Engenharia Florestal
URI permanente desta comunidadehttps://locus.ufv.br/handle/123456789/11734
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Resultados da Pesquisa
Item Growth and yield of teak stands at different spacing(Pesquisa Agropecuária Brasileira, 2018-10) Paiva, Haroldo Nogueira de; Leite, Helio Garcia; Medeiros, Reginaldo Antonio; D’Ávila, Flávio SiqueiraThe 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.Item Crescimento de eucalipto sob efeito de desfolhamento artificial(Pesquisa Agropecuária Brasileira, 2010-09) Matrangolo, Carlos Augusto Rodrigues; Castro, Renato Vinícius Oliveira; Mendes, Ana Flávia Neves; Costa, Júlia Melo Franco Neves; Leite, Helio Garcia; Della Lucia, Terezinha Maria Castro; Della Lucia, Ricardo MariusO objetivo deste trabalho foi avaliar os efeitos do desfolhamento total, realizado após o plantio e ao longo do primeiro ano de cultivo, sobre o crescimento de Eucalyptus grandis, desde a implantação até ao corte do povoamento. Foram avaliados cinco tratamentos: sem desfolhamento; um desfolhamento aos 56 dias após o plantio (DAP); dois desfolhamentos, aos 56 e 143 DAP; dois desfolhamentos, aos 56 e 267 DAP; e três desfolhamentos, aos 56, 143 e 278 DAP. Foram mensurados os diâmetros do tronco a 1,3 m e a altura total de 60 árvores por tratamento, em oito avaliações, do 21º ao 92º mês de cultivo. O crescimento médio em cada tratamento foi descrito por modelos de regressão não lineares e comparados por testes de identidade para comparar as tendências entre a testemunha e os demais tratamentos. O desfolhamento causou reduções significativas nas taxas de crescimento em diâmetro e altura das plantas, e diminuição expressiva no faturamento ao final da rotação, mesmo quando realizado uma única vez, no início do plantio. Maiores danos, no entanto, foram verificados após consecutivos desfolhamentos ao longo do primeiro ano de cultivo. A manutenção de áreas que tenham sofrido desfolhamento total na fase inicial de plantio pode tornar-se uma medida economicamente inviável.Item Artificial neural networks, quantile regression, and linear regression for site index prediction in the presence of outliers(Pesquisa Agropecuária Brasileira, 2019) Araújo Júnior, Carlos Alberto; Souza, Pábulo Diogo de; Assis, Adriana Leandra de; Cabacinha, Christian Dias; Leite, Helio Garcia; Soares, Carlos Pedro Boechat; Silva, Antonilmar Araújo Lopes da; Castro, Renato Vinícius OliveiraThe objective of this work was to compare methods of obtaining the site index for eucalyptus (Eucalyptus spp.) stands, as well as to evaluate their impact on the stability of this index in databases with and without outliers. Three methods were tested, using linear regression, quantile regression, and artificial neural network. Twenty-two permanent plots from a continuous forest inventory were used, measured in trees with ages from 23 to 83 months. The outliers were identified using a boxplot graphic. The artificial neural network showed better results than the linear and quantile regressions, both for dominant height and site index estimates. The stability obtained for the site index classification by the artificial neural network was also better than the one obtained by the other methods, regardless of the presence or the absence of outliers in the database. This shows that the artificial neural network is a solid modelling technique in the presence of outliers. When the cause of the presence of outliers in the database is not known, they can be kept in it if techniques as artificial neural networks or quantile regression are used.Item Sistema computacional para ajuste de funções densidade de probabilidade(Floresta e Ambiente, 2017) Binoti, Daniel Henrique Breda; Leite, Helio Garcia; Silva, Mayra Luiza Marques daEste trabalho teve por objetivo iniciar, implementar e validar um projeto de construção de um sistema computadorizado para ajuste de funções densidade de probabilidade. O FitFD foi desenvolvido utilizando-se a linguagem de programação Java. Como ambiente de desenvolvimento foram utilizadas a IDE (Integrated Development Environment) Netbeans 7.1 e a JDK 7.3 (Java Development Kit). Os