Help for package ForIT

Title:

Functions to Estimate Tree Volume and Phytomass in the Italian Forest Inventory 2005

Version:

2.5.0

Description:

Tabacchi et al. (2011) published a very detailed study producing a uniform system of functions to estimate tree volume and phytomass components (stem, branches, stool). The estimates of the 2005 Italian forest inventory (https://www.inventarioforestale.org/it/) are based on these functions. The study documents the domain of applicability of each function and the equations to quantify estimates accuracies for individual estimates as well as for aggregated estimates. This package makes the functions available in the R environment. Version 2 exposes two distinct functions for individual and summary estimates. To facilitate access to the functions, tree species identification is now based on EPPO species codes (https://data.eppo.int/).

License:

GPL (≥ 3)

Encoding:

UTF-8

LazyData:

true

RoxygenNote:

7.3.2

Imports:

magrittr, dplyr (≥ 1.1.0), purrr, tibble, tidyr, RColorBrewer, metR, rlang, ggplot2

Suggests:

Matrix, testthat

URL:

https://gitlab.com/NuoroForestrySchool/ForIT.git, https://zenodo.org/records/5790157

Depends:

R (≥ 2.10)

NeedsCompilation:

Packaged:

2025-04-25 06:47:43 UTC; nicolapuletti

Author:

Nicola Puletti

[aut, cre], Mirko Grotti [aut], Roberto Scotti

[aut]

Maintainer:

Nicola Puletti <nicola.puletti@gmail.com>

Repository:

CRAN

Date/Publication:

2025-04-25 07:30:02 UTC

ForIT: A package that implements as R functions the INFC-2005 equations estimating single tree volume and phytomass .

Description

The ForIT package provides two main functions, estimating respectively individual and summary values, and some accessory functions, facilitating package use and documenting its content

Author(s)

Maintainer: Nicola Puletti nicola.puletti@gmail.com (ORCID)

Authors:

Mirko Grotti mirko.grotti@gmail.com
Roberto Scotti scotti@uniss.it (ORCID)

References

Tabacchi G., Di Cosmo L., Gasparini P., Morelli S., 2011a. Stima del volume e della fitomassa delle principali specie forestali italiane. Equazioni di previsione, tavole del volume e tavole della fitomassa arborea epigea. Stima del volume e della fitomassa delle principali specie forestali italiane. Equazioni di previsione, tavole del volume e tavole della fitomassa arborea epigea. 412 pp.

Tabacchi G., Di Cosmo L., Gasparini P., 2011b. Aboveground tree volume and phytomass prediction equations for forest species in Italy. European Journal of Forest Research 130: 6 911-934

Pipe operator

Description

See magrittr::%>% for details.

Usage

lhs %>% rhs

'ForIT'-package Database - Ver.2

Description

The package exposes 5 tightly interconnected tibbles:

INFCspecies, INFCcatalog, Quantities, INFCparam, INFCf_domains

Usage

INFCspecies

INFCcatalog

Quantities

INFCparam

INFCf_domains

Format

An object of class tbl_df (inherits from tbl, data.frame) with 44 rows and 3 columns.

An object of class tbl_df (inherits from tbl, data.frame) with 26 rows and 4 columns.

An object of class tbl_df (inherits from tbl, data.frame) with 5 rows and 2 columns.

An object of class tbl_df (inherits from tbl, data.frame) with 130 rows and 5 columns.

An object of class tbl_df (inherits from tbl, data.frame) with 617 rows and 4 columns.

Details

Figure: ForIT-DBschema

Tables columns

INFCspecies

EPPOcode [PK]: species code, adopting EPPO database
pag: section page number in the original reference (Tabacchi et al., 2011a)
PrefName: EPPO preferred name for the species

INFCcatalog

pag [PK]: section page number in the original reference (Tabacchi et al., 2011a)
n_oss: number of sample trees for the section
n_par: number of parameters in the equations for the section
section: section name (species or species group)

Quantities

quantity [PK]: code of the estimated quantity
quantity_definition: estimated quantity definition and measurement units

INFCparam

pag [PK]: section page number in the original reference (Tabacchi et al., 2011a)
quantity [PK]: code of the estimated quantity (see Quantities)
wrv: weighted residual variance
bm: functions coefficients (a list of arrays)
vcm: variance-covariance matrices (a list of 'dspMatrix')

