The Global Ecosystem Dynamics Investigation LiDAR (GEDI) is a new full waveform (FW) based LiDAR system that presents a new opportunity for the observation of forest structures globally. The backscattered GEDI signals, as all FW systems, are distorted by topographic conditions within their footprint, leading to uncertainties on the measured forest variables. In this study, we explore how well several approaches based on waveform metrics and ancillary digital elevation model (DEM) data perform on the estimation of stand dominant heights ($H_{dom}$) and wood volume (V) across different sites of Eucalyptus plantations with varying terrain slopes. In total, five models were assessed on their ability to estimate $H_{dom}$ and four models for V. Results showed that the models using the GEDI metrics, such as the height at different energy quantiles with terrain data from the shuttle radar topography mission’s (SRTM) digital elevation model (DEM) were still dependent on the topographic slope. For $H_{dom}$, an RMSE increase of 14% was observed for data acquired over slopes higher than 20% in comparison to slopes between 10 and 20%. For V, a 74% increase in RMSE was reported between GEDI data acquired over slopes between 0–10% and those acquired over slopes higher than 10%. Next, a model relying on the height at different energy quantiles of the entire waveform ($H{T}_n$) and the height at different energy quartiles of the bare ground waveform ($H{G}_n$) was assessed. Two sets of the $H{G}_n$ metrics were generated, the first one was obtained using a simulated waveform representing the echo from a bare ground, while the second one relied on the actual ground return from the waveform by means of Gaussian fitting. Results showed that both the simulated and fitted models provide the most accurate estimates of $H_{dom}$ and V for all slope ranges. The simulation-based model showed an RMSE that ranged between 1.39 and 1.66 m (between 26.76 and 39.26 m³·ha⁻¹ for V) while the fitting-based method showed an RMSE that ranged between 1.26 and 1.34 m (between 26.78 and 36.29 m³·ha⁻¹ for V). Moreover, the dependency of the GEDI metrics on slopes was greatly reduced using the two sets of metrics. As a conclusion, the effect of slopes on the 25-m GEDI footprints is rather low as the estimation on canopy heights from uncorrected waveforms degraded by a maximum of 1 m for slopes between 20 and 45%. Concerning the wood volume estimation, the effect of slopes was more pronounced, and a degradation on the accuracy (increased RMSE) of a maximum of 20 m³·ha⁻¹ was observed for slopes between 20 and 45%.

Over the past two decades spaceborne LiDAR systems have gained momentum in the remote sensing community with their ability to accurately estimate canopy heights and aboveground biomass. This article aims at using the most recent global ecosystem dynamics investigation (GEDI) LiDAR system data to estimate the stand-scale dominant heights ( H _dom ), and stand volume (V) of Eucalyptus plantations in Brazil. These plantations provide a valuable case study due to the homogenous canopy cover and the availability of precise field measurements. Several linear and nonlinear regression models were used for the estimation of H _dom and V based on several GEDI metrics. H _dom and V estimation results showed that over low-slopped terrain the most accurate estimates of H _dom and V were obtained using the stepwise regression, with an root-mean-square error (RMSE) of 1.33 m (R ² of 0.93) and 24.39 m ³ .ha ^-1 (R ² of 0.90) respectively. The principal metric explaining more than 87% and 84% of the variability (R ² ) of H _dom and V was the metric representing the height above the ground at which 90% of the waveform energy occurs. Testing the postprocessed GEDI metric values issued from six available different processing algorithms showed that the accuracy on H _dom and V estimates is algorithm dependent, with a 16% observed increase in RMSE on both variables using algorithm a5 vs. a1. Finally, the choice to select the ground return from the last detected mode or the stronger of the last two modes could also affect the H _dom estimation accuracy with 12 cm RMSE decrease using the latter.

To identify stable and productive Eucalyptus urophylla S.T. Blake families across diverse climate zones in Brazil, we evaluated growth and survival of 322 open-pollinated families derived from 13 genetically improved seed sources in 10 trials across the country. Survival and growth data were analyzed using linear mixed models and REML/BLUP. Survival ranged from 51% to 92%, and the mean annual increment varied from 19 to 46 m³·ha⁻¹·year⁻¹. Although planted in suitable climatic zones, some trials had low survival and (or) productivity. Conversely, the highest productivity was recorded in a zone considered to be of low suitability. These results show the importance of assessing the climatic requirements of eucalypts beyond those determined from analyses of their natural distribution, especially when testing already improved seed sources. A number of productive and stable families were identified based on analysis of the interaction between genotype and environment, and from these, 144 individuals were selected and had their genetic diversity estimated using 19 microsatellite DNA markers. The genetic diversity of these selected trees was equivalent to that observed in previous studies of natural populations of E. urophylla, indicating that breeding programs of E. urophylla in Brazil still retain high levels of diversity for sustainable genetic gains.

The objective was to select productive and stable E. grandis families across contrasting sites in Brazil and Uruguay. Survival and growth of 130 open pollinated families were evaluated three years after planting. Survival ranged from 28 to 89% and mean annual increment from 20.5 to 48.4 m³ha^- y^-1. Low productivity in one site was attributed to unusually low rainfall and in the other, because of Cylindrocladium leaf disease. Heritability among families and the correlation family by environment were intermediate. Genetic pairwise correlations ranged from 0.03 to 0.81 across sites. The lowest genetic correlation between sites was observed where Cylindrocladium leaf disease occurs. Selection of top families across sites allowed selecting the best ones in each site. However, the effect of genotype-environment interactions was observed where climatic conditions are not adequate to the E. grandis, favoring the occurrence of Cylindrocladium disease.