UAV-LiDAR Dataset for High-Throughput Phenotyping of Triticale and Durum Wheat Genotypes in Athalassa, Cyprus (2024-2025)

This dataset provides multi-temporal UAV LiDAR and multispectral data for high-throughput phenotyping of forage wheat and triticale under Mediterranean conditions. Data were collected during the 2024–2025 growing season at Athalassa, Nicosia, Cyprus (35°08′14″ N, 33°24′14″ E), from 80 experimental plots comprising 20 genotypes with four replications each. The dataset includes LiDAR point clouds from six dates, four-band multispectral imagery from three dates, orthomosaics, plot masks, ground-truth measurements of fresh biomass, dry biomass, and plant height, flight metadata, and derived Digital Terrain Models (DTMs) and Digital Surface Models (DSMs). LiDAR data were acquired using a DJI Zenmuse L2 mounted on a Matrice 350 RTK, while multispectral data were collected using a DJI Mavic 3 platform. These data support crop growth monitoring, canopy structure analysis, vegetation index calculation, LiDAR–multispectral data fusion, and machine-learning applications in agricultural remote sensing and precision agriculture. The dataset accompanies the research paper “AI-Driven Multi-Temporal UAV LiDAR–Multispectral Data Fusion for High-Throughput Phenotyping of Forage Wheat Genotypes under Mediterranean Conditions.” This dataset was generated as part of the PHENOWEX project (Grant Agreement No. 101160158), funded by the European Union under the Horizon Europe programme, and the PHENOTYPOS project, implemented under the THALIA 2021–2027 Programme and co-funded by the Research and Innovation Foundation (RIF) of Cyprus.