INFCf_domains

pag [PK]: section page number in the original reference (Tabacchi et al., 2011a)
htot.m [PK]: tree height class [m] (class width 1 m)
dbh.min: minimum tree diameter class [cm] (class width 1 cm)
dbh.max: maximum tree diameter class [cm] (class width 1 cm)

Columns bm and vcm are lists, the dimensions of the arrays and matrices they store vary depending on n_par.
Matrices in vcm are symmetric, stored as "dspMatrix" class objects.
Database schema is defined, verified and illustrated using package dm

library(dm)
ForIT_DB <- dm(INFCcatalog,
               INFCspecies,
               Quantities,
               INFCparam,
               INFCf_domains) %>%
  dm_add_pk(INFCcatalog, pag, check = TRUE) %>%

  dm_add_pk(INFCspecies, EPPOcode, check = TRUE) %>%
  dm_add_fk(INFCspecies, pag, INFCcatalog, check = TRUE) %>%

  dm_add_pk(Quantities, quantity, check = TRUE) %>%

  dm_add_pk(INFCparam, c(pag, quantity), check = TRUE) %>%
  dm_add_fk(INFCparam, pag, INFCcatalog, check = TRUE) %>%
  dm_add_fk(INFCparam, quantity, Quantities, check = TRUE) %>%

  dm_add_pk(INFCf_domains, c(pag, htot.m), check = TRUE) %>%
  dm_add_fk(INFCf_domains, pag, INFCcatalog, check = TRUE)

dm_examine_constraints(ForIT_DB)

dm_draw(ForIT_DB, rankdir = "BT", view_type = "all", column_types = T)

'ForIT'-package TEST-data - Ver.2

Description

A tiny test dataset including example data displayed in Tabacchi et al. (2011), the basic reference for ForIT package.

Usage

ForIT_test_data

Format

A data frame with 16 rows and 5 variables:

Details

The dataset is produced by the following code.

ForIT_test_data <- dplyr::tribble(
  ~UC, ~IdF, ~specie, ~d130, ~h_dendro,
  # UC: Plot Id (Unità Campionaria)
  # IdF: Stem ID (Identificativo Fusto)
  # specie: EPPO species code (see https://gd.eppo.int/)
  #  - ACRCA: Acer campestre
  #  - ABIAL: Abies alba
  #  - FAUSY: Fagus sylvatica
  # d130: trunk diameter at breast height [cm]
  # h_dendro: tree height [m]
 # Example data in Tabacchi et al. (2011) pag. 25
  "U1","01","ACRCA",10,7,
  "U1","02","ACRCA",15,9,
  "U1","03","ACRCA",20,12,
  "U1","04","ACRCA",30,20,
  "U1","05","ACRCA",32,21,
  "U1","06","ACRCA",24,18,
  "U1","07","ACRCA",36,21,
  "U1","08","ACRCA",40,22,
  "U1","09","ACRCA",8,8,
  "U1","10","ACRCA",18,12,

 # Example continuation, pag. 27
  "U2","01","ABIAL",38,21,
  "U2","02","ABIAL",52,28,
  "U2","03","FAUSY",25,16,
  "U2","04","FAUSY",30,18,
  "U2","05","FAUSY",12,10,

 # Extra lines, to test for 'out of domain'
  "U0","01","ACRCA",22,14,   # pag. 24
  "U0","02","ACRCA",30,10
 )

'ForIT'-package Auxiliary pre-computed data - Ver.2

Description

A large dataset used by 'INFCaccuracyPlot0()' to speed the production of a fine resolution CV surface for the plots.

Usage

INFC_CVgrid

Format

A data frame with 167560 rows and 7 variables:

pag: see 'INFCcatalog' primary key
quantity: see 'Quantities'
dbh: trunk diameter at breast height (dbh), in cm
h_tot: tree height, in m
cv_ie: coefficient of variation for an individual estimate
cv_ea: coefficient of variation for the estimate of an average
est: estimated value for the selected 'quantity'. See 'INFCvpe()' for more details
n_par: number of parameters that the function requires
inD: is the (dbh, htot) point within the function domain?

Details

The dataset is produced by the following code.

