Our proposed dataset comprises 199 cylindrical plots of 10 m radius corresponding to typical pasture land parcels in South-Eastern France. Each plot contains between 3000 and 17000 3D points, and each point is attributed with a total of 10 features: (i) absolute 3D coordinates, (ii) RGB and Near-InfraRed reflectance obtained with aerial cameras, (iii) uncalibrated laser intensity, return number and number of returns provided by the aerial LiDAR. This dataset can be used as training data for our model deep learning model "Vegetation Stratum Occupancy Prediction from Airborne LiDAR 3D Point Clouds" available on https://github.com/ekalinicheva/plot_vegetation_coverage