%0 Conference Proceedings
%4 sid.inpe.br/marte2/2017/10.23.19.24.14
%2 sid.inpe.br/marte2/2017/10.23.19.24.15
%@isbn 978-85-17-00088-1
%F 60195
%T Índice de vegetação da bacia hidrográfica do rio Taturi Oeste PR
%D 2017
%A Cunha, Thais Carvalho,
%A Magalhães, Vanderlei Leopold,
%@electronicmailaddress tccunha3@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 811-817
%S Anais
%1 Instituto Nacional de Pesquisas Espaciais (INPE)
%X The principle of Normalized Difference Vegetation Index (NDVI) is based on the contrast between the spectral regions, the larger the higher contrast the vigor of the vegetation in the imaged areas. The river basin Taturi, part of the Paraná Basin III, is an area that has anthropogenic interference, being necessary to carry out monitoring of the remaining vegetation. In view of this, the aim of this study is to obtain Vegetation Index through images of Landsat - 8 for later use mapping and soil cover of the basin. The NDVI is determined by calculating the ratio between the difference of reflectance of these bands and the sum of them, namely: NDVI = G * [(NIR-R) / (NIR + R)] + offset. The NDVI was generated in the SPRING software on the image of February 2015 to gain 2000 values and 100 offset. The segmentation and classification, thresholds of similarity and 8 pixel area 16 presenting qualitative and quantitative details of vegetation were applied. The classification allowed the generation of 29 issues that were associated with the five classes, highlighting hydrography, vegetation, agricultural area, exposed soil and the urban area. The total area of this vegetation was 56.4822 square kilometers, ie 19.91% of the Taturi River basin. It appears that the mapped vegetation, with this methodology is representative along the riparian forests and sometimes comes in small isolated islands. Note also that the digital processing techniques of images in the SPRING software, using high radiometric and atmospheric correction of the USGS images, were efficient in identifying and quantifying the vegetation, allowing future comparisons or preterit for this basin.
%9 Recursos hídricos
%@language pt
%3 60195.pdf