 Populate_INFC_CVgrid <- function() {
 INFCcatalog %>%
   select(pag) %>%
   inner_join(INFCspecies %>%
                select(pag, EPPOcode),
              by = "pag") %>%
   group_by(pag) %>%
   summarise(EPPOcode = first(EPPOcode),
             .groups = "drop") %>%
   inner_join(Quantities %>% select(quantity), by = character()) %>%
   mutate(grid.k = pmap(list(pag, EPPOcode, quantity), compute_grid0)) %>%
   select(-EPPOcode) %>%
   unnest(cols = c(grid.k)) %>%
   return()
 }

The range of applicability of `INFCvpe()` function

Description

A data.frame containing the "range of applicability" (or "domain") of INFCvpe() function

Format

A data frame with 18563 observations on the following 2 variables.

key: a character vector
in.range: a factor with levels y

References

Reproduce the tables that Tabacchi et al. published in 2011

Description

The tables published in the work on which this package is based, convey a very relevant part of the information produced: printed numbers serve as reference to verify that coded functions return expected results and, more specifically, empty spaces in the printed tables signal function applicability domain. In other words, measurement data used to estimate function coefficients values, cover only the portion of the (dbh, htot) plane where numbers are printed.

Usage

INFCtabulate(
  EPPOcode,
  quantity = "vol",
  dbh.by = 5,
  htot.by = 3,
  digits = 1,
  print_tab = T
)

Arguments

EPPOcode

tree species code defined by the EPPO database https://gd.eppo.int/search. Lookup 'INFCspecies' dataframe to retrieve recognized codes.

quantity

for each species (or species group) different quantities can be estimated. Quantity's definitions and Ids are exposed by the 'Quantities' dataframe. Default value is "vol", estimation of timber volume.

dbh.by

...

htot.by

increment value between rows (respectively columns) expressed in 'cm' (respectively 'm') for dbh (respectively total height, htot). Default 5 cm (respectively 1 m).

digits

number of decimal digits to expose in the table. Default one decimal digit.

print_tab

defaults to TRUE in order to produce a text output. If set to FALSE no printing will occur (see 'return')

Value

Function principal output is the printout of the volume or phytomass tables. If print_tab = FALSE, the function will only return a tibble with a list column containing the tabulation of the required estimation equation/s. Using default values, tables will be identical (or anyway similar) to the corresponding published tables, with white (NA) cells delimiting the domain of applicability of the equation.

Examples

## Not run: 
  INFCtabulate(c("ABIAL", "ACRCA"),
                quantity = "vol",
                dbh.by = 5,
                htot.by = 3,
                digits = 1)
  # EPPO code:  ABIAL  - pag =  33  - quantity =  vol
  #     htot.m
  # dbh.cm    7    10    13    16     19     22     25     28     31
  # 9  23.2  32.4    NA    NA     NA     NA     NA     NA     NA
  # 14   NA  77.9 100.2    NA     NA     NA     NA     NA     NA
  # 19   NA 142.3 183.3 224.3     NA     NA     NA     NA     NA
  # 24   NA    NA 291.1 356.4  421.8  487.2     NA     NA     NA
  # 29   NA    NA    NA 518.9  614.3  709.8  805.2     NA     NA
  # 34   NA    NA    NA 711.6  842.8  974.0 1105.2 1236.4     NA
  # 39   NA    NA    NA    NA 1107.2 1279.8 1452.5 1625.1 1797.7
  # 44   NA    NA    NA    NA     NA 1627.2 1847.0 2066.7 2286.5
  # 49   NA    NA    NA    NA     NA 2016.3 2288.8 2561.4 2833.9
  # 54   NA    NA    NA    NA     NA     NA 2778.0 3109.0 3439.9
  # 59   NA    NA    NA    NA     NA     NA 3314.4 3709.5 4104.6
  # 64   NA    NA    NA    NA     NA     NA     NA 4363.1 4828.0
  
  
  # ---
  #   EPPO code:  ACRCA  - pag =  231  - quantity =  vol
  # htot.m
  # dbh.cm  7.5  10.5  13.5  16.5   19.5   22.5
  # 9.5  26.8  36.8    NA    NA     NA     NA
  # 14.5   NA  83.6 106.9    NA     NA     NA
  # 19.5   NA 149.7 192.0 234.3  276.6     NA
  # 24.5   NA    NA 302.2 369.0  435.7     NA
  # 29.5   NA    NA    NA 534.2  631.0  727.8
  # 34.5   NA    NA    NA 729.9  862.4  994.8
  # 39.5   NA    NA    NA    NA 1129.9 1303.5
  # ---
  
