ASSESSING ALTERNATIVES TO ESTIMATE THE STEM VOLUME OF A SEASONAL SEMI-DECIDUOUS FOREST

The objective of this study was to evaluate the use of linear and hybrid linear models, artificial neural networks (ANN) and support vector machine (SVM) in the estimation of the stem volume in a Seasonal Semi-deciduous Forest. Cubing data of 99 sample-trees of 15 species were used for this purpose. After analysis, we verified that the inclusion of the species as random effect did not contribute to increase the accuracy of the estimates in the structure of a hybrid model. Artificial neural networks and support vector machines, including species as input categorical variables, were the best alternatives to estimate the stem volume of trees of the Seasonal Semi-deciduous Forest. AbstractThe objective of this study was to evaluate the use of linear and hybrid linear models, artificial neural networks (ANN) and support vector machine (SVM) in the estimation of the stem volume in a Seasonal Semi-deciduous Forest. Cubing data of 99 sample-trees of 15 species were used for this purpose. After analysis, we verified that the inclusion of the species as random effect did not contribute to increase the accuracy of the estimates in the structure of a hybrid model. Artificial neural networks and support vector machines, including species as input categorical variables, were the best alternatives to estimate the stem volume of trees of the Seasonal Semi-deciduous Forest.Keywords: Stem volume; artificial neural networks; support vector machines; hybrid linear models; uneven-aged forest. ResumoAvaliando alternativas para estimar o volume do fuste de uma Floresta Estacional Semidecidual. O objetivo desse estudo foi   avaliar o uso de modelos lineares e lineares mistos, redes neurais   artificiais (RNA) e máquina de vetor de suporte (MVS) na estimação dos   volumes dos fustes de árvores em uma Floresta Estacional Semidecidual. Dados de cubagem de 99 árvores-amostra   de 15 espécies foram utilizados para esta finalidade. Após análises, verificou-se que   a inclusão das espécies como efeito aleatório não contribuiu para aumentar a   exatidão das estimativas na estrutura de um modelo misto. As redes neurais artificiais e   as máquinas de vetores de suporte, incluindo as espécies como variáveis   categóricas de entrada, foram as melhores alternativas para estimar o volume   dos fustes das árvores da Floresta Estacional Semidecidual.Palavras-chaves: Volume do   fuste; redes neurais artificiais; máquinas de vetor de suporte; modelos   lineares mistos; floresta inequiânea.

Crescimento e produção de povoamentos de teca em diferentes espaçamentos

The objective of this work was to evaluate the growth and yield of teak (Tectona grandis) stands at different spacing and in different soil classes. Twelve spacing were evaluated in an Inceptisol and Oxisol, in plots with an area of 1,505 or 1,548 m2, arranged in a completely randomized design with nine replicates. The teak trees were measured at 26, 42, 50, and 78 months of age. Total tree height was less affected by spacing. Mean square diameter was greater in wider spacing, whereas basal area and total volume with bark were greater in closer spacing. An increase in volume with bark per tree was observed with the increase of useful area per plant. For teak trees, growth stagnation happens earlier, the growth rate is higher in closer spacing, and the plants grow more in the Inceptisol than in the Oxisol.O objetivo deste trabalho foi avaliar o crescimento e a produção de povoamentos de teca (Tectona grandis) em diferentes espaçamentos e classes de solo. Foram avaliados 12 espaçamentos em Cambissolo e Latossolo, dispostos em parcelas com área de 1.505 ou 1.548 m2, em delineamento inteiramente casualizado, com nove repetições. As plantas de teca foram medidas aos 26, 42, 50 e 78 meses de idade. A altura total das árvores foi menos influenciada pelos espaçamentos. O diâmetro quadrático médio foi superior nos maiores espaçamentos, enquanto a área basal e o volume total com casca foram superiores nos espaçamentos mais adensados. Observou-se aumento do volume com casca por árvore com o aumento da área útil por planta. Em teca, a estagnação do crescimento ocorre mais cedo, a taxa de crescimento é maior nos espaçamentos mais adensados e as plantas crescem mais em Cambissolo do que em Latossolo

CAN LINEAR PROGRAMMING ASSIST METAHEURISTICS IN FOREST PRODUCTION PLANNING PROBLEM?

