Airborne lidar scanner (ALS) technology is used in a variety of applications, including forestry. ALS has enormous potential for the estimation of relevant biometric parameters in forest plantations. This study investigates the use of an object-oriented semi-automated segmentation algorithm for stands delineation, based on modeling ALS data, in plantations of Eucalyptus grandis and E. dunnii in Uruguay. The results show that non-parametric methods delivered more accurate and less biased results for total volume (TV) with R² 0.93, RMSE 20.04 m³ h⁻¹ for E. grandis and R² 0.93, RMSE 18.43 m³ h⁻¹ for E.dunnii; and above ground biomass (AGB) with R² 0.95, RMSE 70.2 kg h⁻¹ for E. grandis and R² 0.96, RMSE: 71.2 Kg h⁻¹ for E. dunnii. Parametric methods performed better for dominant height (Ho) with R² 0.98, RMSE 0.67 m and R²: 0.96, RMSE: 0.8 m for E. grandis and E. dunnii, respectively. The most informative ALS metrics for the estimation of AGB and TV were metrics related to the elevation in parametric models (Elev.70 and Elev.75), while for the non-parametric models (k-NN) they were Elev.75 and canopy density. For Ho, the ALS metrics selected were also related to elevation both in the parametric (Elev.90 and Elev.99) and random forest models (Elev.max and Elev.75). The segmentation methodology proposed here matched closely the segments delineated by human operators, and provides a low-cost, cost-effective, easy to apply and update model aimed at generating AGB or TV maps for harvest tasks, based on rasters derived from ALS metrics. The present research shows the capacity of ALS metrics to improve extensive strategic inventories; validating and promoting the adoption of ALS technology for inventory forest stands of Eucalyptus spp. in Uruguay.

中文翻译：

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桉树的林分特征。使用机载激光雷达扫描仪技术的乌拉圭人工林

机载激光雷达扫描仪（ALS）技术用于包括林业在内的各种应用中。ALS在估算人工林相关生物特征参数方面具有巨大潜力。本研究探讨用于看台划分的基础上，模拟ALS数据，在种植园中使用的面向对象的半自动分割算法的巨桉和E.邓恩桉乌拉圭。结果表明，非参数方法递送更精确和更少偏置结果总体积（TV），其中R ² 0.93，RMSE20.04米³ ħ ^-1为巨桉和R ² 0.93，RMSE18.43米³ ħ ^-1为邓氏大肠杆菌 和地上生物量（AGB），其中R ² 0.95，RMSE70.2公斤ħ ^-1为巨桉和R ² 0.96，RMSE：71.2公斤ħ ^-1为ë。邓尼 参数方法对于优势高度（Ho）表现更好，对于大肠埃希氏菌和大肠埃希氏菌，R ^2为0.98，RMSE为0.67 m，R ²为0.96，RMSE：0.8 m 。， 分别。估计AGB和TV的最有用的ALS指标是与参数模型（Elev.70和Elev.75）中的海拔高度相关的指标，而对于非参数模型（k-NN），它们是Elev.75和树冠密度。对于Ho，在参数（Elev.90和Elev.99）和随机森林模型（Elev.max和Elev.75）中，所选的ALS指标也与海拔高度相关。此处提出的分割方法与人类操作员所描绘的分割紧密匹配，并提供了一种低成本，经济高效，易于应用和更新的模型，旨在基于ALS指标得出的栅格来生成用于收获任务的AGB或TV地图。本研究显示了ALS指标改善大量战略库存的能力。桉树属。在乌拉圭。