@InProceedings{OroAraJúnVelSil:2017:FeAvPo,
               author = "Oro, Oscar Ivan De and Ara{\'u}jo, Fernando Moreira and 
                         J{\'u}nior, Laerte Guimar{\~a}es Ferreira and Veloso, Gabriel 
                         Alves and Silva, Janete R{\^e}go",
                title = "Espectrorradiometria: Uma ferramenta para avalia{\c{c}}{\~a}o do 
                         potencial produtivo das pastagens tropicais",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "3994--4001",
         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 = "In Brazil, there are more than 100 million hectare, between 
                         central and Legal Amazonia, with pasture degradation, these 
                         causing significant economic and environmental damage for the 
                         country. Technological advances such as remote sensing can monitor 
                         the dynamic of grassland, but do not determine the quality of 
                         pastures, because there are intrinsic variables, such as pasture 
                         management that influence the quality of the data. The objective 
                         of this paper was to evaluate the use of spectroradiometry as a 
                         tool to evaluate the productive potential of tropical pastures in 
                         the micro region of S{\~a}o Miguel do Araguaia - Goi{\'a}s. The 
                         methodology was divide an assessment of grazing management and 
                         pasture quality by vegetation index obtained with a 
                         spectroradiometer. The results demonstrated that the farms visited 
                         determined three categories of grazing management, reasonable, 
                         great and bad; the analysis of the quality of pastures were 
                         characterized three types of high vegetative vigor qualities, 
                         agronomic degradation and biological degradation, where the NDVI 
                         (p <0.05) could discriminate roofing Brizantha H (2, N = 182) = 
                         31.993 p <0.001 compared to SAVI and EVI. Pastures with great and 
                         reasonable management is most likely to have the same spectral 
                         behavior than bad. The use of spectroradiometer allows 
                         differentiate these coverages in both types of grass.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "59896",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PSM2BR",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSM2BR",
           targetfile = "59896.pdf",
                 type = "Radiometria e sensores",
        urlaccessdate = "27 abr. 2024"
}