Coeficiente de cultivo para a videira com base no índice de vegetação por diferença normalizada obtido com uso de VANT

Detalhes bibliográficos
Ano de defesa: 2019
Autor(a) principal: GOMES, Maryjane Diniz de Araújo
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Tese
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Estadual Paulista Júlio de Mesquita Filho
Brasil
Faculdade de Ciências Agronômicas
Programa de Pós-Graduação em Agronomia, Irrigação e Drenagem
UNESP
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: https://repositorio.ifpa.edu.br/jspui/handle/prefix/308
Resumo: The diverse interactions of the biophysical environment of an acreage make it difficult to study vegetation behavior through field measurements. These difficulties made remote sensing, through satellite images, a robust tool for investigating these ecosystems in different regions. Satellite images have been a widely used tool for calculating the water demands of irrigated crops with great efficiency. However, there is a limitation of periodicity since the satellites used, such as Landsat 8, take 16 days to return to the same region. As an alternative to high resolution and daily aerial imagery today unmanned aerial vehicles (VANT), such as Drones, are being used. The objective of this work was to determine the water demand of vine Pinot Noir by vegetation index using daily images obtained with the use of VANT. The results obtained were compared with data measured of field. The water demand was calculated by estimating the crop coefficients using the NDVI (Normalized Difference Vegetation Index) and the reference evapotranspiration. The result of this work showed that the resolution influences the values of the vegetative indexes and, consequently, the parameters that can be estimated by them. Therefore, the VANT catches Express values closer to the real on a daily time scale, obtaining more satisfactory results for use in irrigation management.