A fotogrametria moderna, combinada com Sistemas de Aeronaves Remotamente Pilotadas (RPAS) e algoritmos para análises tridimensionais, como o Structure-from-Motion (SfM) está revolucionando o campo da fotogrametria. No setor florestal, a crescente disponibilidade de dados coletados por RPAS oferece oportunidades promissoras para analisar padrões e características da superfície terrestre, além de suas distintas fitofisionomias. Este estudo explora o potencial de imagens obtidas por RPAS, com sensor RGB acoplado, para diferenciar e caracterizar cinco fitofisionomias do Cerrado: Campo Rupestre, Campo Sujo, Cerrado Sentido Restrito, Floresta Estacional Semidecidual e Pastagens. A análise das imagens resultou em métricas descritivas que capturaram as variações estruturais de cada fitofisionomia, revelando padrões distintos de altura e complexidade vertical da vegetação. Os resultados confirmaram a eficácia da metodologia para a diferenciação dessas formações vegetais, com destaque para a capacidade de caracterizar ambientes complexos e heterogêneos, como a Floresta Estacional Semidecidual. A utilização de sensores RGB demonstrou ser uma alternativa economicamente viável para o monitoramento de áreas extensas. Esses resultados têm importantes implicações para a gestão de recursos naturais, o planejamento territorial e o monitoramento ambiental, especialmente em ecossistemas ameaçados como o Cerrado. A metodologia aplicada pode reduzir significativamente os custos de monitoramento ambiental, contribuindo para a preservação da biodiversidade em diversos ecossistemas ao longo do tempo.

Thaumastocoris peregrinus is a pest that damages eucalyptus plantations. Recently in Brazil, there are few studies related to its control. With the advancement of molecular biology, several techniques can assist in the discovery of an effective and sustainable control. The different techniques of analysis of gene expression start with the extraction of the total RNA from the material for genomic analysis, hence it is essential that the RNA be intact. Numerous insect RNA extraction protocols are available, but none of them are widely effective, therefore, several factors and intrinsic characteristics of the tissue to be analyzed can affect the quality of the extracted material. Thus, it is necessary to modify the protocols in order to optimize the extraction of RNA. This study aimed to analyze the efficiency of three methods for RNA extraction from T. peregrinus. The results obtained demonstrated that the RNA extracted with only one method was more efficient due to less contamination with DNA and greater integrity of the samples. It should be noted that the determination of an efficient protocol for the extraction of RNA from T. peregrines will assist in future research, which will assist in the discovery of genes present in the extracted RNA sample. Key words: Ribonucleic acid, bronze bug, Eucalyptus.

This study assessed whether the additional spectral information provided by RPAS-based multispectral imagery improves semi-automatic individual tree crown segmentation relative to RGB imagery in young Eucalyptus spp. stands. RGB and multispectral datasets were acquired 180 days after planting. Representative variables derived from each sensor were selected using Principal Component Analysis and used as input for k-means segmentation, followed by vector-based post-processing and comparison with reference polygons delineated through visual photointerpretation. Multispectral segmentations achieved higher Precision, shorter centroid distances, greater Coincidence Range, and lower modified MSEI, indicating more accurate segment positioning, stronger boundary agreement with the reference delineations, and lower overall geometric discrepancy. Although RGB imagery produced a higher mean Recall, this was associated with lower spatial precision and a greater visual occurrence of merged adjacent crowns, thereby limiting the reliable individualisation of trees. These findings indicate that, in young Eucalyptus spp. stands, multispectral information improves key geometric aspects of individual tree crown segmentation, especially when the aim is to derive tree-level attributes.