This study explores the impact of Eucalyptus plantation characteristics and environmental factors on GEDI returned energy distribution. Random Forest (RF) regression was used to analyze the effect of a diverse parcel-scale Eucalyptus plantation characteristics including trees height, planting density, soil properties, understorey presence, environmental conditions and NDVI generated from Sentinel-2 as a proxy of leaf area index on the GEDI relative heights (RHn). According to the findings, as the vertical distance from the ground increases (from RH5 to RH100), the most important variable explaining a given relative height changes from "NDVI" to "Volume". Moreover, at higher quantiles of the returned energy, the behavior of the GEDI metrics becomes more dependent on a narrower set of forest and environmental characteristics. However, at low RH values, the interplay of complex canopy structures and environmental factors necessitates a combination of features to explain the observed variations.