TSGenerator 2.0 is an R package for acquiring, extracting, quality-assessing, and analysing Copernicus HR-VPP Seasonal Trajectories (ST) and Vegetation Phenology and Productivity (VPP) products.
The 2.0 architecture is built around three explicit components:
hdar.terra-based
extraction and product-aware quality handling.Python/reticulate, raster, the discontinued
VI workflow, and the old QFLAG2 preprocessing chain are not part of the
2.0 core.
TSGenerator 2.0 includes a single integrated graphical workflow for users who prefer not to program directly:
library(TSGenerator)
runTSapp()The application follows Acquire → Prepare/Extract → Quality → Analyze → Export and calls the same public R API used in scripts. Results & Export records available session outputs, acquisition provenance, reproducible R code, and session information. Selected historical mini-apps remain temporarily callable for compatibility, while discontinued VI/QFLAG2 interfaces are blocked.
Install the stable release from CRAN:
install.packages("TSGenerator")For development versions, install from the GitHub development branch:
install.packages("remotes")
remotes::install_github("avalero92/TSGenerator", ref = "cran-preparation")A WEkEO account is required only for online ST/VPP searches and
downloads. These operations also require an active Internet connection
and depend on the availability of the external WEkEO service, which is
outside the control of TSGenerator. Credentials can be supplied to
hda_client() or managed by hdar through
~/.hdarc. Offline processing, local diagnostics, and
package checks do not require WEkEO access.
library(TSGenerator)
check_wekeo()
# For a live authenticated diagnostic:
# check_wekeo(online = TRUE)st_search <- download_st(
start = "2020-04-01",
end = "2020-04-30",
tile_id = "30TXM",
product = c("PPI", "QFLAG"),
download = FALSE
)
# Set download = TRUE and output_dir = "HRVPP_ST" to download.download_st() uses the current HR-VPP ST dataset and
supports PPI and ST-QFLAG. Long requests are divided into
service-compatible temporal windows.
vpp_search <- download_vpp(
start = "2020-01-01",
end = "2020-12-31",
tile_id = "30TXM",
product = c("SOSD", "MAXD", "EOSD", "LENGTH"),
season = "s1",
download = FALSE
)VPP metadata and scaling are handled by product. Date parameters such as SOSD/MAXD/EOSD are not treated like spectral or productivity values.
st_ts <- extract_ts(
x = "HRVPP_ST/PPI",
polygons = parcels,
id_col = "Parcel_ID",
fun = "median"
)The result is a tidy tsg_time_series with
ID, Date, Layer, and
Value. extract_ts() validates polygon IDs and
CRS and preserves the source raster grid.
vpp <- extract_vpp(
x = "HRVPP_VPP",
polygons = parcels,
id_col = "Parcel_ID",
fun = "median"
)The result identifies Year, Season,
Product, Unit, and source Layer.
Date products populate Date; numeric products populate
Value.
Copernicus product quality is deliberately separate from temporal completeness.
quality_info("ST")
quality_info("VPP")
q_summary <- summarize_quality(qflag, type = "ST")
st_masked <- mask_quality(
x = st_raster,
quality = qflag_raster,
type = "ST",
min_quality = 4
)Quality flags are categorical. TSGenerator does not bilinearly resample QFLAG rasters.
plan <- temporal_plan(
st_ts,
expected_step = 10
)
missing <- summarize_missingness(plan)
quality <- assess_ts_quality(plan)summarize_missingness() distinguishes absent
expected dates from explicit NA
values. assess_ts_quality() classifies
completeness; its classes are TSGenerator diagnostics and must not be
confused with Copernicus QFLAG classes.
completed <- impute_ts(
user_series,
method = "linear",
series_type = "user",
complete_grid = TRUE,
expected_step = 10,
max_gap = 2
)ST is already temporally processed, so additional ST imputation is
blocked by default. It requires the explicit
allow_processed = TRUE override when scientifically
justified.
fit <- model_missingness(
missingness_data,
year_col = "Year",
doy_col = "DOY",
value_col = "Value"
)
plot_missingness(fit)The 2.0 API separates the GAM model from plotting. Year is categorical by default and DOY can use a cyclic smooth.
| Module | Functions |
|---|---|
| WEkEO | hda_client(), check_wekeo(),
check_wekeo_integration() |
| Acquisition | download_st(), download_vpp() |
| Geospatial | geospatial_plan(), extract_ts(),
extract_vpp() |
| Product quality | quality_info(), classify_quality(),
summarize_quality(), mask_quality() |
| Temporal quality | temporal_plan(), summarize_missingness(),
assess_ts_quality() |
| Imputation | impute_ts() |
| Diagnostics | model_missingness(),
plot_missingness() |
| Apps | runTSapp() |
The principal replacements are:
| TSGenerator 1.x | TSGenerator 2.0 |
|---|---|
Download.STPPI() |
download_st() |
Download.HRVPP() |
download_vpp() |
get.Series.mean() |
extract_ts(..., fun = "mean") |
get.Series.median() |
extract_ts(..., fun = "median") |
get.Series.VPP() |
extract_vpp() |
QFLAG2.Mask() |
mask_quality() for current ST/VPP QFLAG |
quality.Series() |
assess_ts_quality() |
general.Quality() |
assess_ts_quality() |
count_missing() |
summarize_missingness() |
TsImpute() |
impute_ts() |
GAM.missing() / GAM.plot() |
model_missingness() /
plot_missingness() |
The old VI/QFLAG2 workflow (Download.VI(),
get.Stack(), get.Clean.IV(),
renames.image.IV()) is legacy-only because it targets
discontinued products/workflows. Historical source is retained under
legacy/ for traceability, not as the recommended 2.0
workflow.
