CARACTERIZAÇÃO ESPECTRO-TEMPORAL DE DOSSÉIS DE Eucalyptus spp. MEDIANTE DADOS RADIOMÉTRICOS TM/Landsat5

Ponzoni, Flávio Jorge; Pacheco, Ludmila Roque Ferraz; Santos, Sandra Benfica dos; Filho, Clódis de Oliveira Andrades

doi:10.1590/01047760201521021457

Cited by 13 publications

(14 citation statements)

References 8 publications

(6 reference statements)

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“…A partir de imagens orbitais, utiliza-se dos valores de reflectância espectral para a caracterização de povoamentos florestais como a diferenciação da idade dos povoamentos (AARDT;NORRIS 2008;PONZONI et al, 2015;GOERGEN et al 2016) e estimativas de variáveis descritivas da vegetação tais como volume total (BERRA et al, 2013;COSTA et al, 2015), biomassa (FERRAZ et al, 2014), índice de área foliar (DUBE; MUTANGA, 2015), entre outros. Goergen (2014) ao utilizar dados TM/Landsat 5 para estimativa do volume de povoamentos de eucalipto, obteve modelos que responderam até 54% da variabilidade dos dados de campo.…”

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“…Inúmeras pesquisas relacionaram com êxito essas imagens multiespectrais com as características dos dosséis utilizando os sensores TM/Landsat 5, ETM+/Landsat 7 (BERRA, 2013;FERRAZ et al, 2014;COSTA et al, 2015;DUBE;MUTANGA, 2015;PONZONI et al, 2015;GOERGEN et al, 2016). Da série Landsat, atualmente apenas o satélite Landsat 8 dispõe dados atuais da superfície terrestre, dando sequência ao programa de observação da terra.…”

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USO DE IMAGENS DE MÉDIA RESOLUÇÃO ESPACIAL PARA O MONITORAMENTO DE DOSSÉIS DE Eucalyptus grandis

Alba¹,

Marchesan²,

Tramontina³

et al. 2017

RSA

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Resumo -O objetivo desse estudo foi identificar plantios comerciais de Eucalyptus grandis com diferentesidades e estimar o volume total de madeira utilizando dados radiométricos do sensor OLI/Landsat 8. Demarcaram-se parcelas em povoamentos aos 4, 18 e 23 anos de idade, nas quais foi mensurado o volume total (m³/ha). A imagem OLI/Landsat 8 foi convertida para reflectância de superfície utilizando a correção radiométrica e, posteriormente gerados os índices de vegetação ARVI, DVI, GNDVI, MVI, NDVI, SAVIL=0,25, SAVIL=0,50 e SR. A diferenciação da idade dos dosséis foi estabelecida baseando-se na reflectância das bandas B4 e B5. Os dados espectrais e o volume total de madeira foram submetidos à análise de correlação e regressão múltipla baseada no método Stepwise. Os povoamentos foram diferenciados uma vez que o aumento da idade ocasionou a redução da reflectância na banda B5 e aumento na banda B4. Para a estimativa do volume total, apenas os povoamentos aos 4 anos de idade apresentaram bom ajuste, sendo o modelo composto pelo índice SAVI, explicando 74% da variabilidade do volume de madeira. Os dados espectrais extraídos de imagens OLI/Landsat 8 mostraram-se sensível às variações das características dos indivíduos nas diferentes fases de crescimento dos povoamentos, assim como na estimativa das variações do volume total.Palavras-chave -Sensoriamento remoto, índices de vegetação, volume estimado. Abstract -The objective of this study was to identify commercial Eucalyptus grandis plantations with differentages and estimate the total wood volume using OLI/Landsat 8 radiometric data. Plots were demarcated in stands at 4, 18 and 23 years of age, in which it was measured total volume (m³/ha). The OLI/Landsat 8 image was converted to surface reflectance using the radiometric calibration and, subsequently generated the vegetation indices ARVI, NDVI, NDVI, MVI, NDVI, SAVIL=0.25 SAVIL=0.50 and SR. The differentiation of the age of the canopies was established based on the reflectance of the B4 and B5 bands. The spectral and total volume of wood were subjected to correlation analysis and adjustment of the data to the regression models, leading to selection of variables through the Stepwise -Forward method. The stands were differentiated since the increase of the age caused the reduction in reflectance on B5 band and increase in band B4. For the estimation of total volume, only the stands at 4 years of age presented good adjustment, being the model composed by the SAVI index, explaining 74% of the volume variability of wood. The spectral data extracted from OLI/Landsat 8 images showed to be sensitive to variations in the characteristics of individuals in different growth stages of the stands, as well as in the estimation of changes in the total volume.

