Tratamento de imagens orbitais e suborbitais para caracterização ambiental da cabeceira do Rio São Lourenço-MT

• Ano de defesa: 2012
• Autor(a) principal: Cândido, Anny Keli Aparecida Alves
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Mato Grosso; Brasil; Instituto de Ciências Agrárias e Tecnológicas (ICAT) – Rondonópolis; UFMT CUR - Rondonopólis; Programa de Pós-Graduação em Engenharia Agrícola
• Palavras-chave em Português: Campo Verde-MT; Planejamento ambiental; Sensoriamento remoto; CNPQ::CIENCIAS AGRARIAS::ENGENHARIA AGRICOLA; Environmental planning; Remote sensing
• Link de acesso: http://ri.ufmt.br/handle/1/1120

The thesis has been divided into two chapters. In the first chapter aimed to identify potential environmental changes that occurred over a period of 26 years. For this we used satellite imagery scenes of Landsat TM 5 of 1985, 1997 and 2011, for procedures supervised classification by region, with the maximum likelihood algorithm. From these images, we obtained maps of NDVI from the subtraction of wavelengths near infrared and red, divided by the sum of the ratio of wavelengths of near infrared and red spectrum. In mapping land use, it was found that over 80% of the watershed area is allocated to agriculture. The reduced class savannah and forest class increased over the years analyzed. The NDVI showed areas that were appropriately with little plant biomass, differing areas with dense vegetation cover. Regarding the detection of degraded areas in the watershed, there was a demo unit of ecological restoration (UDRE), established in 2010, in terms of spectral response, obtained via NDVI, is similar to the class agriculture. It is believed that this area of permanent preservation degraded in the recovery phase, tends to become similar areas with dense vegetation, over the next few years. The second is a chapter emphasized the treatment of aerial photographs of high spatial resolution, obtained by unmanned aerial vehicle (UAV), aiming at environmental characterization of the watershed is located where the headwaters of the St. Lawrence River. We tested several routines supervised classification and unsupervised pixel by pixel and by region, using two Geographic Information Systems. The supervised classification by region segmentation 20 and 200 of area similarity, showed statistical similarity with the conventional procedure performed by photointerpretation. The techniques presented in this research will be useful for jobs that involve monitoring of degraded areas, bringing effective contribution to setting the methodological route plan reclamation prevailing in the state of Mato Grosso.