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      Modelos para estimativa de volume de árvores individuais pela morfometria da copa obtida com lidar Translated title: Models to estimate volume of individual trees by morphometry of crowns obtained with lidar

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          Abstract

          A estimativa volumétrica, a partir do escaneamento digital de florestas por meio do uso do LIDAR, potencializa o emprego de técnicas de manejo de precisão no planejamento da exploração nas florestas tropicais. A utilização dessa tecnologia de sensoriamento remoto permite a incorporação de variáveis da morfometria de copa, ainda pouco empregadas e menos conhecidas em decorrência da dificuldade de coleta em campo. O objeto deste estudo foi construir equações capazes de estimar o volume do fuste de árvores individuais dominantes e codominantes, a partir da morfometria da copa obtida por meio do LIDAR aerotransportado, considerando duas situações de inventário florestal: a) com a coleta do DAP, conjuntamente com as variáveis morfométrica da copa obtidas pelo LIDAR e b) apenas com os dados de morfometria de copa. Para seleção dos modelos foram considerados: a matriz de correlação das variáveis preditoras e a combinação das variáveis que geraram os melhores resultados estatísticos pelos critérios Syx , Syx(%) e Press p, e que foram homocedásticos e com disposição dos resíduos normais e independentes. Para as melhores equações foram realizadas análise de influência. Os resultados estatísticos do ajuste dos modelos para as duas situações permitiram selecionar equações com e sem DAP, com resultados R²aj. (%) de a) 92,92 e b) 79,44; Syx(%) de a) 16,73 e b) 27,47; e, critério de Press p de a) 201,15 m6 e b) 537,47 m6, respectivamente. Por meio das variáveis morfométricas, foi possível desenvolver equações capazes de estimar com precisão o volume do fuste de árvores dominantes e codominantes em florestas tropicais.

          Translated abstract

          The volumetric estimate from digital scanning of the forests through the use of LIDAR increases the precision of forest management techniques in planning tropical forest logging operations. The use of this remote detection technology allows the incorporation of crown morphometric variables which are still little known and little used due to the difficulty of collecting field data for volume equations. The objective of this study was to build equations capable of estimating the stem volume of dominant and codominant individual trees from the crown's morphometry obtained by airborne LIDAR, considering two forest inventory situations: a) with the collection of diameter at breast height (DBH), and crown morphometric variables obtained from LIDAR data and b) using only the crown morphometry variables. For the selection of models the factors considered were: the correlation matrix of predictor variables and the combination of variables that generates the best results by statistical criteria Syx, Syx(%) and Press p, and that were homoscedastic and had a normal and independent distribution of errors. The influence analysis was performed for the best equations. The results for the statistical fit of the equations to the two situations allowed the selection of models with and without DBH, with R²aj.( %) values of a) 92.92 and b) 79.44, Syx(%) values of a) 16.73 and b) 27.47, and, Press p criterion values of a) 201.15 m6 and b) 537.47 m6, respectively. Through morphometric variables it was possible to develop equations capable of accurately estimating the stem volume of dominant and codominant trees in tropical forests

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                Author and article information

                Contributors
                Role: ND
                Role: ND
                Role: ND
                Role: ND
                Journal
                cerne
                CERNE
                CERNE
                UFLA - Universidade Federal de Lavras (Lavras )
                2317-6342
                December 2014
                : 20
                : 4
                : 621-628
                Affiliations
                [1 ] Embrapa Acre Brazil
                [2 ] Instituto Nacional de Pesquisas da Amazônia Brazil
                Article
                S0104-77602014000400016
                10.1590/01047760201420041693
                7bca7cf8-cbbf-4ff4-ba50-850c7f016047

                http://creativecommons.org/licenses/by/4.0/

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                Product

                SciELO Brazil

                Self URI (journal page): http://www.scielo.br/scielo.php?script=sci_serial&pid=0104-7760&lng=en
                Categories
                FORESTRY

                Forestry
                Laser profiling,Regression analysis,Precision forestry,Amazon,Perfilamento a laser,Análise de regressão,Manejo florestal de precisão,Amazônia

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