Distinção de espécies de eucaliptode diferentes idades por meio de imagens TM/Landsat 5

Goergen, Laura Camila de Godoy; Kilca, Ricardo de Vargas; Narvaes, Igor da Silva; Silva, Matheus Nunes; Silva, Emanuel Araújo; Pereira, Rudiney Soares; Adami, Marcos

doi:10.1590/s0100-204x2016000100007

Cited by 6 publications

(10 citation statements)

References 24 publications

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“…The most relevant vegetation indices were used for forest cover analysis, as shown by Ponzoni et al (2012), Berra et al (2014) and Goergen et al (2016). Seven vegetation indices were determined, thus allowing the evaluation of different vegetation aspects, as well as their comparison in terms of performance and sensitivity (Table 1).…”

Section: Methodsmentioning

confidence: 99%

“…Reflectance mean and standard deviation obtained from spectral variables were calculated using the R statistical software (R Core Team, 2016). According to Goergen et al (2016), standard deviation is used to verify the internal change of the spectral variables in each plot.…”

Section: Methodsmentioning

confidence: 99%

“…The identification of tree species and the determination of the age of forest stands is traditionally carried out through field surveys (Goergen et al, 2016), but the use of remote sensing techniques streamlines the process of acquiring and organizing information. The understanding of vegetation attributes led to the need for reliable mapping with the use of spectral data (Dube & Mutanga, 2015).…”

Section: Introductionmentioning

confidence: 99%

“…According to Ponzoni et al (2015), the association of the spectral characteristics of an object with the physicochemical properties of the vegetation is done based on the radiometric variable and often using reflectance values. Goergen et al (2016) (Ponzoni et al, 2015;Goergen et al, 2016), dendrometric and/or biophysical variables (Canavesi et al, 2010;Berra et al, 2014;Tillack et al, 2014;Dube et al, 2015) and structural characteristics are some of the variables on which orbital data have been applied for the spectral characterization of vegetation cover.…”

Section: Introductionmentioning

confidence: 99%

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Spectral characterization of forest plantations with Landsat 8/OLI images for forest planning and management

Alba

Mello

Marchesan

et al. 2017

Pesq. agropec. bras.

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-The objective of this work was to evaluate the use of Landsat 8/OLI images to differentiate the age and estimate the total volume of Pinus elliottii, in order to determine the applicability of these data in the planning and management of forest activity. Fifty-three sampling units were installed, and dendrometric variables of 9-and-10-year-old P. elliottii commercial stands were measured. The digital numbers of the image were converted into surface reflectance and, subsequently, vegetation indices were determined. Red and nearinfrared reflectance values were used to differentiate the ages of the stands. Regression analysis of the spectral variables was used to estimate the total volume. Increase in age caused an addition in reflectance in the near-infrared band and a decrease in the red band. The general equation for estimating the total volume for P. elliottii had an R² adj of 0.67 with a S yx of 31.46 m³ ha -1. Therefore, the spectral data with medium spatial resolution from the Landsat 8/OLI satellite can be used to distinguish the growth stages of the stands and can, thus, be used in the planning and proper management of forest activity on a spatial and temporal scale.Index terms: Pinus elliottii, remote sensing, vegetation indices, volume modeling. Caracterização espectral de plantios florestais com imagens Landsat 8/OLI para planejamento e manejo florestalResumo -O objetivo deste trabalho foi avaliar o uso de imagens Landsat 8/OLI na diferenciação da idade e na estimativa do volume total de Pinus elliottii, para determinar a aplicabilidade desses dados no planejamento e no manejo da atividade florestal. Foram instaladas 53 unidades amostrais e mensuradas as variáveis dendrométricas de povoamentos comerciais de P. elliottii aos 9 e 10 anos. Os números digitais da imagem foram convertidos à reflectância de superfície e, posteriormente, foram elaborados índices de vegetação. A diferenciação da idade dos povoamentos baseou-se nos valores de reflectância da banda do vermelho e do infravermelho próximo. A análise de regressão das variáveis espectrais foi utilizada na estimativa do volume total. O aumento da idade propiciou um acréscimo da reflectância na banda do infravermelho próximo e uma redução na banda do vermelho. A equação geral de estimativa do volume total para P. elliottii apresentou R² aj de 0,67 com S yx de 31,46 m³ ha -1. Dessa forma, os dados espectrais de média resolução espacial provenientes do satélite Landsat 8/OLI podem ser utilizados na distinção das fases de crescimento dos povoamentos sendo, portanto, passíveis de utilização no planejamento e no manejo adequado da atividade florestal em escala espacial e temporal.Termos para indexação: Pinus elliottii, sensoriamento remoto, índices de vegetação, modelagem do volume.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Spectral characterization of forest plantations with Landsat 8/OLI images for forest planning and management