testes do sistema foram realizados em ambiente Windows. Foram implementadas no sistema as seguintes funções densidade de probabilidade: Weibull (2P, 3P, 2P com dap mínimo como locação, 3P truncada), hiperbólica (2P, 3P, 2P com dap mínimo como locação, 3P truncada), log-logística (2P, 3P, 2P com dap mínimo como locação), logística generalizada, Fatigue life (2P e 3P) e Frechet (2P e 3P). O sistema desenvolvido auxilia os usuários na definição e escolha da fdp que melhor atenda suas necessidades, contudo melhorias são necessárias. O projeto iniciado mostrou-se eficiente para ajustes de funções de densidade probabilidade.Item Airborne laser scanning applied to eucalyptus stand inventory at individual tree level(Pesquisa Agropecuária Brasileira, 2018-12) Cosenza, Diogo Nepomuceno; Soares, Vicente Paulo; Leite, Helio Garcia; Gleriani, José Marinaldo; Amaral, Cibele Hummel do; Gripp Júnior, Joel; Silva, Antonilmar Araújo Lopes da; Soares, Paula; Tomé, MargaridaThe objective of this work was to evaluate the application of airborne laser scanning (ALS) to a large-scale eucalyptus stand inventory by the method of individual trees, as well as to propose a new method to estimate tree diameter as a function of the height obtained from point clouds. The study was carried out in a forest area of 1,681 ha, consisting of eight eucalyptus stands with ages varying from four to seven years. After scanning, tree heights were obtained using the local maxima algorithm, and total wood stock by summing up individual volumes. To determine tree diameters, regressions fit using data measured in the inventory plots were used. The results were compared with the estimates obtained from field sampling. The equation system proposed is adequate to be applied to the tree height data derived from ALS point clouds. The tree individualization approach by local maxima filters is efficient to estimate number of trees and wood stock from ALS data, as long as the results are previously calibrated with field data.Item Crescimento e qualidade de mudas de Cassia grandis Linnaeus f. em resposta à adubação fosfatada e calagem(Ciência Florestal, 2017-04) Freitas, Eliane Cristina Sampaio de; Paiva, Haroldo Nogueira de; Leite, Helio Garcia; Oliveira Neto, Silvio Nolasco deO objetivo deste estudo foi avaliar o crescimento e a qualidade de mudas de Cassia grandis Linnaeus f. (cássia-rosa) em função da adubação fosfatada e da calagem. Os tratamentos foram representados por um fatorial de seis níveis de fósforo (0, 120, 240, 360, 480 e 600 mg dm-3) por cinco níveis de saturação por bases do substrato (3,5 (original), 25, 40, 55, 70%), sendo dispostos no delineamento em blocos ao acaso, com quatro repetições. Aos 65 dias após a repicagem, foram medidos a altura da parte aérea (H), o diâmetro do coleto (DC), a massa de matéria seca da parte aérea (MSPA), massa de matéria seca de raízes (MSRA) e massa de matéria seca total (MST), e calculada a relação MSPA/MSRA e o índice de qualidade de Dickson (IQD). A adubação fosfatada teve influência significativa em todas variáveis estudadas. A dose de fósforo adequada para a produção de mudas de qualidade de Cassia grandis nas condições estudadas, na saturação por bases de 25%, é de 600 mg dm-3.Item A multi-agent system for forest transport activity planning(Cerne, 2017-07) Araújo Júnior, Carlos Alberto; Leite, Helio Garcia; Soares, Carlos Pedro Boechat; Binoti, Daniel Henrique Breda; Souza, Amaury Paulo de; Santana, Antônio Ferraz; Torre, Carlos Moreira Miquelino EletoThis study aims to propose and implement a conceptual model of an intelligent system in a georeferenced environment to determine the design of forest transport fleets. For this, we used a multi-agent systems based tool, which is the subject of studies of distributed artificial intelligence. The proposed model considers the use of plantation mapping (stands) and forest roads, as well as information about the different vehicle transport capacities. The system was designed to adapt itself to changes that occur during the forest transport operation process, such as the modification of demanded volume or the inclusion of route restrictions