filter_winter: Filter winter NDVI
In irg: Instantaneous Rate of Green Up

Description Usage Arguments Details Value See Also Examples

Using lower quantile (default = 0.025) of multi-year MODIS data, determine the "winterNDVI" for each id.

filter_winter(
  DT,
  probs = 0.025,
  limits = c(60L, 300L),
  doy = "DayOfYear",
  id = "id"
)

`DT`	data.table of NDVI time series
`probs`	quantile probability to determine "winterNDVI". default is 0.025.
`limits`	integer vector indicating limit days of absolute winter (snow cover, etc.). default is c(60, 300): 60 days after Jan 1 and 65 days before Jan 1.
`doy`	julian day column. default is 'DayOfYear'.
`id`	id column. default is 'id'. See details.

The id argument is used to split between sampling units. This may be a point id, polygon id, pixel id, etc. depending on your analysis.

filtered data.table with appended 'winter' column of each id's "winterNDVI" baseline value.

Other filter: filter_ndvi(), filter_qa(), filter_roll(), filter_top()

# Load data.table
library(data.table)

# Read example data
ndvi <- fread(system.file("extdata", "sampled-ndvi-MODIS-MOD13Q1.csv", package = "irg"))
filter_qa(ndvi, ndvi = 'NDVI', qa = 'SummaryQA', good = c(0, 1))
filter_winter(ndvi, probs = 0.025, limits = c(60L, 300L), doy = 'DayOfYear', id = 'id')