The planning of forest production requires the adoption of mathematical models to optimize the utilization of available resources. Hence, studies involving the improvement of decision-making processes must be performed. Herein, we evaluate an alternative method for improving the performance of metaheuristics when they are applied for identifying solutions to problems in forest production planning. The inclusion of a solution obtained by rounding the optimal solution of linear programming to a relaxed problem is investigated. Such a solution is included in the initial population of the clonal selection algorithm, genetic algorithm, simulated annealing, and variable neighborhood search metaheuristics when it is used to generate harvest and planting plans in an area measuring 4,210 ha comprising 120 management units with ages varying between 1 and 6 years. The same algorithms are executed without including the solutions mentioned in the initial population. Results show that the performance of the clonal selection algorithm, genetic algorithm, and variable neighborhood search algorithms improved significantly. Positive effects on the performance of the simulated annealing metaheuristic are not indicated. Hence, it is concluded that rounding off the solution to a relaxed problem is a good alternative for generating an initial solution for metaheuristics

Curvas de índices de local em povoamentos de eucalipto obtidas por regressão quantílica

The objective of this work was to obtain site index curves in eucalyptus plantations by quantile regression, and to compare them to the obtained ones with the use of fitted regressions by the method of ordinary least squares. Quantile regression can be used to generate site index curves, especially in the presence of outliers. The method generates a bundle of curves better adjusted to the observed data, compared to the one generated with the estimates of ordinary least squares, either by the guide curve method (anamorphic curves) or by polymorphic curves (using different percentiles).O objetivo deste trabalho foi obter curvas de índice de local, em povoamentos de eucalipto, por meio de regressão quantílica, e compará‑las às obtidas com o uso de regressões ajustadas pelo método de mínimos quadrados ordinários. A regressão quantílica pode ser utilizada para a geração de curvas de índice de local, especialmente em presença de dados discrepantes. O método gera um feixe de curvas mais bem ajustadas aos dados observados, em comparação ao feixe gerado com as estimativas de mínimos quadrados ordinários, seja pelo método da curva‑guia (curvas anamórficas), seja pela geração de curvas polimórficas (com o uso de diferentes percentis)

USE OF QUANTILE REGRESSION AND RANSAC ALGORITHM IN FITTING VOLUME EQUATIONS UNDER THE INFLUENCE OF DISCREPANT DATA

The objective of this study was to evaluate three estimation methods to fit volume equations in the presence of influential or leverage data. To do so, data from the forest inventory carried out by the Centro Tecnológico de Minas Gerais Foundation were used to fit the Schumacher and Hall (1933) model in its nonlinear form for Cerradão forest, considering the quantile regression (QR), the RANSAC algorithm and the nonlinear Ordinary Least Squares (OLS) method. The correlation coefficient ( ) between the observed and estimated volumes, root-mean-square error (RMSE), as well as graphical analysis of the dispersion and distribution of the residuals were used as criteria to evaluate the performance of the methods. After the analysis, the nonlinear least squares method presented a slightly better result in terms of the goodness-of-fit statistics, however it altered the expected trend of the fitted curve due to the presence of influential data, which did not happen with the QR and the RANSAC algorithm, as these were more robust in the presence of discrepant data

Forest restoration monitoring through digital processing of high resolution images

Monitoring and evaluating forest restoration projects is a challenge especially in large-scale, but the remote monitoring of indicators with the use of synoptic, multispectral and multitemporal data allows us to gauge the restoration success with more accurately and in small time. The objective of this study was to elaborate and compare methods of remote monitoring of forest restoration using Light Detection and Ranging (LIDAR) data and multispectral imaging from Unmanned Aerial Vehicle (UAV) camera, in addition to comparing the efficiency of supervised classification algorithms Maximum Likelihood (ML) and Random Forest (RF). The study was carried out in a restoration area with about 74 ha and five years of implementation, owned by Fibria Celulose S.A., in the southern region of Bahia State, Brazil. We used images from Canon S110 NIR (green, red, Near Infrared) on UAV and LIDAR data composition (intensity image, Digital Surface Model, Digital Terrain Model, normalized Digital Surface Model). The monitored restoration indicator was the land cover separated in three classes: canopy cover, bare soil and grass cover. The images were classified using the ML and RF algorithms. To evaluate the accuracy of the classifications, the Overall Accuracy (OA) and the Kappa index were used, and the last was compared by Z test. The area occupied by different land cover classes was calculated using ArcGIS and R. The results of OA, Kappa and visual evaluation of the images were excellent in all combinations of the imaging methods and algorithms analyzed. When Kappa values for the two algorithms were compared, RF presented better performance than ML with significant difference, but when sensors (UAV camera and LIDAR) were compared, there were no significant differences. There was little difference between the area occupied by each land cover classes generated by UAV and LIDAR images. The highest cover was generated for canopy cover followed by grass cover and bare soil in all classified images, indicating the need of adaptive management interventions to correct the area trajectory towards the restoration success. The methods employed in this study are efficient to monitor restoration areas, especially on a large scale, allowing us to save time, fieldwork and invested resources

Growth and yield of commercial plantations of eucalyptus estimated by two categories of models

