@InProceedings{SouzaLoSoPaMoSaLo:2017:AvEsUm,
               author = "Souza, Jos{\'e} Carlos and Lopes, Elfany Reis do Nascimento and 
                         Sousa, Jocy Ana Paix{\~a}o de and Padovanni, Naia Godoy and 
                         Morais, Maria Cintia Matias and Sales, Jomil Costa and 
                         Louren{\c{c}}o, Roberto Wagner",
                title = "Avalia{\c{c}}{\~a}o espectral da umidade da 
                         vegeta{\c{c}}{\~a}o por meio do Normalized Difference Water 
                         Index - NDWI",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "204--210",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 18. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "Among the numerous applications of remote sensing we have the 
                         estimate of vegetation index and the evaluation of the spectral 
                         behavior of vegetation cover, in relationship atmospheric 
                         conditions of time. The goal this study is to estimate 
                         quantitatively the moisture content of vegetation through in the 
                         NDWI (Normalized Difference Water Index) and evaluate the temporal 
                         changes of this index, pixel by pixel, considering periods of rain 
                         and drought. The study was applied in the watershed of the river 
                         Una, in the municipality of Ibi{\'u}na, S{\~a}o Paulo. The NDWI 
                         was generated in the software ArcGis 10, using images of the 
                         sensor OLI/Landsat 8 of the months of January and August 2015. The 
                         index image generated was processed in the software Matlab 7.12 
                         here was built a matrix, correlating the variations of the index, 
                         pixel by pixel, in both periods analyzed. The results showed 
                         direct influence of seasonality on the variation of index of 
                         moisture of the vegetation, showing loss in the water content of 
                         the vegetation in 73.03% of the pixels evaluated. The class of the 
                         NDWI that showed more marked change was the range 0.4 - 0.5 which 
                         ranged from 30.4%. Another evident factor is the influence of 
                         irrigated agriculture in the behavior of vegetation n January to 
                         6.76% in August, where 5.92% of the pixels had higher NDWI values 
                         in the dry month.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "60069",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PS43J9",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PS43J9",
           targetfile = "60069.pdf",
                 type = "Landsat OLI",
        urlaccessdate = "27 abr. 2024"
}