woodland 339749.8 23.85
## 3 Pinyon / juniper woodland 14854.7 100
## 4 Douglas-fir 881189 14.21
## 5 Ponderosa pine 889542.8 12.82
## 6 Engelmann spruce 467196.7 19.99output
## Forest type Estimate Percent Sampling Error
## 1 Rocky Mountain juniper 637719.7 17.17
## 2 Juniper woodland 340093.9 23.8
## 3 Pinyon / juniper woodland 14854.7 100
## 4 Douglas-fir 863774.3 14.62
## 5 Ponderosa pine 944562.8 13.77
## 6 Engelmann spruce 473242.2 20.02## Number of live trees by species, Wyoming, 2011-2013, with post-stratification
tree.strat <- modGBtree(GBpopdat = GBpopdat.strat, # pop - population calculations for WY, post-stratification
landarea = "FOREST", # est - forest land filter
sumunits = TRUE, # est - sum estimation units to population
estvar = "TPA_UNADJ", # est - number of trees per acre, numerator
estvar.filter = "STATUSCD == 1", # est - live trees only, numerator
rowvar = "FORTYPCD", # est - row domain
table_opts = table_options(
row.FIAname = TRUE, # est - row domain names
allin1 = FALSE # out - return output with est(pse)
))
## Number of live trees by species, Wyoming, 2011-2013, no post-stratification
tree.nostrat <- modGBtree(GBpopdat = GBpopdat.nostrat, # pop - population calculations for WY, no post-stratification
landarea = "FOREST", # est - forest land filter
sumunits = TRUE, # est - sum estimation units to population
estvar = "TPA_UNADJ", # est - number of trees per acre, numerator
estvar.filter = "STATUSCD == 1", # est - live trees only, numerator
rowvar = "FORTYPCD", # est - row domain
table_opts = table_options(
row.FIAname = TRUE, # est - row domain names
allin1 = FALSE # out - return output with est(pse)
)) # Compare estimates and percent standard errors with and without post-stratification
head(tree.strat$est)output
## Forest type Estimate Percent Sampling Error
## 1 Rocky Mountain juniper 94791336.1 24.57
## 2 Juniper woodland 54049570 28.36
## 3 Pinyon / juniper woodland 1072754.3 100
## 4 Douglas-fir 240480740.8 21.25
## 5 Ponderosa pine 260800542.8 17.27
## 6 Engelmann spruce 201830027 25.03output
## Forest type Estimate Percent Sampling Error
## 1 Rocky Mountain juniper 95715598.7 24.12
## 2 Juniper woodland 54055007.6 28.29
## 3 Pinyon / juniper woodland 1072754.3 100
## 4 Douglas-fir 238146030.4 21.41
## 5 Ponderosa pine 271234746.9 17.55
## 6 Engelmann spruce 203591491.9 25.02## Number of live trees per acre by species, Wyoming, 2011-2013, with post-stratification
ratio.strat <- modGBratio(GBpopdat = GBpopdat.strat, # pop - population calculations for WY, post-stratification
landarea = "FOREST", # est - forest land filter
sumunits = TRUE, # est - sum estimation units to population
estvarn = "TPA_UNADJ", # est - number of trees per acre, numerator
estvarn.filter = "STATUSCD == 1", # est - live trees only, numerator
rowvar = "FORTYPCD", # est - row domain
table_opts = table_options(
row.FIAname = TRUE, # est - row domain names
allin1 = FALSE # out - return output with est(pse)
))
## Number of live trees per acre by species, Wyoming, 2011-2013, no post-stratification
ratio.nostrat <- modGBratio(GBpopdat = GBpopdat.nostrat, # pop - population calculations for WY, no post-stratification
landarea = "FOREST", # est - forest land filter
sumunits = TRUE, # est - sum estimation units to population
estvarn = "TPA_UNADJ", # est - number of trees per acre, numerator
estvarn.filter = "STATUSCD == 1", # est - live trees only, numerator
rowvar = "FORTYPCD", # est - row domain
table_opts = table_options(
row.FIAname = TRUE, # est - row domain names
allin1 = FALSE # out - return output with est(pse)
)) # Compare estimates and percent standard errors with and without post-stratification
head(ratio.strat$est)output
## Forest type Estimate Percent Sampling Error
## 1 Rocky Mountain juniper 149.9 17.49
## 2 Juniper woodland 159.1 14.1
## 3 Pinyon / juniper woodland 72.2 0
## 4 Douglas-fir 272.9 15.15
## 5 Ponderosa pine 293.2 11.01
## 6 Engelmann spruce 432 15.51output
## Forest type Estimate Percent Sampling Error
## 1 Rocky Mountain juniper 150.1 17.1
## 2 Juniper woodland 158.9 14.06
## 3 Pinyon / juniper woodland 72.2 0
## 4 Douglas-fir 275.7 15.09
## 5 Ponderosa pine 287.2 10.79
## 6 Engelmann spruce 430.2 15.34By estimation unit (sumunits = FALSE)
If you just wanted estimates by estimation unit and did not want to
sum them, set sumunits = FALSE. If
sumunits = FALSE, the estimates and percent standard errors
returned are by estimation unit, with an attribute, named ‘unit’
appended to data frame, with the unit value. The raw data returned will
look the same as if sumunits = TRUE.
View Code
area.unit <- modGBarea(GBpopdat = GBpopdat, # pop - population calculations for WY, post-stratification
landarea = "FOREST", # est - forest land filter
sumunits = FALSE, # est - sum estimation units to population
rowvar = "FORTYPCD", # est - row domain
colvar = "STDSZCD", # est - column domain
returntitle = TRUE, # out - return title information
table_opts = table_options(
allin1 = TRUE # out - return output with est(pse)
))
# Estimate and percent sampling error of estimate (first 6 rows)
head(area.unit$est)output
## unit Forest type 1 2 3 5
## 1 1 182 19,698.3 (102.67) -- ( --) 19,698.3 (102.67) -- ( --)
## 2 1 184 -- ( --) -- ( --) -- ( --) -- ( --)
## 3 1 185 -- ( --) -- ( --) -- ( --) -- ( --)
## 4 1 201 28,215.6 ( 87.92) -- ( --) -- ( --) -- ( --)
## 5 1 221 89,329.6 ( 45.13) -- ( --) -- ( --) -- ( --)
## 6 1 265 -- ( --) -- ( --) -- ( --) -- ( --)
## Total
## 1 39,396.6 ( 72.29)
## 2 28,215.6 ( 87.92)
## 3 89,329.6 ( 45.13)
## 4 112,862.2 ( 39.62)
## 5 28,215.6 ( 87.92)
## 6 106,303.3 ( 39.92)output
## [1] 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45
## Levels: 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45References
Bechtold, William A.; Patterson, Paul L., Editors. 2005. The enhanced Forest Inventory and Analysis program national sampling design and estimation procedures. Gen. Tech. Rep. SRS-80. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research Station. 85 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.
Westfall, James A.; Patterson, Paul L.; Coulston, John W. 2011. Post-stratified estimation: with-in strata and total sample size recommendations. Canadian Journal of Forest Research. 41: 1130-1139.