pa_cardinal_dates: Predict cardinal dates from satellite image data

In pacu: Precision Agriculture Computational Utilities

Predict cardinal dates from satellite image data

Description

Predict cardinal dates from satellite image data

Usage

pa_cardinal_dates(x, ...)

## S3 method for class 'numeric'
pa_cardinal_dates(
  x,
  y,
  baseline.months = c(1:3, 12),
  model = c("none", "card3", "scard3", "agauss", "harmonic"),
  prior.means,
  prior.vars,
  bias.correction,
  ...
)

## S3 method for class 'Date'
pa_cardinal_dates(
  x,
  y,
  baseline.months = c(1:3, 12),
  model = c("none", "card3", "scard3", "agauss", "harmonic"),
  prior.means,
  prior.vars,
  bias.correction,
  ...
)

## S3 method for class 'veg.index'
pa_cardinal_dates(
  x,
  y = NULL,
  baseline.months = c(1:3, 12),
  model = c("none", "card3", "scard3", "agauss", "harmonic"),
  prior.means,
  prior.vars,
  bias.correction,
  ...
)

Arguments

x	vector containing the date or day of the year of that the satellite data was collected
...	ignored
y	vector containing the satellite data value
baseline.months	vector containing the months used as a baseline reference for when there are no crops in the field. For example, c(1:3, 12) represent Jan, Feb, Mar, and Dec.
model	a string naming the model to be used to estimate cardinal dates
prior.means	a vector of length three containing the prior means for cardinal dates
prior.vars	a vector of length three containing the prior variances for cardinal dates
bias.correction	a vector of length three containing the bias correction factor for cardinal dates

Value

when x is a vector, returns a vector of length 3 with the predicted cardinal dates. When x is a veg.index object, returns a stars object with spatially distributed cardinal dates

Examples

## Not run: 
x <- seq(1, 365, 6)
y <- nlraa::scard3(x, 120, 210, 300)
pa_cardinal_dates.vector(
  x = x,
  y = y,
  model = 'scard3',
  prior.means = c(130, 190, 297),
  prior.vars = c(11, 13, 18),
  bias.correction = c(10, 10, 10)
)

## End(Not run)

pacu documentation built on June 8, 2025, 10:44 a.m.