This map presents the spatial distribution of the main vegetation and land cover classes within the Danube Delta, Romania, based on Sentinel-2 satellite imagery acquired in July 2025. The classification was performed using the Random Forest machine learning algorithm, which assigns each pixel to the most probable land cover class based on its spectral characteristics.

The resulting classified raster distinguishes the dominant vegetation and land cover types of the study area, including open water, reed beds, aquatic vegetation, forests, grasslands, agricultural land, and sandy areas. Each class is represented by a distinct color, allowing for clear visualization of the heterogeneous landscape and ecological patterns of the Danube Delta.

This vegetation map serves as a fundamental dataset for environmental monitoring and spatial analysis. It supports the assessment of vegetation distribution, land cover composition, and habitat patterns, while providing a reliable basis for further analyses such as overlay with protected areas, area statistics, habitat evaluation, and change detection.

By combining Sentinel-2 multispectral imagery with the Random Forest classification approach, the map provides an accurate and up-to-date representation of vegetation conditions in the Danube Delta during July 2025, supporting biodiversity conservation, ecosystem management, and GIS-based environmental research.