The estimation of stand- and individual tree information is one of the major goals of forest inventory. Conventionally, field data in forest inventory are collected at tree level on sample plots by means of manual measurements (e.g., caliper, tape). In recent years, modern laser-supported sensors and automatic routines for feature extraction were increasingly used instead of the traditional forest inventory methods. In 2020, Apple (Apple Inc. Cupertino, California, USA) implemented a LiDAR (Light Detection and Ranging) sensor into the new 4th Generation of Apple iPad Pro. Consequently, LiDAR-generated 3D point clouds can nowadays be recorded with consumer-level devices for the first time. Novel methodology is able to provide estimates of the terrain height, tree positions, stem diameters, and tree heights from these 3D point clouds. This dataset was made publicly accessible to show recent iPad 3D point clouds of forest inventory sample plots and to test new software routines for the automatic measurement of trees. Benchmark studies with performance tests of different algorithms are welcome. The dataset contains co-registered raw 3D point-cloud data collected on 21 forest inventory sample plots in Austria. The data was collected by two different laser scanning systems: (i) the iPad pro (Apple Inc. Cupertino, California, USA), and (ii) a mobile personal laser scanner (PLS) (ZEB Horizon, GeoSLAM Ltd., Nottingham, UK). The data also contains application videos of the iPad, digital terrain models (DTM), field measurements as reference data (“ground-truth”), and the output of recent software routines for the automatic tree detection and the automatic stem diameter measurement.