%0 Conference Proceedings
%4 sid.inpe.br/marte2/2017/10.27.14.00.58
%2 sid.inpe.br/marte2/2017/10.27.14.00.59
%@isbn 978-85-17-00088-1
%F 59993
%T Detecção semiautomática de nuvens e sombras nas imagens WFI/CBERS-4 utilizando a ferramenta cloud detection do sistema TerraAmazon
%D 2017
%A Moraes, Douglas Rafael Vidal de,
%A Dias, Emily Regina Siqueira,
%A Feitosa, Jeremias Vitório Pinto,
%A Quadros, Camila Barata,
%A Dias, Mírian Corrêa,
%A Souza, Jefferson Jesus de,
%A Santos, Laís Freitas Moreira dos,
%A Miranda, Magda Valéria Corrêa,
%A Luz, Nelton Cavalcante,
%A Ronise,
%@affiliation
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@electronicmailaddress douglas.moraes@funcate.org.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 5009-5016
%S Anais
%1 Instituto Nacional de Pesquisas Espaciais (INPE)
%X The Amazon region, by its geographical location, with influences of the Intertropical Convergence Zone, offers to optical sensors, the obtainment of images with high cloud coverage in the greater part of the year, which makes difficult and/or prevents the orbital images interpretation and can become an obstacle for the remote sensing and geoprocessing in the forests monitoring. Keeping this in view, it was implemented a cloud automatic detection tool, the Cloud Detection, which is available in the application TerraAmazon, developed by INPE and FUNCATE to give support to the projects, developed by the National Institute for Space Research (INPE) for the monitoring of forests. The present work applied different values to the parameters referring to the plugin Cloud Detection in the semiautomatic detection of clouds and shadows for WFI/CBERS-4 images, to verify which parameters collaborate for the efficiency of the detection and vectorization of the two targets in question. The results showed that the values of the morphological filters opening was the one who collaborates more for the differences in the vectorization; and there will always have confusion related to some water bodies that, because of theirs similar reflectance, they are detected as shadows, which can be edited manually and deleted of the mapping.
%9 CBERS
%@language pt
%3 59993.pdf