See
vignette("migration-1x-to-2x", package = "TSGenerator")
after installation for the detailed migration guide.
The development branch includes offline tests and an opt-in live WEkEO integration harness. Maintainers should run:
devtools::document()
testthat::test_local()
devtools::check(document = FALSE, manual = FALSE)
check_wekeo(online = TRUE)
z <- check_wekeo_integration(download = FALSE)
stopifnot(z$ok)A controlled real-download smoke test should also be completed before a release candidate.
vignette("getting-started", package = "TSGenerator") —
architecture and core workflow.vignette("st-vpp-workflows", package = "TSGenerator") —
acquisition-to-analysis examples.vignette("migration-1x-to-2x", package = "TSGenerator")
— detailed 1.x → 2.0 migration.Alexey Valero-Jorge — creator and maintainer.
ORCID: 0000-0002-5993-7346.
Departamento de Sistemas Agrícolas, Forestales y Medio Ambiente (Unidad
asociada a EEAD-CSIC Suelos y Riegos), Centro de Investigación y
Tecnología Agroalimentaria de Aragón (CITA), Avda. Montañana 930, 50059
Zaragoza, Spain.
Mª Auxiliadora Casterad Seral — researcher.
ORCID: 0000-0003-4458-6966.
Departamento de Sistemas Agrícolas, Forestales y Medio Ambiente (Unidad
asociada a EEAD-CSIC Suelos y Riegos), Centro de Investigación y
Tecnología Agroalimentaria de Aragón (CITA), Avda. Montañana 930, 50059
Zaragoza, Spain.
José-Tomás Alcalá Nalvaiz — researcher. ORCID:
0000-0001-7549-8825.
Departamento de Métodos Estadísticos, Instituto Universitario de
Investigación en Matemáticas y Aplicaciones (IUMA), Universidad de
Zaragoza, Zaragoza, Spain.
Alexey Valero-Jorge —
avalero@cita-aragon.es
Current maintenance version: 2.0.1. Cite the archived software release using its version-specific Zenodo DOI:
Valero-Jorge, A., Casterad Seral, M. A., & Alcalá Nalvaiz, J.-T. (2026). TSGenerator 2.0.1: Tools for Copernicus HR-VPP Vegetation Time-Series Processing (Version 2.0.1) [Computer software]. Zenodo. https://doi.org/10.5281/zenodo.23620160
GitHub release: https://github.com/avalero92/TSGenerator/releases/tag/v2.0.1
Historical citation — TSGenerator 2.0.0:
Valero-Jorge, A., Casterad Seral, M. A., & Alcalá Nalvaiz, J.-T. (2026). TSGenerator 2.0.0: Tools for Copernicus HR-VPP Vegetation Time-Series Processing (Version 2.0.0) [Computer software]. Zenodo. https://doi.org/10.5281/zenodo.23265767
The historical DOI above identifies the archived 2.0.0 release. The scientific publications below are separate research outputs and should be cited additionally when relevant.
TSGenerator has been presented and applied in scientific research involving Copernicus HR-VPP products and vegetation time-series processing.
Valero-Jorge, A., Casterad, M. A., & Alcalá, J.-T. (2026). TSGenerator: librería R de código abierto para el procesado integrado de productos fenológicos HR-VPP de Copernicus. Congresos UEx, Actas de Congresos, 2. https://doi.org/10.17398/3101-7177.2.123
Valero-Jorge, A., Casterad, M. A., & Alcalá, J.-T. (2025). Evaluating the Influence of Missing Data from the Crop Vegetation Index Time Series on Copernicus HR-VPP Phenological Products. Engineering Proceedings, 94(1), 4. https://doi.org/10.3390/engproc2025094004
TSGenerator supports processing of Copernicus HR-VPP products and uses WEkEO for online data access. References to Copernicus and WEkEO identify data sources and services; they do not imply institutional endorsement of TSGenerator.
TSGenerator was created within the LAIKcA I+D+i project PID2021-124029OR-I00, funded by MICIU/AEI/10.13039/501100011033 and FEDER/EU. Alexey Valero Jorge acknowledges grant PRE2022-102328 funded by MICIU/AEI/10.13039/501100011033 and FSE+.
MIT. See LICENSE.