## End(Not run)

Estimate bole volume or tree phytomass for individual stems, with associated accuracy info

Description

Using the functions developed for INFC 2005 (the 2005 Italian national forest inventory), stem volume or tree compartment phytomass are estimated for each (EPPOcode, dbh.cm, htot.m) input tuple. Accompaining the main value, accuracy estimates are returned, as attributes. The functions are documented in Tabacchi et al. (2011a)

Usage

INFCvpe(EPPOcode, dbh.cm, htot.m, quantity = "vol")

Arguments

EPPOcode

Character vector of tree species code, as defined in EPPO database, (See INFCspecies() and https://gd.eppo.int )

dbh.cm

Numeric vector of stem/s breast height diameter (in cm)

htot.m

Numeric vector of tree total height/s (in m). Length equal to dbh.cm vector or one. In this case same value will be replicated for all dbh.cm entries

quantity

(default = vol) Character vector specifying required quantity, one of c("vol", "dw1" : "dw4"). Use qantities() to retrieve codes definitions. Length equal to dbh.cm vector or one. In this case same value will be replicated for all dbh.cm entries

Details

Output value will have following added attributes with estimates accuracy evaluations for each stem:

pag - page number, referred to original source
wrv - weighted residual variance
Var_ea - variance for an estimated average
or variance for 'confidence interval' estimation, see prediction.lm(.., interval = "confidence")
Var_ie - variance for an individual estimate
or 'prediction variance', (see prediction.lm(.., interval = "prediction") and Freese, 1964 - in:Tabacchi, 2011
InDomain - logical indicating whether the (dbh, htot) point lies out of the domain explored by the experimental data (see 'INFCtabulate()')

Value

The functions returns a Numeric vector of the same length of the dbh.cm argument, with accuracy info as attributes

Examples

# COMPARE WITH Tabacchi (2011a) page 25 ----
(v <- INFCvpe("ACRCA", dbh.cm = 22, htot.m = 14))
# [1] 252.9581
# attr(,"pag")
# [1] 231
# attr(,"wrv")
# [1] 2.271e-05
# attr(,"Var_ea")
# [1] 33.17182
# attr(,"Var_ie")
# [1] 1075.883
# attr(,"InDomain")
# [1] TRUE

# Standard Error of the Estimate
see <- sqrt(attr(v, "Var_ie"))
# Degrees of freedom
df <- INFCcatalog$n_oss[INFCcatalog$pag == attr(v, "pag")] -
      INFCcatalog$n_par[INFCcatalog$pag == attr(v, "pag")]
# confidence level
p <- 95/100
# Confidence Interval Half Width
cihw <- qt(1-(1-p)/2, df) * see
cat(" *** Volume confidence interval (p = ", p*100, "%) is [", round(v, 1),
    " +/- ", round(cihw, 1), "] dm^3\n", sep = "")

# ESTIMATION OF PHYTOMASS ----
Quantities[5,] %>% as.data.frame()
#   quantity         quantity_definition
# 1      dw4 phytomass of the whole tree [kg]
tree_phy <- INFCvpe(c("ACRCA", "ALUCO"),
                    dbh.cm = c(22, 15),
                    htot.m = c(14, 16),
                    quantity = "dw4")
tree_phy
# [1] 185.1291  87.7970
# attr(,"pag")
# [1] 231 245
# attr(,"wrv")
# [1] 3.142e-05 2.104e-05
# attr(,"Var_ea")
# [1] 45.89002  9.12407
# attr(,"Var_ie")
# [1] 1488.5135  281.8072
# attr(,"InDomain")
# [1] TRUE TRUE

# PROCESSING A TALLY DATA-FRAME ----
tst_vol <- ForIT_test_data %>%
  dplyr::mutate(vol = INFCvpe(specie, d130, h_dendro),
                OutOfDomain = !attr(vol, "InDomain"))
tst_vol %>%
  dplyr::filter(OutOfDomain)
tst_vol %>%
  dplyr::filter(UC == "U1")

