occTest (version 0.1.1)

geoEnvAccuracy: Coordinate accuracy

Description

Detect records with low accuracy in space and time

Usage

geoEnvAccuracy(
  df,
  xf,
  yf,
  af,
  dsf,
  ef,
  tf,
  method = "all",
  r.env,
  accept.threshold.cell = 0.5,
  accept.threshold.env = 0.5,
  bearing.classes = 10,
  distance.classes = 5,
  env.quantiles = c(0.3, 0.7),
  elev.threshold = 100,
  raster.elevation = NULL,
  verbose = FALSE,
  do = TRUE,
  doParallel = FALSE,
  mc.cores = 2
)

Value

data.frame

Arguments

df

data.frame of species occurrences

xf

character. column name in df containing the x coordinates

yf

character. column name in df containing the y coordinates

af

character. column name in df containing the coordinate uncertainty value (in the same)

dsf

character. column name in df containing the dataset to which the record belongs to (e.g. Forest Inventory of Spain)

ef

character. column name in df containing the registered elevation for the record.

tf

character. column name in df containing the dataset with the date/time where the species is recorded

method

character. Vector of methods to be used. See details. Default 'all'

r.env

raster. Raster with environmental data

accept.threshold.cell

numeric. Acceptance threshold for how much percentage of the Area of uncertainty in the cell we want to accept. Default to 0.5

accept.threshold.env

numeric. Default 0.5

bearing.classes

numeric. Default to 10.

distance.classes

integer. Default to 5.

env.quantiles

numeric. Default to c(0.3,0.7)

elev.threshold

numeric. Default to 100

raster.elevation

numeric. Default to 100

verbose

logical. Print messages? Default FALSE

do

logical. Should tests be performed? Default TRUE

doParallel

logical. Should computation use parallel functions? Default FALSE

mc.cores

numeric. How many cores to use? (used when doParallel = TRUE). Default 2

Author

Josep M Serra-Diaz ([e-mail]), A Zizka (CoordinateCleaner package)

Details

Geoenvironmental accuracy function will implement differnt methods to assess occurrence accuracy in environmnental and geographic space.
Current implmented methods are: 'lattice' : tests for lattice arrangement in occurrence datasets. Borrowed from cd_round .
'elevDiff' : assess the elevation difference between a given raster (or automatically downloaded fro SRTM), and the elevation recorded. If differences >elev.threshold then the record is considered as a low accuracy threshold
'noDate' : assess whether there is a date or timestamp information in the record.
'noDateFormatKnown' : assess whether the information in the timestamp agrees with different formatting of Dates.
'outDateRange' : (not implemented) assess whether the record is within a user specified time frame.
'percDiffCell' : assess whether the record may be falling in a different raster cell given an information of coordinate accuracy.
'envDeviation' : assess whether the climate in a given record may be outside of the interval 30th-70th (default values) for a given variable due to coordinate uncertainty.

See Also

cd_round

Other analysis: .nearestcell3(), centroidDetection(), countryStatusRangeAnalysis(), duplicatesexcludeAnalysis(), humanDetection()

Examples

#see examples in vignetteXtra-occTest