Using QA band information, filter the NDVI time series.
filter_qa(DT, ndvi = "NDVI", qa = "SummaryQA", good = c(0, 1))
filtered data.table with appended 'filtered' column of "quality" NDVI.
See the details for the example data in ?sampled-ndvi-Landsat-LC08-T1-L2.csv
and ?sampled-ndvi-MODIS-MOD13Q1.csv
For MODIS MOD13Q1, the SummaryQA band
For Landsat
Other filter:
filter_ndvi()
,
filter_roll()
,
filter_top()
,
filter_winter()
# 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))
#> id NDVI SummaryQA DayOfYear yr filtered
#> <int> <num> <num> <num> <num> <num>
#> 1: 0 0.1864 3 11 2015 NA
#> 2: 1 0.0541 2 3 2015 NA
#> 3: 2 0.1781 3 11 2015 NA
#> 4: 3 0.1024 2 5 2015 NA
#> 5: 4 0.0898 2 3 2015 NA
#> ---
#> 801: 2 0.1179 2 364 2019 NA
#> 802: 3 0.0789 2 364 2019 NA
#> 803: 4 0.1572 2 364 2019 NA
#> 804: 5 0.0763 2 364 2019 NA
#> 805: 6 0.1197 2 362 2019 NA