View source: R/smooth_wHANTS.R
smooth_wHANTS | R Documentation |
Weighted HANTS smoother
smooth_wHANTS(
y,
t,
w,
nf = 3,
ylu,
periodlen = 365,
nptperyear,
wFUN = wTSM,
iters = 2,
wmin = 0.1,
...
)
y |
Numeric vector, vegetation index time-series |
t |
Numeric vector, |
w |
(optional) Numeric vector, weights of |
nf |
number of frequencies to be considered above the zero frequency |
ylu |
|
periodlen |
length of the base period, measured in virtual samples (days, dekads, months, etc.). nptperyear in timesat. |
nptperyear |
Integer, number of images per year. |
wFUN |
weights updating function, can be one of 'wTSM', 'wChen' and 'wBisquare'. |
iters |
How many times curve fitting is implemented. |
wmin |
Double, minimum weigth (i.e. weight of snow, ice and cloud). |
... |
Additional parameters are passed to |
ws
: weights of every iteration
zs
: curve fittings of every iteration
Wout Verhoef, NLR, Remote Sensing Dept. June 1998 Mohammad Abouali (2011), Converted to MATLAB Dongdong Kong (2018), introduced to R and modified into weighted model.
library(phenofit)
data("MOD13A1")
dt <- tidy_MOD13(MOD13A1$dt)
d <- dt[site == "AT-Neu", ]
l <- check_input(d$t, d$y, d$w, nptperyear=23)
r_wHANTS <- smooth_wHANTS(l$y, l$t, l$w, ylu = l$ylu, nptperyear = 23, iters = 2)
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