The paper describes production steps and accuracy assessment of an analysis-ready open
environmental data cube (2000--2021+) for continental Europe; at working resolutions
from 10~m to 30~m and with quarterly to annual estimates. The data cube is based on
processing and harmonizing earth observation (EO) images: Landsat GLAD ARD (2000-
-2020+), Sentinel-2 images (2017--2021+) and Digital Elevation data. These datasets were
created with accessibility, user-friendliness, interoperability and synthesis in mind. This
has required systematic spatiotemporal harmonization, efficient compression, and
imputation of missing values. To ensure a missing value percentage below 1%, the EO
data was first aggregated into 4 quarterly periods approximating the 4 seasons common in
Europe (winter, spring, summer and autumn), and then split into three percentiles (25th,
50th and 75th). Remaining missing data in the Landsat time-series was imputed with a
temporal moving window median (TMWM) approach. The accuracy assessment shows
TMWM gap-ûlling achieves higher performance in Southern Europe, and lower performance
in mountainous regions such as the Scandinavian Mountains, the Alps, and the Pyrenees.
The intended uses of the EcoDataCube platform include vegetation, soil, land cover and
land use mapping projects, environmental monitoring and automated generation of data
for statistical oûces including Eurostat. Combining all four datasets produced in this work
(DTM, Landsat 30m, Sentinel-2 30m and Sentinel-2 10m) yields the highest land cover
classification accuracy, with different datasets improving the results for different land
cover classes. The Environmental data cube for Europe is available under CC-BY license as
Cloud-Optimized GeoTIFFs (ca. 12TB in size) through STAC and the EcoDataCube data
portal.