phenofit (version 0.2.5-2)

season: Growing season dividing

Description

Divide growing seasons according to rough fitting (rFUN) result .

For season, rough fitting is applied for whole. For season_mov rough fitting is applied in every year, during which maxExtendMonth is extended.

Usage

season(INPUT, rFUN = wWHIT, wFUN = wTSM, iters = 2, wmin = 0.1,
  lambda, nf = 3, frame = floor(INPUT$nptperyear/5) * 2 + 1,
  minpeakdistance, r_max = 0.2, r_min = 0.05, ypeak_min = 0.1,
  rtrough_max = 0.6, MaxPeaksPerYear = 2, MaxTroughsPerYear = 3,
  calendarYear = FALSE, IsPlot = FALSE, plotdat = INPUT,
  print = FALSE, adj.param = TRUE, ...)
season_mov(INPUT, rFUN = wWHIT, wFUN = wTSM, iters = 2, wmin = 0.1,
  IsOptim_lambda = FALSE, lambda = NULL, nf = 3,
  frame = floor(INPUT$nptperyear/5) * 2 + 1, maxExtendMonth = 12,
  calendarYear = FALSE, ..., IsPlot = TRUE, IsPlot.vc = FALSE,
  IsPlot.OnlyBad = FALSE, plotdat = INPUT, print = TRUE,
  titlestr = "")
stat_season(INPUT, brks)

Arguments

INPUT

A list object with the elements of t, y, w, Tn (optional) and ylu, returned by check_input().

rFUN

Rough curve fitting function, can be one of wSG(), wWHIT() and wHANTS().

wFUN

weights updating function, can be one of wTSM(), wChen(), wBisquare() and wSELF().

iters

How many times curve fitting is implemented.

wmin

Double, minimum weigth (i.e. weight of snow, ice and cloud).

lambda

The smoothing parameter of wWHIT(). For season_mov(), if lambda is NULL, init_lambda() will be used. Generally, it was set as 10000, 15, and 5 for daily, 8-day and 16-day inputs respectively.

nf

The parameter of wHANTS(), number of frequencies to be considered above the zero frequency.

frame

The parameter of wSG(), moving window size. Suggested by TIMESAT, default frame = floor(nptperyear/7)*2 + 1.

minpeakdistance

Numberic, in the unit of points (default as nptperyear/6). The minimum distance of two peaks. If the distance of two maximum extreme value less than minpeakdistance, only the real maximum value will be left.

r_max

Similar as r_min, The maximum threshold should be greater than r_max.

r_min

Threshold is defined as the difference of peak value with trough value. There are two threshold (left and right). The minimum threshold should be greater than r_min.

ypeak_min

ypeak >= ypeak_min

rtrough_max

ytrough <= rtrough_max*A, A is the amplitude of y.

MaxPeaksPerYear

This parameter is used to adjust lambda in iterations. If PeaksPerYear > MaxPeaksPerYear, then lambda = lambda*2.

MaxTroughsPerYear

This parameter is used to adjust lambda in iterations. If TroughsPerYear > MaxTroughsPerYear, then lambda = lambda*2.

calendarYear

If true, only one static calendar growing season will be returned.

IsPlot

Boolean

plotdat

(optional) A list or data.table, with t, y and w. Only if IsPlot=TRUE, plot_input() will be used to plot. Known that y and w in INPUT have been changed, we suggest using the original data.table.

print

Whether to print progress information

adj.param

Adjust rough curve fitting function parameters automatically, if too many or to less peak and trough values.

...

For season_mov(), Other parameters passed to season(); For season(), other parameters passed to findpeaks().

IsOptim_lambda

Whether to optimize Whittaker's parameter lambda by V-curve theory?

maxExtendMonth

Previous and subsequent maxExtendMonth data were added for every year curve fitting.

IsPlot.vc

Whether to plot V-curve optimized time-series.

IsPlot.OnlyBad

If true, only plot partial figures whose NSE < 0.3.

titlestr

string for title

brks

A list object returned by season or season_mov.

Value

• whit: Rough fitting result.

• dt: Growing season dividing information.

List object, list(whit, dt)

Details

Before dividing growing season, INPUT should be added a year in head and tail first by add_HeadTail.

Finally, use findpeaks() to get local maximum and local minimum values. Two local minimum define a growing season. If two local minimum(maximum) are too closed, then only the smaller(biger) is left.

See Also

findpeaks().

Examples

# NOT RUN {
library(phenofit)
data("MOD13A1")

df <- tidy_MOD13.gee(MOD13A1$dt)
st <- MOD13A1$st

date_start <- as.Date('2013-01-01')
date_end   <- as.Date('2016-12-31')

sitename <- 'CA-NS6' # df$site[1]
d     <- df[site == sitename & (date >= date_start & date <= date_end), ]
sp    <- st[site == sitename, ]
south <- sp$lat < 0
nptperyear <- 23

# global parameter
IsPlot = TRUE
print  = FALSE
ypeak_min  = 0.05
wFUN = wTSM

# add one year in head and tail
dnew     <- add_HeadTail(d, south = south, nptperyear = nptperyear) 
INPUT    <- check_input(dnew$t, dnew$y, dnew$w, QC_flag = dnew$QC_flag,
     nptperyear = nptperyear, south = south, 
     maxgap = nptperyear/4, alpha = 0.02, wmin = 0.2)
# all year as a whole
brks  <- season(INPUT,
    rFUN = wWHIT, wFUN = wFUN,
    lambda = 10,
    plotdat = d, IsPlot = IsPlot, print = FALSE, IsPlot.OnlyBad = FALSE)
# curve fitting by year
brks2 <- season_mov(INPUT,
    rFUN = wWHIT, wFUN = wFUN,
    lambda = 10,
    plotdat = d, IsPlot = IsPlot, print = FALSE, IsPlot.OnlyBad = FALSE)
# }