Abstract Forest fragmentation in the Cerrado biome exposes the tree species Myracrodruon urundeuva to the risk of extinction. Thus, the objective of the study was to evaluate silvicultural characteristics related to wood quality, based on genetic parameters estimated in two M. urundeuva progenies from natural populations, assessed in Bauru-SP (PBAU) and Selvíria-MS (PSEL), 31 years after planting. The genetic parameters were estimated according to the REML/BLUP (Restricted maximum likelihood/Best Linear Unbiased Prediction) method using a mixed linear model. The progeny tests detected genetic variation. In PSEL, more positive genetic correlations and a greater number of clusters were observed. Based on the heartwood/sapwood ratio, a higher genetic gain was predicted for PBAU, and for the basic wood density, the genetic gain of the populations was approximately the same. Consequently, the areas of the two progeny tests may be used as future seed orchards to ensure wood quality and long-term ex situ conservation.

RESUMO São poucos os estudos dedicados a entender a criação de modelo digital de terreno (MDT) para florestas amazônicas. O MDT tem uma importante função quando o escaneamento laser aerotransportado é usado para estimar a biomassa da vegetação. Examinamos a relação da densidade de pulsos, resolução espacial, algoritmos de filtragem, densidade da vegetação e inclinação do terreno com a qualidade do MDT. Três áreas de floresta amazônica foram sobrevoadas usando LiDAR aerotransportado. Cada nuvem de dados original teve sua densidade reduzida objetivando 20; 15; 10; 8; 6; 4; 2; 1; 0,75; 0,5 e 0,25 pulsos por metro quadrado, utilizando um processo de reamostragem aleatória. Os MDTs das nuvens reamostradas foram comparados com o MDT de referência, produzido a partir da nuvem original, calculando o desvio pixel a pixel e resumindo-o por meio do erro padrão da estimativa (RMSE). Os MDTs das nuvens reamostradas também foram avaliados quanto ao nível de correspondência com o MDT de referência. Houve uma clara compensação entre densidade de pontos e resolução horizontal. Dosséis mais densos exigem uma maior densidade de retornos, ou MDT com menor resolução.

ABSTRACT Very few studies have been devoted to understanding the digital terrain model (DTM) creation for Amazon forests. DTM has a special and important role when airborne laser scanning is used to estimate vegetation biomass. We examined the influence of pulse density, spatial resolution, filter algorithms, vegetation density and slope on the DTM quality. Three Amazonian forested areas were surveyed with airborne laser scanning, and each original point cloud was reduced targeting to 20, 15, 10, 8, 6, 4, 2, 1, 0.75, 0.5 and 0.25 pulses per square meter based on a random resampling process. The DTM from resampled clouds was compared with the reference DTM produced from the original LiDAR data by calculating the deviation pixel by pixel and summarizing it through the root mean square error (RMSE). The DTM from resampled clouds were also evaluated considering the level of agreement with the reference DTM. Our study showed a clear trade-off between the return density and the horizontal resolution. Higher forest canopy density demanded higher return density or lower DTM resolution.