Fill not equally-spaced time series

Fill temporal gaps in a time series smoothed with function smooth_s2ts() to obtain homogeneous values (daily or with a regular time step).

fill_s2ts(
  ts,
  frequency = "daily",
  method = "fmm",
  max_na_days = Inf,
  max_extrapolation = 0.1
)

Arguments

ts

Time series in s2ts format (generated using smooth_s2ts()).

frequency

(optional) One of the followings:

• daily: daily frequency (default);

• dop (Days Of Passage): values are returned corresponding to the theoretic Sentinel-2 dates of passage.

method

(optional) Argument passed to spline().

max_na_days

(optional) maximum number of consecutive days with missing values which can be filled (in case of longer time windows with missing data, NA are returned). Default is to fit everything (unless this could lead to errors in case of long NT time windows, currently it is the only way to get subsequent functions working).

max_extrapolation

(optional) Numeric: maximum allowed extrapolation out of original range (relative value). Default is 0.1 (+10%). Set to Inf in order not to set any constraint.

Value

The output time series in tabular format (see extract_ts()).

Author

Luigi Ranghetti, PhD (2020) luigi@ranghetti.info

Examples

#' # Load input data
data("ts_smoothed")

# Gap filling using default parameters (daily)
ts_filled <- fill_s2ts(ts_smoothed)
ts_filled # standard print
#> An interpolated s2ts time series with 301 dates and 2 IDs.
#>            Date Orbit Sensor         1            2   
#>   1: 2020-01-04   022     2B 0.1160602 ○  0.1740709 ○ 
#>   2: 2020-01-05  <NA>   <NA> 0.1207222 ~  0.1749062 ~ 
#>   3: 2020-01-06  <NA>   <NA> 0.1247380 ~  0.1759228 ~ 
#>   4: 2020-01-07  <NA>   <NA> 0.1281397 ~  0.1771040 ~ 
#>   5: 2020-01-08  <NA>   <NA> 0.1309599 ~  0.1784328 ~ 
#>  ---                                                  
#> 297: 2020-10-26  <NA>   <NA>        NA ~         NA ~ 
#> 298: 2020-10-27  <NA>   <NA>        NA ~         NA ~ 
#> 299: 2020-10-28  <NA>   <NA>        NA ~         NA ~ 
#> 300: 2020-10-29  <NA>   <NA>        NA ~         NA ~ 
#> 301: 2020-10-30   022     2B        NA ~         NA ~ 
#> 
#> Quality flags:  ● [1]  ◕ [0.9,1)  ◑ [0.75,0.9)  ◔ [0.5,0.75)  ○ [0,0.5)
#> Interpolated values are marked with "~".
head(as.data.frame(ts_filled)) # see content
#>   id       date orbit sensor     value   qa     rawval interpolated
#> 1  1 2020-01-04   022     2B 0.1160602 0.33 0.11613333        FALSE
#> 2  1 2020-01-05  <NA>   <NA> 0.1207222   NA         NA         TRUE
#> 3  1 2020-01-06  <NA>   <NA> 0.1247380   NA         NA         TRUE
#> 4  1 2020-01-07  <NA>   <NA> 0.1281397   NA         NA         TRUE
#> 5  1 2020-01-08  <NA>   <NA> 0.1309599   NA         NA         TRUE
#> 6  1 2020-01-09   022     2A 0.1332310 0.00 0.02017083         TRUE
plot(ts_filled)


# Generate a regular time series using the minimum number of required records
ts_filled_2 <- fill_s2ts(ts_smoothed, frequency = "dop")
print(ts_filled_2, topn = 5) # standard print
#> An interpolated s2ts time series with 61 dates and 2 IDs.
#>           Date Orbit Sensor          1             2   
#>  1: 2020-01-04   022     2B 0.11606015 ○  0.17407087 ○ 
#>  2: 2020-01-09   022     2A 0.13323097 ~  0.17989257 ~ 
#>  3: 2020-01-14   022     2B 0.13748313 ~  0.18856602 ~ 
#>  4: 2020-01-19   022     2A 0.13286728 ~  0.19798907 ~ 
#>  5: 2020-01-24   022     2B 0.12343408 ○  0.20605959 ○ 
#> ---                                                    
#> 57: 2020-10-10   022     2B 0.05760022 ○  0.10211348 ○ 
#> 58: 2020-10-15   022     2A 0.04666769 ~  0.09472827 ~ 
#> 59: 2020-10-20   022     2B 0.05767390 ○  0.10161563 ○ 
#> 60: 2020-10-25   022     2A         NA ~          NA ~ 
#> 61: 2020-10-30   022     2B         NA ~          NA ~ 
#> 
#> Quality flags:  ● [1]  ◕ [0.9,1)  ◑ [0.75,0.9)  ◔ [0.5,0.75)  ○ [0,0.5)
#> Interpolated values are marked with "~".