%0 Conference Proceedings
%4 sid.inpe.br/marte2/2017/10.27.13.03
%2 sid.inpe.br/marte2/2017/10.27.13.03.08
%@isbn 978-85-17-00088-1
%F 59452
%T Modelo Linear de Mistura Espectral em imagens CBERS-4 e Resourcesat-2 para estimativa da vegetação às margens do Lago de Itaipu (PY-BR)
%D 2017
%A Wagner, Michelle Cristine,
%A Magalhães, Vanderlei Leopold,
%@electronicmailaddress mih.cwagner@gmail.com
%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 3152-3159
%S Anais
%1 Instituto Nacional de Pesquisas Espaciais (INPE)
%X Among the Remote Sensing techniques, used to facilitate the extraction of information contained in a particular satellite image, the Linear Spectral Mixture Analysis (LSMA) stands out for estimating the proportions of the components soil, shade and vegetation from spectral responses of each band in order to emphasize targets of interest. Usually the LSMA is combined with segmentation and classification techniques, as in the Digital PRODES (Amazon Gross Deforestation Estimate Project), developed by INPE. The aim of this work was to generate the LSMA for images relating the banks of the Itaipu Lake, in western Paraná, in 2015 using images of the CBERS-4 and ResourceSat-2 satellites. In addition, it was created maps of land use, applying the segmentation and classification techniques. The component that showed the best result of the LSMA was the image-fraction shadow, which was used in the remaining stages of the work. The map of land use and cover indicated that the analyzed area consists mainly of vegetation, followed by agricultural areas. Even though the images refers to different dates, the CBERS-4 to November when planting is still recent and cultures are not very developed, and the ResourceSat-2 to July, when there is no planting or harvest, after applying the LSMA and the thematic mapping, it is clear that the results were similar, due to the proximity of spatial and radiometric resolutions of the satellites.Thus, the LSMA has proved to be an effective tool for quantifying the vegetation cover and the advance of the agricultural frontier.
%9 CBERS
%@language pt
%3 59452.pdf