Woody plant encroachment in grassy ecosystems is a widely reported phenomenon associated with negative impacts on ecosystem functions. Most studies of this phenomenon have been carried out in arid and semi-arid grasslands. Therefore, studies in tropical regions, particularly savannas, which are composed of grassland and woodland mosaics, are needed. Our objective was to evaluate the accuracy of woody encroachment classification in the Brazilian Cerrado, a tropical savanna. We acquired dry and wet season unmanned aerial vehicle (UAV) images using RGB and multispectral cameras that were processed by the support vector machine (SVM), decision tree (DT), and random forest (RF) classifiers. We also compared two validation methods: the orthomosaic and in situ methods. We targeted two native woody species: Baccharis retusa and Trembleya parviflora. Identification of these two species was statistically (p < 0.05) most accurate in the wet season RGB images classified by the RF algorithm, with an overall accuracy (OA) of 92.7%. Relating to validation assessments, the in situ method was more susceptible to underfitting scenarios, especially using an RF classifier. The OA was higher in grassland than in woodland formations. Our results show that woody encroachment classification in a tropical savanna is possible using UAV images and field surveys and is suggested to be conducted during the wet season. It is challenging to classify UAV images in highly diverse ecosystems such as the Cerrado; therefore, whenever possible, researchers should use multiple accuracy assessment methods. In the case of using in situ accuracy assessment, we suggest a minimum of 40 training samples per class and to use multiple classifiers (e.g., RF and DT). Our findings contribute to the generation of tools that optimize time and cost for the monitoring and management of woody encroachment in tropical savannas.

Traditional forest restoration (FR) monitoring methods employ spreadsheets and photos taken at the ground level. Since remotely piloted aircraft (RPA) generate a panoramic high resolution and georeferenced view of the entire area of interest, this technology has high potential to improve the traditional FR monitoring methods. This study evaluates how low-cost RPA data may contribute to FR monitoring of the Brazilian Atlantic Forest by the automatic remote measurement of Tree Density, Tree Height, Vegetation Cover (area covered by trees), and Grass Infestation. The point cloud data was processed to map the Tree Density, Tree Height, and Vegetation Cover parameters. The orthomosaic was used for a Random Forest classification that considered trees and grasses as a single land cover class. The Grass Infestation parameter was mapped by the difference between this land cover class (which considered trees and grasses) and the Vegetation Cover results (obtained by the point cloud data processing). Tree Density, Vegetation Cover, and Grass Infestation parameters presented F_scores of 0.92, 0.85, and 0.64, respectively. Tree Height accuracy was indicated by the Error Percentage considering the traditional fieldwork and the RPA results. The Error Percentage was equal to 0.13 and was considered accurate because it estimated a 13% shorter height for trees that averaged 1.93 m tall. Thus, this study showed that the FR structural parameters were accurately measured by the low-cost RPA, a technology that contributes to FR monitoring. Despite accurately measuring the structural parameters, this study reinforced the challenge of measuring the Biodiversity parameter via remote sensing because the classification of tree species was not possible. After all, the Brazilian Atlantic Forest is a biodiversity hotspot, and thus different species have similar spectral responses in the visible spectrum and similar geometric forms. Therefore, until improved automatic classification methods become available for tree species, traditional fieldwork remains necessary for a complete FR monitoring diagnostic.

Remotely Piloted Aircraft Systems (RPAS) are already a reality in Brazil. They are used in different fields of knowledge to obtain digital products that contribute to the identification, monitoring, control, and precision of the agricultural decision process. However, the cost-benefit of applying this technology to produce seedlings in commercial tomato nurseries needs better evaluation. This research analyzes the use of an RPAS with RGB camera over areas of table tomato seedlings and compares the cartographic products with the information obtained through semi-structured interviews with rural property owners in the States of Goiás, Minas Gerais, and the Federal District (Brasília). The results were not divided into external area applications and internal (greenhouse) mapping, as adopting technology for monitoring the seedling production process inside greenhouses is still economically unfeasible compared to human identification, thus not justifying the investment. Nonetheless, images of the external area provide crucial information for planning a nursery, considering its structural aspects and adequate disposal. Keywords: Seedling production; Digital Image Processing; UAV; Drones.

A produção de mudas em formato comercial compreende o fornecimento de um insumo-chave na produção de hortaliças, que se vincula aos demais elos da cadeia produtiva, numa estreita relação de causa e efeito. Neste trabalho, objetivou-se identificar o perfil dos empreendedores e as características dos empreendimentos que produzem mudas de tomate de mesa destinadas ao estado de Goiás. Para tanto, adotou-se uma abordagem exploratória e descritiva, com a aplicação de questionário e análise do discurso, compreendendo, portanto, em uma pesquisa de natureza quali-quantitativa. Os resultados evidenciaram que os viveiros se encontram estrategicamente instalados próximo ou nos municípios que figuram como maiores produtores de tomate fresco no estado, sendo as relações comerciais estabelecidas e mantidas de acordo com a qualidade física, nutricional e sanitária das mudas produzidas. Verificou-se ainda que os materiais semeados são definidos considerando a demanda de mercado, associada à resistência a pragas e doenças, sendo um ponto de atenção, na tomaticultura de mesa, desde a produção das mudas, o manejo de defensivos utilizados. Ademais, os viveiristas sinalizam a estagnação do setor, imposta por fatores como: redução da área plantada, aumento dos custos de produção, redução do poder de compra do consumidor, oscilações do preço pago ao produtor, dentre outros fatores que intensificam os riscos econômicos e financeiros da atividade, apontando, portanto, a necessidade de ações que contemple os diferentes atores da cadeia produtiva do tomate de mesa.

Em Goiás a apicultura é uma atividade de grande importância econômica e ambiental. Com clima favorável e flora diversificada, o estado de Goiás apresenta excelente potencial para a produção de mel e seus derivados. Nesse contexto, os Arranjos Produtivos Locais (APLs) têm importante papel na organização e fortalecimento do setor. O objetivo deste artigo é realizar uma análise comparativa e descritiva de diferentes APLs apícolas de Goiás, destacando as especificidades de cada arranjo e região. Para tanto será adotado como procedimento metodológico o levantamento bibliográfico e documental de dados disponibilizados por Instituto de pesquisa. Os resultados sinalizam as diferenças na produção melífera por arranjo, assim como a carência de dados atualizados acerca dos arranjos produtivos do mel no estado, o que potencialmente compromete o fortalecimento da cadeia do mel no Estado. Ao mesmo tempo, reforça a fragilidade dos arranjos produtivos como políticas pública desenvolvimentista, quando tratada como política de Governo e não de Estado.