This function queries the given database to retrieve data on vegetation (ready for use in calculate_vegetation function).

load_data_vegetation(
  database,
  plottype = NA,
  forest_reserve = NA,
  processed = TRUE
)

Arguments

database

name of Fieldmap/Access database (with specific Fieldmap structure) including path

plottype

possibility to select only data for a certain plot type, e.g. 'CP' for Circular plot or 'CA' for Core area (the default NA means that data from all plots are retrieved)

forest_reserve

possibility to select only data for 1 forest reserve by giving the name of the forest reserve (the default NA means that data from all plots are retrieved)

processed

Should only processed and surveyed data be added? Defaults to TRUE (yes).

Value

Dataframe with vegetation data, containing columns as total_herb_cover, total_shrub_cover, total_tree_cover, total_soildisturbance_game, date_vegetation (= date of vegetation survey), year_main_survey (= year of vegetation survey), ....

Examples

library(forrescalc)
# (add path to your own fieldmap database here)
path_to_fieldmapdb <-
  system.file("example/database/mdb_bosres.sqlite", package = "forrescalc")
load_data_vegetation(path_to_fieldmapdb)
#> # A tibble: 43 × 42
#>    forest_reserve   plot_id plottype subplot_id period year_main_survey
#>    <chr>              <int> <chr>         <int>  <int>            <int>
#>  1 Everzwijnbad         101 CP                1      1             2002
#>  2 Withoefse heide      204 CP                1      1             2003
#>  3 Liedekerke          1005 CP                1      1             2006
#>  4 Kersselaerspleyn    2006 CP                1      1             2001
#>  5 Kersselaerspleyn   11000 CA           155511      1             2000
#>  6 Kersselaerspleyn   11000 CA           155512      1             2000
#>  7 Kersselaerspleyn   11000 CA           155513      1             2000
#>  8 Harras             21000 CA               17      1             2009
#>  9 Harras             21000 CA               18      1             2009
#> 10 Harras             21000 CA               19      1             2009
#> # ℹ 33 more rows
#> # ℹ 36 more variables: date_vegetation <dttm>, totalplotarea_ha <dbl>,
#> #   plotarea_ha <dbl>, total_moss_cover_id <int>, total_herb_cover_id <int>,
#> #   total_shrub_cover_id <int>, total_tree_cover_id <int>,
#> #   total_waterlayer_cover_id <int>, total_soildisturbance_game_id <int>,
#> #   moss_cover_interval <chr>, moss_cover_min <dbl>, moss_cover_max <dbl>,
#> #   herb_cover_interval <chr>, herb_cover_min <dbl>, herb_cover_max <dbl>, …