The development of new tools based on remote sensing data in agriculture contributes to cost reduction, increased production, and greater profitability. Airborne LiDAR (Light Detection and Ranging) data show a significant potential for geometrically characterizing tree plantations. This study aims to develop a methodology to extract walnut (Juglans regia L.) crowns under leafless conditions using airborne LiDAR data. An original approach based on the alpha-shape algorithm, identification of local maxima, and k-means algorithms is developed to extract the crowns of walnut trees in a plot located in Viver (Eastern Spain) with 192 trees. In addition, stem diameter and volume, crown diameter, total height, and crown height were estimated from cloud metrics and other 2D parameters such as crown area, and diameter derived from LiDAR data. A correct identification was made of 178 trees (92.7%). For structure parameters, the most accurate results were obtained for crown diameter, stem diameter, and stem volume with coefficient of determination values (R²) equal to 0.95, 0.87 and 0.83; and RMSE values of 0.43 m (5.70%), 0.02 m (9.35%) and 0.016 m³ (21.55%), respectively. The models that gave the lowest R² values were 0.69 for total height and 0.70 for crown height, with RMSE values of 0.84 m (12.4%) and 0.83 m (14.5%), respectively. A suitable definition of the central and lower parts of tree canopies was observed. Results of this study generate valuable information, which can be applied for improving the management of walnut plantations.

基于农业遥感数据的新工具的开发有助于降低成本，增加产量并提高利润。机载LiDAR（光检测和测距）数据显示了在几何上表征人工林的巨大潜力。这项研究旨在开发一种提取核桃（胡桃木）的方法。L.）使用机载LiDAR数据在无叶条件下冠冕。开发了一种基于alpha形状算法，局部最大值识别和k均值算法的原始方法，以提取位于Viver（西班牙东部）的一棵有192棵树的地块中胡桃树的树冠。此外，还可以根据云量度和其他2D参数（例如冠面积和从LiDAR数据得出的直径）估算出杆直径和体积，冠冠直径，总高度和冠冠高度。正确识别了178棵树（92.7％）。对于结构参数，冠冠直径，杆直径和杆体积获得了最准确的结果，测定系数（R ²）等于0.95、0.87和0.83；和RMSE值分别为0.43 m（5.70％），0.02 m（9.35％）和0.016 m ³（21.55％）。给出最低R ²值的模型的总高度为0.69，冠高为0.70，RMSE值分别为0.84 m（12.4％）和0.83 m（14.5％）。观察到了树冠中央和下部的合适定义。这项研究的结果产生了有价值的信息，可用于改善核桃种植园的管理。