This dataset contains the National Demonstration products that were generated within the ESA SEN4LDN project: "High resolution Land Degradation Neutrality Monitoring" for the sub-indicator on Trends in Land Cover over Colombia, Portugal and Uganda. Trends in land cover between 2018 and 2023 are evaluated based on an automated algorithm to map land cover dynamics at 10 m resolution that combines deep learning and a pixel classifier on pre-processed Sentinel-2 imagery and ancillary input layers. Post-processing is performed to mitigate class fluctuations, resulting in consistent annual land cover maps. Land cover probabilities are used to generate land cover transition (probability) layers, that are further processed to discrete and continuous land degradation products. The dataset includes: Annual Land Cover Maps (LCM) for the years 2018 to 2023, with file naming LCM__.zip Land Cover Transition (LCT) for 2018-2023, with file naming LCT__2018-2023.zip Land Cover Degradation (LCD) classes for 2018-2023, with file naming LCD__2018-2023.zip Land Cover Degradation Probabilities (LCD-PROB) for 2018-2023, with file naming LCD-PROB__2018-2023.zip Products are distributed as 3x3° tiles with 1/12000° resolution (~10m) in Cloud Optimized Geotiff format. More information on product format and content can be found in the Product User Guide, available on the SEN4LDN Deliverables web page. The SEN4LDN project aimed to develop, demonstrate and validate a robust and scientifically-sound EO methodology that exploits the high frequency and spatial resolution of open and free-of-charge satellite imagery to increase the spatial details of national assessments of land degradation and restoration, and provide synoptic information for countries to plan LDN interventions at appropriate scales. More information on http://esa-sen4ldn.org/ . Click here to view the maps in an interactive Google Earth Engine application.