Martijn Witjes is a PhD candidate at OpenGeoHub foundation. In this talk, he expounded the first results of his research on land cover time-series data stack for Europe between 2000 and 2019. The classification sees 33 different land use / land cover (LULC) classes between 2000 and 2019 using a single spatiotemporal ensemble machine learning model in a fully automated, free and open source workflow. This workflow includes harmonization and preprocessing of several high-resolution publically available covariate datasets and over five million training samples, spatial K-fold cross-validation, hyperparameter optimization, and multiple methods for LULC change analysis. Martijn also showed how the per-class probability predictions facilitated useful prediction uncertainty metrics, informed use case-tailored post-processing strategies, and enabled a novel way to quantify LULC change dynamics without relying on hard-class predictions. The results of his study suggest that the method developed by his team, enables land cover classification for subsequent years without waiting for new training data, while facilitating improved training data collection through analysing variable importance, per-class performance, and uncertainty metrics.