Utilização de imagens sintéticas para monitoramento agrícola

• Autor(a) principal: Silva, Bruno Bonemberger da
• Data de Publicação: 2019
• Tipo de documento: Tese
• Idioma: por
• Título da fonte: Biblioteca Digital de Teses e Dissertações do UNIOESTE
• Texto Completo: http://tede.unioeste.br/handle/tede/4480
• topic: Fusão de imagens; NDVI; ESTARFM; Data fusion; NDVI; ESTARFM; CIENCIAS AGRARIAS::ENGENHARIA AGRICOLA

This doctoral thesis aims to use and evaluate synthetic images in agricultural monitoring. Thus, in Article 1 the objective was to apply the ESTARFM algorithm in multispectral images in an area covering the municipality of Cascavel, Paraná. The MODIS and Landsat 8 images were fused to produce 20 synthetic Landsat 8 images from October 2014 to September 2015, and the accuracy of the results was determined by comparing the reflectance valuesbetween the values of the synthetic and real images of the Landsat 8. The observed results showed that the red band presented better results when compared to infrared, and that the NDVI generated with these images reproduced well the dynamics of the soy and corn crops. Secondly, for Article 2 the objective of the study was to apply the SEBAL model and the ESTARFM methodology to estimate daily ET in an agricultural property of the Municipality of Cascavel, Paraná. MODIS and Landsat 8 OLI/TIRS images were fused to produce synthetic images between October 2014 and October 2015. The results obtained indicated good symmetry between the estimated ETs with Landsat 8 images and the synthetic ones, being the best results found for the culture of soybeans and the worst in times when the agricultural area was covered with corn stubble. In general, ESTARFM tended to overestimate the results.