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@InProceedings{MoreiraTeixGalv:2015:UtÍnVe,
               author = "Moreira, Luis Clenio J{\'a}rio and Teixeira, Adunias dos Santos 
                         and Galv{\~a}o, L{\^e}nio Soares",
          affiliation = "{} and {} and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Utiliza{\c{c}}{\~a}o de {\'{\i}}ndices de 
                         vegeta{\c{c}}{\~a}o obtidos de dados multiespectrais e 
                         hiperespectrais para detectar estresse salino na cultura do 
                         arroz",
            booktitle = "Anais...",
                 year = "2015",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "2387--2394",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 17. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "The purpose of this study was to evaluate multispectral and 
                         hyperspectral vegetation indices aimed at characterizing soil 
                         salinization from spectral information of rice canopies. The work 
                         was performed using plots of rice in the same phenological stage 
                         in the second semester of 2013. With a GPS rover, sampling points 
                         were marked in the field and then the electrical conductivity (EC) 
                         of the soil was measured. Four multispectral vegetation indices 
                         (OLI sensor/Landsat-8) and 10 hyperspectral indices 
                         (Hyperion/EO-1) were computed. Linear regression was used to 
                         describe the relationship between the indices and EC. Spectral 
                         information from the Red (R) vs near infrared (NIR) was plotted 
                         against EC soil above and below 3.00 dS/m. Spectra of the 
                         extracted images indicated an increasing reflectance in red and 
                         reducing in NIR and mid infrared (SWIR) with increasing soil EC. 
                         In the NIR region, the separation of pixels under stress (EC> 3.00 
                         dS/m) from pixels under normal conditions (EC <3.00dS/m) presented 
                         good performance. In the evaluation of multispectral indices, the 
                         Normalized Difference Vegetation Index (NDVI) and Enhanced 
                         Vegetation Index (EVI) showed the best results with R2 of 0.68 and 
                         0.70, respectively. The most promising hyperspectral index is the 
                         Salinity and Water Stress Index (SWSI1) with R2 = 0.70. Therefore, 
                         from both (OLI and Hyperion) sensors, changes in the canopy 
                         reflectance of rice under stress.",
  conference-location = "Jo{\~a}o Pessoa",
      conference-year = "25-29 abr. 2015",
                 isbn = "978-85-17-0076-8",
                label = "481",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3JM49UB",
                  url = "http://urlib.net/rep/8JMKD3MGP6W34M/3JM49UB",
           targetfile = "p0481.pdf",
                 type = "Sensoriamento remoto hiperespectral",
        urlaccessdate = "28 nov. 2020"
}


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