Caracterização espectral dos dosséis e estimativa de variável biofísica em plantios de Eucalyptus grandis e Pinus elliottii a partir de imagens Landsat 8/OLI

• Autor(a) principal: Alba, Elisiane
• Data de Publicação: 2016
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Manancial - Repositório Digital da UFSM
• dARK ID: ark:/26339/001300000d8n6
• Texto Completo: http://repositorio.ufsm.br/handle/1/8781
• topic: Reflectância; Análise de regressão; Volume estimado; Índices de vegetação; Reflectance; Regression analysis; Estimated volume; Vegetation indexes; CNPQ::CIENCIAS AGRARIAS::RECURSOS FLORESTAIS E ENGENHARIA FLORESTAL

The area occupied by planted forests has increased significantly in the country, especially with Eucalyptus and Pinus genus. However, the means of determining of dendrometric variables the field are costly, require time and covers small areas. Thus, the orbital products applied in estimating the biophysical variables constitute an important source of data, which facilitate the process of acquiring information of the canopies, being useful, especially, in the planning in order to optimize productivity. This manner, this study aims evaluate the potential of the Landsat 8 satellite images in the differentiation of stage of growth and determining the biophysical variable of Eucalyptus grandis e Pinus elliottii. We used the 221-083 scene of Landsat 8/OLI satellite of the day 30th August 2013, being this converted to surface bidirectional reflectance from the radiometric calibration and, subsequently generated the ARVI vegetation indices, NDVI, NDVI, MVI, NDVI, SAVIL=0.25 SAVIL=0.50 and SR. The spectral behavior of the stands with different ages was established based on the reflectance of the red and near infrared bands. The reflectance of the bands and vegetation indexes was related to the forest volume, analyzing their correlation and adjustment of the data to the regression models, leading to selection of variables through Stepwise method. The Landsat 8 images are sensitive the variations of the characteristics of individuals according to the different growth stages of the forest stands, wherein for E. grandis to 4, 18 and 23 years, the increasing age caused reduction in reflectance in the NIR band and increased in the band Red. However, in stands of P. elliottii it was observed that increasing age led to an increased reflectance in the NIR band and reduction in red band. Correlation analysis between the spectral data and the forest volume of E. grandis showed that SAVIL=0.50 index showed better correlation with forest variable at both ages. The stands of P. elliottii the B5 band showed higher correlation with the volume to 9 years old, however at 10 years of age, the DVI index showed the highest correlation with the forest variable. Regression analysis for E. grandis has exposed the models of best fit, so that at 4 and 18, the equation containing the SAVI index explained 76% and 68% of the variability of the data. At 23 years, the composite model of the SAVI index and B7 band obtained R²aj of 0.67. For P. elliottii the best model to 9 years of age explained 74% of data variability, being this composed of the DVI index and B7 band. Thus, the Landsat 8 / OLI data can be used in forest planning, assisting in forest inventory, as well as knowledge of the individual phases of growth and the identification of forest species.