# SUMS AND direct ACCUARACY AGGREGATION (instead of via ?INFCvpeSUM) ----
df <- function(pag) return(
  INFCcatalog %>%
    dplyr::right_join(tibble::tibble(pag = !!pag), by = "pag") %>%
    dplyr::transmute(df = n_oss - n_par) %>%
    purrr::pluck(1)
)
p <- 95/100
tst_vol %>%
  dplyr::mutate(cihw = qt(1-(1-p)/2,
                          df(attr(vol, "pag"))) *
                  sqrt(attr(vol, "Var_ie"))
  ) %>%
  dplyr::filter(!OutOfDomain) %>%
  dplyr::group_by(specie) %>%
  dplyr::summarise(.groups = "drop",
                   est = sum(vol),
                   cihw = sqrt(sum(cihw^2)),
  ) %>%
  dplyr::left_join(INFCspecies %>% dplyr::select(EPPOcode, pag),
                   by = c("specie" = "EPPOcode")) %>%
  dplyr::left_join(INFCcatalog %>% dplyr::select(pag, section),
                   by = "pag") %>% 
  dplyr::select(-c(specie, pag)) %>% 
  dplyr::rename(specie = section) %>% 
  dplyr::mutate(dplyr::across(c("est", "cihw"), ~round(.x, 1))) %>% 
  dplyr::arrange(specie) %>%
  dplyr::select(specie, est, cihw) -> tab
tab[c(2,1,3),] %>% 
  t()
rm(tst_vol, tab, df)

Estimate tree bole volume or phytomass for stems groups, with associated accuracy info

Description

Cumulative estimation of the volume or phytomass of groups of trees is just the summation of the values computed with INFCvpe(), but the computation of accuracy estimates is improved using these summation functions.
Two approaches are available.

Via INFCvpe_summarise() that processes and returns a data frame
or by following aggregation functions within a standard summarise():
- INFCvpe_sum()
- INFCvpe_ConfInt()
- INFCvpe_OutOfDomain()

Usage

INFCvpe_summarise(
  in.data,
  EPPOcode_C,
  dbh_C,
  h_tot_C,
  quantity = "vol",
  p = 0.95
)

INFCvpe_sum(EPPOcode, dbh, h_tot, quantity = "vol")

INFCvpe_ConfInt(EPPOcode, dbh, h_tot, quantity = "vol", p = 0.95)

INFCvpe_OutOfDomain(EPPOcode, dbh, h_tot)

Arguments

in.data

A dataframe (or tibble) containing tally data to be matched with "EPPOcode_C", "dbh_C" and "htot_C" arguments

EPPOcode_C

A string, the name of the column in in.data with the species EPPO codes

dbh_C

A string, the name of the column in in.data with the breast height diameter values

h_tot_C

A string, the name of the column in in.data with the tree total height values

quantity

(default = "vol") A character vector specifying required quantity/ies: c("vol", "dw1" : "dw4"). Use qantities() to decode definitions.

for INFCvpe_summarise(), if length(unique(quantity)) > 1, rows in in.data will be replicated for each value.
for INFCvpe_SUM functions, length(quantity) must be 1

p

(default p = 95%) probability used to compute cihw (with length = 1 or length = length(dbh))

OPZIONE 2 INFCvpe_SUM functions:

EPPOcode

A character vector with the species EPPO codes (with length = 1 or length = length(dbh))

dbh

A numeric vector with the brest height diameter values

h_tot

A numeric vector with the tree total height values (with length = 1 or length = length(dbh))

Details

Functions developed following Tabacchi et al. (2011), pages 23-26.

Value

INFCvpe_summarise() returns a dataframe (tibble) with the grouping columns defined with group_by(), and the following columns:
- quantity: as additional grouping column,
- n : number of trees in the group,
- n_out : the number of (dbh, htot) pairs that are 'out of the domain',
- est : the estimated value,
- cihw : confidence interval half width
- p: probability used computing cihw
INFCvpe_SUM - the functions of this family return a numeric vector, aggregating rows within the same group,
- INFCvpe_sum() returns the sum of the estimated quantities,
- INFCvpe_ConfInt() returns 'confidence interval half width',
- INFCvpe_OutOfDomain() returns the number of 'out of domain' (dhb, h_tot) pairs included in the summation

