%0 Conference Proceedings
%4 sid.inpe.br/marte2/2017/10.27.14.06.26
%2 sid.inpe.br/marte2/2017/10.27.14.06.27
%@isbn 978-85-17-00088-1
%F 60046
%T Mapeamento espectral para identificação de assinaturas espectrais de minerais de lítio em imagens ASTER (NE/MG)
%D 2017
%A Mendes, Deborah,
%A Perrotta, Monica Mazzini,
%A Costa, Manoel Augusto Correa da,
%A Paes, Vinícius José de Castro,
%@electronicmailaddress deborah.mendes@cprm.gov.br
%E Gherardi, Douglas Francisco Marcolino,
%E Aragão, Luiz Eduardo Oliveira e Cruz de,
%B Simpósio Brasileiro de Sensoriamento Remoto, 18 (SBSR)
%C Santos
%8 28-31 maio 2017
%I Instituto Nacional de Pesquisas Espaciais (INPE)
%J São José dos Campos
%P 5273-5280
%S Anais
%1 Instituto Nacional de Pesquisas Espaciais (INPE)
%X Spectral mapping has been proceeded using ASTER sensor multispectral data for the CPRM Project: Evaluation of Lithium Potential in Brazil. The supervised spectral mapping considered only the metassediments exposed areas, where pegmatite-hosted lithium deposits are known. Training sites were delimited in imagery data by selecting pixels in mining stage areas. The data was processed by a classification wizard including Minimum Noise Fraction (MNF), Pixel Purity Index (PPI), Spectral Angle Mapper (SAM) and Mixture Tuned Matched Filtering (MTMF) methods. The results show that the sensor ASTER spectral and spatial features are able to identify significant spectral features for pegmatite intrusions spectral mapping. The intersection of the images resulting from the application of MTMF and SAM techniques generated results consistent with the spectral signatures of the targets taken from the image. On the other hand, the spectral modeling of the pegmatite intrusions using ASTER data showed the difficulty in the direct application of signatures obtained in the laboratory as reference for the spectral mapping, since, due to the low spatial resolution of the images, a significant mixture of materials is represented in a pixel, in addition to the low spectral resolution of the sensor which has only nine spectral bands, while the laboratory measurements have 2151 bands. Even so, it is possible to recognize spectral features characteristic of mineral phases present in the assemblies studied, such as the different types of clay minerals.
%9 Geologia
%@language pt
%3 60046.pdf