used by the vehicles. For its development, we used the Java programming language associated with the LPSolve library for the optimization calculation, the JADE platform to develop agents, and the ArcGis Runtime to determine the optimal transport routes. Five agents were modelled: the transporter, controller, router, loader and unloader agents. The model is able to determine the amount of trucks among the different vehicles available that meet the demand and availability of routes, with a focus on minimizing the total costs of timber transport. The system can also rearrange itself after the transportation routes change during the process.Item Forest restoration monitoring through digital processing of high resolution images(Ecological Engineering, 2019-02) Reis, Bruna Paolinelli; Martins, Sebastião Venâncio; Fernandes Filho, Elpídio Inácio; Sarcinelli, Tathiane Santi; Gleriani, José Marinaldo; Leite, Helio Garcia; Halassy, MelindaMonitoring 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.Item Influência da variabilidade edafoclimática no crescimento de clones de eucalipto no Nordeste baiano(Pesquisa Florestal Brasileira, 2017-07) Santos, Ana Carolina Albuquerque; Silva, Simone; Leite, Helio Garcia; Cruz, Jeovane Pereira daObjetivou-se estudar o crescimento de três clones de eucalipto em diferentes tipos de solos e do histórico de precipitação pluviométrica (PP) na região nordeste da Bahia. Para isso, utilizaram-se dados de parcelas permanentes medidas em povoamentos clonais de eucalipto em Argilosso Amarelo, Argissolo, Vermelho-Amarelo, Latossolo Amarelo e Neossolo Quartzarênico, com e precipitação média anual variando de 700 mm a 1700 mm. Foram ajustados modelos de crescimento em função da idade para altura dominante, diâmetro quadrático, área basal e volume por ha para cada combinação de clone e solo. Para analisar o efeito da PP na predição do volume, foi incluído um modificador associado à precipitação no modelo de Gompertz. O maior crescimento no Argissolo Amarelo foi obtido pelo clone 1. O modelo ajustado, com a inclusão da PP, reduziu os erros em torno de 62,9%. em comparação com o modelo biológico tradicional. Concluiu-se que a consideração da variabilidade dos solos e da PP na modelagem de crescimento em regiões com ampla variabilidade da PP, afetou a exatidão das estimativas. E, ainda, a análise das curvas de crescimento em diferentes solos e PP auxilia na definição do clone adequado para locais onde não há informações de inventário.Item Artificial neural networks: Modeling tree survival and mortality in the Atlantic Forest biome in Brazil(Science of The Total Environment, 2018-12-15) Rocha, Samuel José Silva Soares da; Torres, Carlos Moreira Miquelino Eleto; Jacovine, Laércio Antônio Gonçalves; Leite, Helio Garcia; Schettini, Bruno Leão Said; Villanova, Paulo Henrique; Zanuncio, José Cola; Gelcer, Eduardo Monteiro; Silva, Liniker Fernandes da; Reis, Leonardo PequenoModels to predict tree survival and mortality can help to understand vegetation dynamics and to predict effects of climate change on native forests. The objective of the present study was to use Artificial Neural Networks, based on the competition index and climatic and categorical variables, to predict tree survival and mortality in Semideciduous Seasonal Forests in the Atlantic Forest biome. Numerical and categorical trees variables, in permanent plots, were used. The Agricultural Reference Index for Drought (ARID) and the distance-dependent competition index were the variables used. The overall efficiency of classification by ANNs was higher than 92% and 93% in the training and test, respectively. The accuracy for classification and number of surviving trees was above 99% in the test and in training for all ANNs. The classification accuracy of the number of dead trees was low. The mortality accuracy rate (10.96% for training and 13.76% for the test) was higher with the ANN 4, which considers the climatic variable and the competition index. The individual tree-level model integrates dendrometric and meteorological variables, representing a new step for modeling tree survival in the Atlantic Forest biome.