Examples

## Not run: 
Sezione <- function(EPPOcodes){
  # retrive 'Sezione' name, decoding EPPO codes
  INFCspecies %>% 
    dplyr::filter(EPPOcode %in% EPPOcodes) %>%
    dplyr::left_join(INFCcatalog,by = "pag")%>% 
    dplyr::select(section) %>% 
    purrr::pluck(1)
}

tst <- ForIT_test_data %>%
  dplyr::filter(UC != "U0") 
# select Tabachi et al. example data

tst %>%
  dplyr::group_by(specie) %>%
  INFCvpe_summarise("specie", "d130", "h_dendro") %>%
  dplyr::ungroup() %>%
  dplyr::mutate(specie = Sezione(specie),
                dplyr::across(c("est", "cihw"), ~round(.x, 1))
  ) %>%
  dplyr::select(specie, est, cihw) %>%
  dplyr::arrange(specie) %>%
  dplyr::slice(2, 1, 3) %>% 
  t() %>% 
  provideDimnames(base = list(dimnames(.)[[1]], ""), unique=FALSE)
# Compare ForIT (ver 2) output
## specie "Aceri"  "Abete bianco" "Faggio"
## est    "4623.0" "4044.2"       "1079.4"
## cihw   "567.5"  "661.2"        "275.4" 
# with 'Tabella 2' in Tabacchi et al. (2011, pag. 27)
## specie "aceri"  "abete bianco" "faggio"
## est    "4623.0" "4044.2"       "1079.4"
## cihw   "567.4"  "662.4"        "279.2"

# Using 'INFCvpe_summarise()'

## Overall totals
tst %>%
  INFCvpe_summarise("specie", "d130", "h_dendro", quantity = c("vol", "dw4"))

## Group by dbh class ('cld')
tst %>%
  dplyr::mutate(cld = ceiling(d130/5)*5) %>%
  dplyr::group_by(UC, specie, cld) %>%
  INFCvpe_summarise("specie", "d130", "h_dendro")

## Group by sampling unit ('UC')
tst %>%
  dplyr::group_by(UC) %>%
  INFCvpe_summarise("specie", "d130", "h_dendro", quantity = "dw4")

# Using 'INFCvpeSUM' aggregation functions

## Esitmate 'dw4' phytomass, by sampling unit ('UC')
tst %>%
  dplyr::group_by(UC) %>%
  dplyr::summarise(
    n_stems = dplyr::n(),
    OoD = INFCvpe_OutOfDomain(specie, d130, h_dendro),
    dw4 = INFCvpe_sum(specie, d130, h_dendro, quantity = "dw4"),
    dw4_ConfInt = INFCvpe_ConfInt(specie, d130, h_dendro, quantity = "dw4")
  )

## Esitmate volume, by sampling unit ('UC')
tst %>%
  dplyr::group_by(UC) %>%
  dplyr::summarise(
    n_stems = dplyr::n(),
    OoD = INFCvpe_OutOfDomain(specie, d130, h_dendro),
    vol = INFCvpe_sum(specie, d130, h_dendro),
    vol_ConfInt = INFCvpe_ConfInt(specie, d130, h_dendro)
  )

rm(tst, Sezione)

## End(Not run)

Plotting the accuracy and reliability region (or 'domain') of the volume and phytomass estimation functions

Description

Volume and phytomass functions are tabulated in Tabacchi et al. (2011a). The tabulation covers a limited region of the dbh by h_tot rectangle. This region is the "domain" of the reliable estimates, based on the distribution of the sample trees used to calibrate the functions. The coefficient of variation (CV = standard_deviation / estimate) is computed and plotted (as 'filled contours') for the whole rectangular area, the limits of the region of reliable estimates (the "domain"), is superimposed as a light colored line. Function output is a ggplot object that can be used by its self or as a background on top of which the user can plot his/her data to verify eventual accuracy or reliability problems.
Two functions are available.

INFCaccuracyPlot() - allows the plots to be fully customized but, beware, all values required for the 'fill' will be computed and, at finer resolution, the process can be slow.
INFCaccuracyPlot0() - produces, much faster, the plots at the finest resolution, using pre-calculated values stored in a specific auxiliary data.frame (see INFC_CVgrid), necessarily leaving less customization freedom.