O objetivo deste trabalho foi avaliar e comparar duas categorias de modelos de crescimento e produção em plantios comerciais de eucalipto. Para isso, foram ajustados um modelo de crescimento e produção para povoamento e outro para árvore individual, por meio de equações simultâneas e redes neurais artificiais, respectivamente. O volume de madeira por área foi estimado em diferentes idades e classes de produtividade. Foram avaliados dados de 63 parcelas permanentes de plantios clonais, não desbastados, do híbrido Eucalyptus grandis x E. urophylla, com os dados de 33 parcelas utilizados para o ajuste do modelo e o treinamento das redes neurais, e os das 30 parcelas restantes, para a validação dos modelos. As duas categorias de modelos ajustaram-se bem aos dados observados. No entanto, na validação dos modelos com dados independentes, o volume de madeira por área foi mais bem estimado com o modelo para árvore individual.The objective of this work was to evaluate and compare two categories of growth and yield models of commercial plantations of eucalyptus. For that, a whole stand model, and an individual tree growth model were adjusted through simultaneous equations and artificial neural networks, respectively. Wood volume per area was estimated for tree different ages and productivity classes. Data of 63 permanent plots of unthinned clonal hybrid Eucalyptus grandis x E. urophylla were evaluated, from which those referring to 33 plots were used for model fitting and neural network training, and those referring to the other 30 plots were used for model validation. The two categories of models adjusted well to the observed data. However, for the validation of the models with independent data, the wood volume per area was better estimated with the individual tree growth model

Influência de estimativas de produção de madeira em processos de regulação florestal utilizando programação linear.

The main objective of this work was to evaluate the consequences of the use of yield and growth estimates from different prediction yield and growth models in a Linear Programming model applied to forest regulation. Thus, using data of continuous forest inventory, the yield estimation in future volume was obtained using a yield model based on age, another one based on age and site index, and a third model that used age and site index besides density, which was represented by the basal area per hectare. Also a model based on data of continuous forest inventory which uses data of volume on a period of time to make linear projections of yield for the next period was tested. Next, a simplified forest regulation problem was proposed and solved by the model I by means of Linear Programming, using data from the four volume prediction models. At the end, the conclusion was: a) that models of forest regulation, supplied with estimates from different yield models, when solved by Linear Programming, result in different ways of treating the forests; b) that the matrix of technological coefficients, supplied with different yield data and for a same objective function affects in a significant way the decision making process.Este trabalho teve como principal objetivo avaliar as conseqüências do uso de estimativas de produção oriundas de diferentes modelos de crescimento e produção em um modelo de Programação Linear aplicado à regulação florestal. Assim, utilizando dados de um inventário florestal contínuo, obtiveram-se diferentes estimativas da produção futura em volume, pelo ajuste de um modelo de produção em função da idade, outro em função da idade e do índice de local e por um terceiro modelo que incluiu, além da idade e do índice de local, a densidade, representada pela área basal por hectare. Testou-se também um modelo baseado nos dados de inventário florestal contínuo que utiliza os dados de volume de um período para fazer projeções lineares da produção para o período seguinte. Em seguida, um problema de regulação florestal simplificado foi idealizado e resolvido pelo modelo I por meio de Programação Linear, utilizando dados oriundos dos quatro modelos de predição do volume. Ao final, concluiu-se: a) que modelos de regulação florestal, alimentados por estimativas provenientes de diferentes modelos de produção, quando resolvidos por Programação Linear, resultam em diferentes maneiras de se conduzir a floresta; b) que a matriz de coeficientes tecnológicos, alimentada por diferentes dados de produção e para uma mesma função objetivo, afeta, de maneira significativa, o processo de tomada de decisão

Classificação da capacidade produtiva de povoamentos não desbastados de clones de eucalipto

The objective of this work was to develop and propose a procedure for stratification of unthinned eucalyptus clone forest, in order to classify its productive capacity. Data from 70 clones, distributed into 5,020 permanent plots of continuous forest inventories, were used with at least three annual measurements for each clone. For all clones, the Schumacher model was fit for the variables: basal area; dominant height; mean diameter; and commercial volume, with bark. The Tocher method was used to group clones displaying similar dominant height growth tendencies, and this procedure showed to be efficient. Site index estimate, for clones with less than tree measurements, can be determined from information regarding dominant height, mean diameter, basal area and commercial volume obtained from continuous forest inventories.O objetivo deste trabalho foi desenvolver e propor um procedimento para a estratificação de florestas de clones de eucalipto não desbastados, para a classificação de sua capacidade produtiva. Utilizaram-se dados provenientes de 70 clones, distribuídos em 5.020 parcelas permanentes de inventários florestais contínuos, com pelo menos três medições, de periodicidade anual, em cada clone. Para todos os clones, foi ajustado o modelo de Schumacher para as variáveis: área basal; altura dominante; diâmetro médio; e volume comercial, com casca. Com esses parâmetros, foi utilizado o método de Tocher, que se mostrou eficiente para agrupar clones com tendências semelhantes de crescimento em altura dominante. A estimativa de índice de local, para clones com menos de três medições, pode ser determinada a partir das informações de altura dominante, diâmetro médio, área basal e volume, obtidas do inventário florestal contínuo de outros clones