Aim of study: In this study we applied 3D point clouds generated by images obtained from an Unmanned Aerial Vehicle (UAV) to evaluate the uniformity of young forest stands.Area of study: Two commercial forest stands were selected, with two plots each. The forest species studied were Eucalyptus spp. and Pinus taeda L. and the trees had an age of 1.5 years.Material and methods: The individual trees were detected based on watershed segmentation and local maxima, using the spectral values stored in the point cloud. After the tree detection, the heights were calculated using two approaches, in the first one using the Digital Surface Model (DSM) and a Digital Terrain Model, and in the second using only the DSM. We used the UAV-derived heights to estimate an uniformity index.Main results: The trees were detected with a maximum 6% of error. However, the height was underestimated in all cases, in an average of 1 and 0.7 m for Pinus and Eucalyptus stands. We proposed to use the models built herein to estimate tree height, but the regression models did not explain the variably within the data satisfactorily. Therefore, the uniformity index calculated using the direct UAV-height values presented results close to the field inventory, reaching better results when using the second height approach (error ranging 2.8-7.8%).Research highlights: The uniformity index using the UAV-derived height from the proposed methods was close to the values obtained in field. We noted the potential for using UAV imagery in forest monitoring.

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Resumo-O objetivo deste trabalho foi realizar o ajuste de modelos para estimar biomassa e carbono total de indivíduos de caixeta (Tabebuia cassinoides (Lam.) DC.), localizado em Guaratuba, litoral Paranaense, Brasil. Foram testados 13 modelos, e a escolha do melhor baseou-se nos indicadores estatísticos R 2 aj , S yx (%) e análise gráfica dos resíduos. Realizou-se ainda, como critério complementar de escolha, a avaliação das condicionantes de regressão dos resíduos dos melhores modelos. Não foram feitos ajustes de biomassa e carbono por compartimentos devido à baixa correlação entre as variáveis dependentes (biomassa e carbono) e independentes, diâmetro à altura do peito (dap) e altura total (h). Para a biomassa total, o modelo Y = β0 + β1*dap se mostrou superior aos demais, apresentando um R 2 aj de 0,96 e S yx (%) de 7,94. Para carbono, melhor ajuste foi obtido pelo modelo (Y = β0 + β1*dap + β2*dap² + β3*dap³ + β4*dap 4 , com valores de R 2 aj 0,97 e S yx (%) 8,09. Constatou-se a baixa variação dos resíduos para ambos os modelos. A variável altura total, utilizada de forma isolada, revelou-se inadequada para explicar as variáveis biomassa total e carbono total. Estimation of yotal biomass and carbon for caixeta trees in Parana State, Brazil

The Geoprocessing has been considered a fundamental tool in the definition of intervention policies and environmental management. This work presents a methodological guide of application of Geoprocessing technologies to characterize the environmental fragility of Arroio Cadena sub river basin, inserted in the municipality of Santa Maria, central region of Rio Grande do Sul state. We used the methodology proposed by Ross in (1994), which is based in the comprehension of the characteristics and the dynamics of the natural environment. To evaluate the fragility, it is established weights or grades to each situation that the variables can present. We used as indicators of the potential environmental fragility, the factors: declivity and soil type, and as indicators of emerging fragility, the factors: declivity, soil type and the use and occupation of the land. Among the uses of the basin, the areas of soil that is exposed and urbanization predominate. The basin has a weak potential fragility, with 52.9% in relation to the total area, and it is a consequence of the flat declivity aggregated in the soil type. It presents a strong emerging fragility, with 37.7% of the total area, due to the irregular occupations and the inadequate use of natural resources.

