Produtividade de biomassa de cana-de-açúcar em função dos índices de vegetação utilizando técnicas de sensoriamento remoto

• Ano de defesa: 2015
• Autor(a) principal: Oliveira, Gildriano Soares de [UNESP]
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Estadual Paulista (Unesp)
• Palavras-chave em Português: Sensoriamento remoto; Biomassa; Cana-de-açúcar; Produtividade; Modelos matematicos; Biomass
• Link de acesso: http://hdl.handle.net/11449/136733; http://www.athena.biblioteca.unesp.br/exlibris/bd/cathedra/22-03-2016/000859640.pdf

The relevance of sugarcane in the energy sector and the production of sugar and ethanol are essential for Brazilian agribusiness and have shown good performance at each crop year. This study aims to determine mathematical models to estimate the biomass productivity of sugarcane in function of NDVI, through images of OLI sensor by Landsat 8. The study was conducted on a territorial extension of Barrinha County, in a sugarcane experimental area, located in the northeast of São Paulo, administrative region of Ribeirão Preto. The evaluation of the estimated biomass productivity of sugarcane by remote sensors was carried out by mathematical modeling productivity, using NDVI images. For all images of each date, there has been calculated the average value of the NDVI pixels within the area of each block, and a linear regression analysis of variance for the varieties in the different ages of plants and at two growing seasons (2012/2013 and 2013/2014) was performed. The models were selected by the significance of the coefficient of determination and correlation. The mathematical model that estimated the biomass productivity of sugarcane in function of NDVI images and the best statistical significance was within 8 months old after harvest (Y = 3823,3e-5,646NDVI; R² = 0.466; p = 0.002) for the harvest of 2012/2013 and the best statistical quality to 2013/2014, with NDVI images, were at 8 months (Y = 31,986e1,2071NDVI; R² = 0.213; p = 0.054), 9 months (Y = + 31.399 66,723NDVI; R² = 0.201; p = 0.062) and at 7 months of age after cutting (Y = 101,5NDVI0,9536; R² = 0.170; p = 0.089)