(** compute_grid0() - is an internal function exported for the sake of the Populate_INFC_CVgrid() function **)

Usage

INFCaccuracyPlot(
  EPPOcod,
  quantity = "vol",
  ie.Var = FALSE,
  cv.ul = 0.1,
  fixed = TRUE,
  plot.est = FALSE,
  dbh.step = 5,
  htot.step = dbh.step,
  dbh.buf = 1,
  htot.buf = dbh.buf
)

INFCaccuracyPlot0(
  EPPOcod,
  quantity = "vol",
  ie.Var = FALSE,
  cv.ul = 0.1,
  fixed = TRUE,
  plot.est = FALSE
)

compute_grid0(pag, EPPOcod, quantity)

Arguments

EPPOcod

A string, one of the EPPO tree species codes listed in INFCspecies table (Reference: https://gd.eppo.int )

quantity

(optional) A string specifying the quantity to be estimated, one of c("vol", "dw1" : "dw4"). Lookup Quantities table to retrieve codes definitions. Defaults to "vol".

ie.Var

(optional) Logical. Choose variance estimator:

TRUE = variance for an 'individual estimate'
FALSE = variance for the 'estimate of an average' value Default ie.Va = FALSE

cv.ul

(optional) Numeric. Cutoff CV level for the plot. Defaults to 0.1

fixed

(optional) Logical. Contour plot breaks:

TRUE = break levels are fixed
FALSE = breaks are tailored to the specific case (in order to split the values within the range of interest [0, cv.ul], into equally numerous bins) Default fixed = TRUE

plot.est

(optional) Logical. Add the 'estimated quantity' layer as contour lines. Default plot.est = FALSE

dbh.step

(optional) Numeric. Computation with smaller step produces a plot with better resolution but increases consistently computation time (see INFCaccuracyPlot0()). To reduce computation time, the step defaults to 5.

htot.step

(optional) Numeric. As for dbh.

dbh.buf

(optional) Numeric. Extra space in the plot beyond the 'domain'. Default: 1

htot.buf

(optional) Numeric. As for dbh.

pag

for the internal function compute_grid0()

Value

INFCaccuracyPlot The function returns a ggplot object.

Examples

## Not run: 
INFCaccuracyPlot("FRXAN") # 'INFCaccuracyPlot()' can be slow because
#       it computes all the CV values needed to fill backgroud plot,
#              hence default values are set to a coarser resolution.
\donttest{
  INFCaccuracyPlot("FRXAN",
                   dbh.step = 1,
                   htot.step = 1) 
  # computing with high resolution is slow
}

INFCaccuracyPlot0("FRXAN") 
# 'INFCaccuracyPlot0()' is quick, it uses stored values
INFCaccuracyPlot0("FRXAN", "dw4")
INFCaccuracyPlot0("FRXAN", "dw4", ie.Var = TRUE) 
# deafult fixed break values are not alwais optimal
INFCaccuracyPlot0("FRXAN", "dw4", ie.Var = TRUE, fixed = FALSE, cv.ul=.9) 
# tailoring can improve
INFCaccuracyPlot0("FRXAN", plot.est = TRUE) 
# 'quantity' estimation iso-lines can be superimposed


background <- INFCaccuracyPlot0("ACROP", plot.est = TRUE)
foreground <-  ForIT_test_data %>%
  dplyr::filter(specie == "ACROP") %>%
  dplyr::mutate(vol = INFCvpe(specie, d130, h_dendro)) %>%
  ggplot2::geom_point(map = ggplot2::aes(h_dendro, d130, size = vol))
background + foreground  # Adding a custom foreground
rm(background, foreground)

INFCaccuracyPlot0("ABIAL") 
# high resolution and quick, using pre-calculated backgroung values
INFCaccuracyPlot("ABIAL") 
# default values produce a coarser resolution

## End(Not run)

ForIT: A package that implements as R functions the INFC-2005 equations estimating single tree volume and phytomass .

Description

Author(s)

References

See Also

Pipe operator

Description

Usage

'ForIT'-package Database - Ver.2

Description

Usage

Format

Details

'ForIT'-package TEST-data - Ver.2

Description

Usage

Format

Details

'ForIT'-package Auxiliary pre-computed data - Ver.2

Description

Usage

Format

Details

The range of applicability of INFCvpe() function

Description

Format

References

Reproduce the tables that Tabacchi et al. published in 2011

Description

Usage

Arguments

Value

Examples

Estimate bole volume or tree phytomass for individual stems, with associated accuracy info

Description

Usage

Arguments

Details

Value

See Also

Examples

Estimate tree bole volume or phytomass for stems groups, with associated accuracy info

Description

Usage

Arguments

Details

Value

See Also

Examples

Plotting the accuracy and reliability region (or 'domain') of the volume and phytomass estimation functions

Description

Usage

Arguments

Value

Examples

The range of applicability of `INFCvpe()` function