PhenoExtractMeth: Phenology Extraction methods

In phenofit: Extract Remote Sensing Vegetation Phenology

Description

• PhenoTrs Threshold method

• PhenoDeriv Derivative method

• PhenoGu Gu method

• PhenoKl Inflection method

Usage

PhenoTrs(
  fFIT,
  approach = c("White", "Trs"),
  trs = 0.5,
  asymmetric = TRUE,
  IsPlot = TRUE,
  ...
)

PhenoDeriv(
  fFIT,
  analytical = TRUE,
  smoothed.spline = FALSE,
  IsPlot = TRUE,
  show.lgd = TRUE,
  ...
)

PhenoGu(fFIT, analytical = TRUE, smoothed.spline = FALSE, IsPlot = TRUE, ...)

PhenoKl(
  fFIT,
  analytical = TRUE,
  smoothed.spline = FALSE,
  IsPlot = TRUE,
  show.lgd = TRUE,
  ...
)

Arguments

fFIT	fFIT object returned by optim_pheno().
approach	to be used to calculate phenology metrics. 'White' (White et al. 1997) or 'Trs' for simple threshold.
trs	threshold to be used for approach "Trs", in (0, 1).
asymmetric	If true, background value in spring season and autumn season is regarded as different.
IsPlot	whether to plot?
...	other parameters to PhenoPlot
analytical	If true, numDeriv package grad and hess will be used; if false, D1 and D2 will be used.
smoothed.spline	Whether apply smooth.spline first?
show.lgd	whether show figure lelend?

Examples

library(phenofit)
# simulate vegetation time-series
fFUN = doubleLog.Beck
par  = c( mn  = 0.1 , mx  = 0.7 , sos = 50 , rsp = 0.1 , eos = 250, rau = 0.1)

t    <- seq(1, 365, 8)
tout <- seq(1, 365, 1)
y <- fFUN(par, t)

methods <- c("AG", "Beck", "Elmore", "Gu", "Zhang") # "Klos" too slow
fFITs <- curvefit(y, t, tout, methods)
fFIT  <- fFITs$fFIT$AG

par(mfrow = c(2, 2))
PhenoTrs(fFIT)
PhenoDeriv(fFIT)
PhenoGu(fFIT)
PhenoKl(fFIT)

Example output

sos eos 
 50 250 
sos pop eos 
 47 150 253 
 UD  SD  DD  RD 
 26  73 227 275 
   Greenup   Maturity Senescence   Dormancy 
        16         82        218        284 

phenofit documentation built on April 2, 2020, 5:07 p.m.