Mapeamento e estimativa de área de cana-de-açúcar no estado do Paraná

• Ano de defesa: 2016
• Autor(a) principal: Cechim Júnior, Clóvis
• Orientador(a): Johann, Jerry Adriani
• Banca de defesa: Mercante, Erivelto , Rocha, Jansle Vieira
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Estadual do Oeste do Parana
• Programa de Pós-Graduação: Programa de Pós-Graduação "Stricto Sensu" em Engenharia Agrícola
• Departamento: Engenharia
• País: BR
• Palavras-chave em Português: Classificação digital de imagens; Indices de vegetação; Análise harmônica de imagens; Séries temporais MODIS; Redes neurais artificiais; Canasat
• Palavras-chave em Inglês: Digital images classification; Vegetation index; Harmonic analysis of images; MODIS time series; Artificial neural networks; Canasat
• Área do conhecimento CNPq: CNPQ::CIENCIAS AGRARIAS::ENGENHARIA AGRICOLA
• Link de acesso: http://tede.unioeste.br:8080/tede/handle/tede/2722

Sugarcane has been cropped and produced in Brazil for a long time, so, it deserves mention because it makes the country as the largest producer, with also representativeness in sugar and ethanol production. The knowledge of reliable estimates concerning their cropped areas is essential for Brazilian agribusiness, as they help in determining prices to producers by power plants as well as allow establishing logistics flow of production. The cropped areas estimates are made by official agencies. Therefore, in order to reduce this subjectivity, geotechnology use comes as an alternative since it has been widely used in mappings agricultural crops. Thus, this study aimed at developing a methodology for mapping sugarcane crop in Paraná State with satellite images as LANDSAT, IRS and spectrum-temporal series of vegetation indexes from MODIS sensor, for 2010/2011 to 2014/2015 harvesting season. The carried out mappings indicated a strong positive correlation concerning Canasat and official IBGE. The developed method was based on Fuzzy ARTMAP classification and was efficient to map and estimate the sugarcane cropped area using vegetation index in Paraná State.