Geoestatística e imagens orbitais para caracterizar a distribuição espacial e danos de larvas de melolontídeos em cereais de inverno

• Ano de defesa: 2010
• Autor(a) principal: Dal Prá, Elder
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Santa Maria; BR; Engenharia Agrícola; UFSM; Programa de Pós-Graduação em Engenharia Agrícola
• Palavras-chave em Português: Agricultura de precisão; Sensoriamento remoto; Semivariograma; Krigagem; Classificação; Melolonthidae; Precision farm; Remote sensing; Kriging; Semivariogram; Classification; K-means; CNPQ::CIENCIAS AGRARIAS::ENGENHARIA AGRICOLA
• Link de acesso: http://repositorio.ufsm.br/handle/1/7525

This study aimed to analyze the spatial distribution and use of orbital images for the identification of white grub damage. Will be presented in two chapters, the chapter one, presents the geostatistical characterization of white grub spatial distribution and chapter two describes the use of orbital images for the identification of white grub damage. Surveys were made during 2009 in São Francisco de Assis, Cruz Alta, Ijuí, Lagoa Vermelha, Vacaria and Tapejara, RS. The perimeters of the areas were marked with GPS navigation, with interface for computer-to-hand, used the CR-Campeiro software to create grids of sampling. The population density was estimated from soil trenches, the analysis of spatial variability was made with semivariograms, maps were generated with the ArcGIS 9.3 software, and spatial dependence estimated by classification of Cambardella et al. (1994). The satellite image is from the ALOS satellite, a scene was selected from the PRISM sensor with spatial resolution of 2.5 m, which has a dimension of 35 x 70 km. The classification of the orbital image and white grub spatial distribution map was performed in ENVI software, for this we used the unsupervised classification, the K-means algorithm to evaluate the classification accuracy; this was related to the true field (larvae m-²). The models are adjusted for different species and areas, and the species of white grubs present spatial dependence in all areas, the semivariograms indicate that the species of white grubs have different behavior spatial variability, the sampling grids and sampling can be used to characterize the spatial distribution of white grubs, the map of the spatial distribution of white grubs pests showed the aggregate behavior of these species, white grubs influence the spectral response of culture, Kappa coefficient is considered good, the ALOS image to identify white grubs damage.