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USO DE IMAGENS DE MÉDIA RESOLUÇÃO ESPACIAL PARA O MONITORAMENTO DE DOSSÉIS DE Eucalyptus grandis

Alba¹,

Marchesan²,

Tramontina³

et al. 2017

RSA

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“…For instance, plantations comprised of different Eucalyptus species may have very similar values of basal area and volume, but have different spectral characteristics due to differences in spectral behaviour of the species that form the canopies. Also, according to Ponzoni et al (2015), the canopy reflectance of older Eucalyptus plantations (between 4 and 6 years) tend to contain a greater contribution from green leaves and a lower contribution from shadows, the background, and from dry branches inside the canopies than the canopy reflectance of young Eucalyptus plantations (< 4 years). Thus, the canopy reflectance of older Eucalyptus plantations generated highest correlations with bands of the infrared region of the electromagnetic spectrum and, therefore, with vegetation indices that include these bands in their compositions (Ponzoni et al 2015).…”

Section: Discussionmentioning

confidence: 99%

“…Also, according to Ponzoni et al (2015), the canopy reflectance of older Eucalyptus plantations (between 4 and 6 years) tend to contain a greater contribution from green leaves and a lower contribution from shadows, the background, and from dry branches inside the canopies than the canopy reflectance of young Eucalyptus plantations (< 4 years). Thus, the canopy reflectance of older Eucalyptus plantations generated highest correlations with bands of the infrared region of the electromagnetic spectrum and, therefore, with vegetation indices that include these bands in their compositions (Ponzoni et al 2015). These results are consistent with the best correlations found in this study among the infrared bands, vegetation indices derived from these bands, basal area, and volume.…”

Section: Discussionmentioning

confidence: 99%

“…The analysis of remote sensing information combined with field data has been used by several authors to fill the information gap left by data collected only in the field (Watt et al 2016, Boisvenue et al 2016, Moreno et al 2016, Fayad et al 2016, Vicharnakorn et al 2014. Ponzoni et al (2015) used data collected from Landsat 5 thematic mapper (TM) images for spectral-temporal characterisation of Eucalyptus canopies. Berra et al (2012) estimated the volume of a Eucalyptus plantation in the southern region of Brazil from Landsat 5 TM images.…”

Section: Introductionmentioning

confidence: 99%

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Spatial prediction of basal area and volume in Eucalyptus stands using Landsat TM data: an assessment of prediction methods

Reis

Carvalho

Mello

et al. 2018

N.Z. j. of For. Sci.

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Background: In fast-growing forests such as Eucalyptus plantations, the correct determination of stand productivity is essential to aid decision making processes and ensure the efficiency of the wood supply chain. In the past decade, advances in remote sensing and computational methods have yielded new tools, techniques, and technologies that have led to improvements in forest management and forest productivity assessments. Our aim was to estimate and map the basal area and volume of Eucalyptus stands through the integration of forest inventory, remote sensing, parametric, and nonparametric methods of spatial prediction. Methods: This study was conducted in 20 5-year-old clonal stands (362 ha) of Eucalyptus urophylla S.T.Blake x Eucalyptus camaldulensis Dehnh. The stands are located in the northwest region of Minas Gerais state, Brazil. Basal area and volume data were obtained from forest inventory operations carried out in the field. Spectral data were collected from a Landsat 5 TM satellite image, composed of spectral bands and vegetation indices. Multiple linear regression (MLR), random forest (RF), support vector machine (SVM), and artificial neural network (ANN) methods were used for basal area and volume estimation. Using ordinary kriging, we spatialised the residuals generated by the spatial prediction methods for the correction of trends in the estimates and more detailing of the spatial behaviour of basal area and volume. Results: The ND54 index was the spectral variable that had the best correlation values with basal area (r = − 0.91) and volume (r = − 0.52) and was also the variable that most contributed to basal area and volume estimates by the MLR and RF methods. The RF algorithm presented smaller basal area and volume errors when compared to other machine learning algorithms and MLR. The addition of residual kriging in spatial prediction methods did not necessarily result in relative improvements in the estimations of these methods. Conclusions: Random forest was the best method of spatial prediction and mapping of basal area and volume in the study area. The combination of spatial prediction methods with residual kriging did not result in relative improvement of spatial prediction accuracy of basal area and volume in all methods assessed in this study, and there is not always a spatial dependency structure in the residuals of a spatial prediction method. The approaches used in this study provide a framework for integrating field and multispectral data, highlighting methods that greatly improve spatial prediction of basal area and volume estimation in Eucalyptus stands. This has potential to support fast growth plantation monitoring, offering options for a robust analysis of high-dimensional data.

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Conservation of Schomburgkia crispa Lindl. (Orchidaceae) by reintroduction into a fragment of the Brazilian Cerrado

Soares

Santiago

Sorgato

2020

Journal for Nature Conservation

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CARACTERIZAÇÃO ESPECTRO-TEMPORAL DE DOSSÉIS DE Eucalyptus spp. MEDIANTE DADOS RADIOMÉTRICOS TM/Landsat5

Cited by 13 publications

References 8 publications

USO DE IMAGENS DE MÉDIA RESOLUÇÃO ESPACIAL PARA O MONITORAMENTO DE DOSSÉIS DE Eucalyptus grandis

USO DE IMAGENS DE MÉDIA RESOLUÇÃO ESPACIAL PARA O MONITORAMENTO DE DOSSÉIS DE Eucalyptus grandis

Spatial prediction of basal area and volume in Eucalyptus stands using Landsat TM data: an assessment of prediction methods

Conservation of Schomburgkia crispa Lindl. (Orchidaceae) by reintroduction into a fragment of the Brazilian Cerrado

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