Global overview of cloud-, snow-, and shade-free Landsat (1982-2025) and Sentinel-2 (2015-2025) data

Landsat and Sentinel-2 acquisitions are among the most frequently used
medium-resolution (i.e., 10-30 m) optical data. The data are extensively
used in terrestrial vegetation applications, including but not limited to,
land cover and land use mapping, vegetation condition and phenology
monitoring, and disturbance and change mapping. While the Landsat archives
alone provide over 40 years, and counting, of continuous and consistent
observations, since mid-2015 Sentinel-2 has enabled a revisit frequency of
up to 2-days. Although the spatio-temporal availability of both data
archives is well-known at the scene level, information on the actual
availability of usable (i.e., cloud-, snow-, and shade-free) observations
at the pixel level needs to be explored for each study to ensure correct
parametrization of used algorithms, thus robustness of subsequent
analyses. However, a priori data exploration is time and
resource‑consuming, thus is rarely performed. As a result, the
spatio-temporal heterogeneity of usable data is often inadequately
accounted for in the analysis design, risking ill-advised selection of
algorithms and hypotheses, and thus inferior quality of final results.
Here we present a global dataset comprising precomputed daily availability
of usable Landsat and Sentinel-2 data sampled at a pixel-level in a
regular 0.18°-point grid. We based the dataset on the complete 1982-2025
Landsat surface reflectance data (Collection 2) and 2015-2025 Sentinel-2
top-of-the-atmosphere reflectance scenes (pre‑Collection-1 and
Collection-1). Derivation of cloud-, snow-, and shade-free observations
followed the methodology developed in our recent study on data
availability over Europe (Lewińska et al., 2023;
https://doi.org/10.20944/preprints202308.2174.v2). Furthermore, we
expanded the dataset with growing season information derived based on the
2001‑2019 time series of the yearly 500 m MODIS land cover dynamics
product (MCD12Q2; Collection 6). As such, our dataset presents a unique
overview of the spatio-temporal availability of usable daily Landsat and
Sentinel-2 data at the global scale, hence offering much-needed a priori
information aiding the identification of appropriate methods and
challenges for terrestrial vegetation analyses at the local to global
scales. The dataset can be viewed using the dedicated GEE App (link in
Related Works). As of February 2025 the dataset has been extended with the
2024 data. As of May 2026 the dataset has been extended with the
2025 data.