ResumoEste trabalho teve como objetivo predizer a biomassa acima do solo (AGB) em plantações de Pinus taeda L., localizados na região sul do Brasil. A base de dados utilizada no estudo foi originada de levantamentos a laser aerotransportados (LiDAR), complementados por informações de campo. Os modelos preditores da biomassa foram ajustados por modelagem não paramétrica, Random Forests (RF), implementado no ambiente R. Para compor os dados de campo foram inventariadas 50 parcelas de área fixa, nas quais foram mensurados os diâmetros de todas as árvores e parte das alturas. Posteriormente o volume individual foi estimado por modelos polinomiais de quinto grau e serviu de base para o cálculo dos valores de AGB. O modelo final, preditor da biomassa, foi composto pelas métricas LiDAR referente a Altura no percentil 99 (H99TH), Coeficiente de Variação da Altura (HCV) e Assimetria da altura (HSKEW) por proporcionarem baixa correlação entre si, e fornecerem os maiores valores de Razão de Melhoria do Modelo (MIR). O modelo final apresentou um o coeficiente de determinação ajustado (R 2 aj. ) de 0,98, Raiz Quadrada do Erro Médio (RMSE) de 5,98%, enquanto que para a validação, esses valores foram de 0,93 e 12,64%, respectivamente. Portanto conclui-se que o modelo gerou resultados satisfatórios na predição da biomassa aérea em plantações de P. taeda, podendo ser considerado como uma ferramenta eficaz no manejo de florestas plantadas. Palavras-chave:Inventário Florestal, Modelagem Não-paramétrica, Plantações Florestais, Métricas LiDAR. AbstractThe aim of this study was to predict aboveground biomass (AGB) from Pinus taeda L. plantations, located in South of Brazil, using LiDAR data, in-situ measurements and Random Forests (RF) modeling. Fifty regular sample plots were used, in which the diameter at the breast height (DBH) for all trees and about 15% of the heights were measured. Afterwards. forest stem volume was predicted using a fifth degree polynomial model, and used to calculate the field AGB values. To create the RF model we selected the H99TH, HCV and HSKEW LiDAR metrics, because they were not highly correlated to each other and presented the higher calculated value of Model Improvement Ratio (MIR). The estimative model of AGB presented a coefficient of determination (Adj.R 2 ) of 0.98 and RMSE of 5.98%, while for the validation these values were 0.93 and 12.64%, respectively. It was possible to conclude that the RF and LiDAR-derived metrics were able to predict precisely the values of AGB in P. taeda plantation, therefore, it can be used as a helpful tool to forest management.

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SUMMARYThe aim of this study was to analyze the environmental fragility of Iguaçu River watershed, Paraná. Regarding fragility potential, most watersheds fell under the moderate fragility class (40.47 % of the total), followed by very low (18.83 %), low (16.20 %), high (13.27 %) and very high with only 8.68 %. Concerning emerging fragility, most watersheds again lay within moderate fragility (41.55 %), though in this case low fragility was found in second place (with 40.73 %), followed by very low (7.67 %), high (6.50 %) and very high (0.99 %). Urban areas corresponded to 1.37 % and bodies of water to 1.18 % of the area. From a visual analysis, emerging fragility was observed to be high and very high, when present, followed by flooded areas; thus, demonstrating the importance of considering them in such studies, since they are environments with very unstable structural features including certain soil types, significant erosion from water, among others. The results of certain classes also appeared to depend on the weights given to factors considered as affecting the outcome. When the mean fragility methodology was used, the classes tended to follow a normal distribution, i.e. with a dominant moderate class. Therefore one can conclude that determining the importance of each factor is essential in evaluating environmental fragility, and therefore, weights should be carefully defined for each situation.Key words: environmental planning, land use, vulnerability. RESUMENEl objetivo de este estudio fue analizar la fragilidad ambiental de la cuenca del río Iguaçu, Paraná. El potencial de la fragilidad, la mayor parte de la cuenca se encuentra en la clase media de la debilidad (40.47 % del total), seguido por la clase muy baja (18,83 %), baja (16,20 %), alto (13,27 %) y muy alta con sólo 8,68 %. En cuanto a la fragilidad emergentes, la mayoría de la taza de nuevo está en la clase media de la debilidad (41,55 %), pero en este caso se encontró que la baja fragilidad en el segundo lugar (con el 40,73 %), seguido de clases muy bajas (7,67 %), alta (6,50 %) y muy alto (0,99 %). Las áreas urbanas corresponden a 1,37 % y los cuerpos de agua a 1,18 % de la superficie. También se observa a partir de análisis visual, las clases de fragilidad emergentes de alta y muy alta, cuando está presente, siguen las zonas de inundación, lo que demuestra la importancia de considerar en este tipo de estudios, ya que son entornos con características estructurales muy inestable debido a los tipos de suelo, la presencia de gran erosión por la fuerza del agua, entre otros. También se observó que el uso de diferentes factores de ponderación considera que afecta el resultado de ciertas clases y que cuando se utiliza la metodología de debilidad promedio de las clases es la tendencia de presentar una distribución normal, es decir, con el dominio de clase media. Por lo tanto, se puede observar que la determinación de la importancia de cada factor es dominante para la evaluación de la fragilidad ecologista, y por lo tanto, una definición de los mismos pe...