Alba

Mello

Marchesan

et al. 2017

Pesq. agropec. bras.

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“…Importantes estudos sobre a temática, tais como as primeiras aplicações do índice de área foliar -IAF (Jordan, 1969), a distribuição espectral da luz na floresta (Federer e Tanner, 1966), o índice de vegetação por diferença normalizada -NDVI (Rouse et al, 1974), o índice de vegetação ajustado ao solo -SAVI (Huete, 1988), os índices de água por diferença normalizada -NDWI (Gao, 1996;McFeeters, 1996), o índice de área construída por diferença normalizada -NDBI (Zha et al, 2003), a modificação do índice de água por diferença normalizada -MNDWI (Xu, 2006) e o de inundações desérticas -DFI (Wang, 2007) estão em concomitância com escritos envolvendo análises ecossistêmicas, uma vez que, observa-se monitoramentos via sensoriamento em agricultura (Rouse, 1974;Epiphanio et al, 1996;Goergen et al, 2016), dossel de vegetação (Tucker e Maxwell, 1976;Rosa et al, 2015), perímetros irrigados (Epiphanio e Vitorello, 1983;Silva et al, 2012), uso e ocupação do solo (Borges et al, 1993;Menke et al, 2009;Silva et al, 2015), áreas litorâneas (Moraes et al, 2015) e ações antrópicas (Alves e Skole, 1996;Grecchi et al, 2016).…”

Section: Introductionunclassified

Índices de vegetação do Sensoriamento Remoto para processamento de imagens na faixa do visível (RGB)

Silva

Paz²,

Lima-Silva³

et al. 2019

Jour. Hypers. Rem. Sensg.

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It is of extreme relevance to understand the behavior of vegetation for planning and decision-making regarding areas for planting, adequate use of water resources, irrigation and monitoring of vegetation dynamics, for example. In this sense, Remote Sensing (SR) has been a relevant support for the monitoring of ecosystems, since it is observed several researches involving the application of this technique through different mathematical algorithms titled indexes. The new satellites, unmanned vehicles and highresolution cameras that maintains products in the visible (RGB) range bring new perspectives to RS's performance in vegetation, especially in agriculture. Thus, it was developed over the years indices that allowed the detection of vegetation in visible spectral bands and, thus, facilitating agropastoral processes, precision agriculture and the reduction of SR as a whole. Thus, this work aims to review vegetation indices for processing in the RGB range. From the review, the origin of fifteen RGB indices is verified, being designed by diverse needs and equipment, where all reach competitive satisfactory. It is important to note that the developed indexes have improved the RS analyzes, where these improvements have led to new learning that directly contributed to the study of ecosystems, especially vegetation environments. The RS's dynamism makes it an innovation gimmick, in which, through demands and demands, new indices can be created by contributing to the maintenance and provision of social, economic and ecological activities.

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Zoning the occurrence of Thyrinteina arnobia in eucalypts and its relationship with the spectral behaviour of canopies and soil attributes

Medauar,

de Assis Silva,

Carvalho

et al. 2024

Southern Forests: a Journal of Forest Science

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Distinção de espécies de eucaliptode diferentes idades por meio de imagens TM/Landsat 5

Cited by 6 publications

References 24 publications

Spectral characterization of forest plantations with Landsat 8/OLI images for forest planning and management

Spectral characterization of forest plantations with Landsat 8/OLI images for forest planning and management

Índices de vegetação do Sensoriamento Remoto para processamento de imagens na faixa do visível (RGB)

Zoning the occurrence of Thyrinteina arnobia in eucalypts and its relationship with the spectral behaviour of canopies and soil attributes

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