@InProceedings{SilvaChavVascDuve:2015:ApÍnVe,
               author = "Silva, Marcus Vinicius Rios da and Chaves, Joselisa Maria and 
                         Vasconcelos, Rodrigo Nogueira and Duverger, Soltan Galano",
                title = "Aplica{\c{c}}{\~a}o do {\'{\i}}ndice de vegeta{\c{c}}{\~a}o 
                         ajustado ao solo-SAVI para a identifica{\c{c}}{\~a}o de 
                         fragmentos de caatinga em cultivos de Agave sisalana Perrine na 
                         regi{\~a}o Semi{\'a}rida do Brasil",
            booktitle = "Anais...",
                 year = "2015",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "5850--5857",
         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 = "Remote sensing has allowed the extraction of information on 
                         vegetation and indices-IV are commonly applied in mapping and 
                         vegetation modeling. The Vegetation Index Soil-Adjusted SAVI is 
                         the most commonly Index used on the identification of vegetation 
                         in semi-arid and deserts. The main objective of this article was 
                         to present the tests performed using the SAVI to identify 
                         fragments of Caatinga among Agave sisala Perrine crops in the 
                         semiarid of Bahia region. The methods consisted: i) collecting 30 
                         points on the field to represent areas of Caatinga and A. sisala; 
                         ii) correlation between data field and SAVI values for L = 1 and L 
                         = 0.5, generated from the satellite image Landsat OLI 8; and iii) 
                         statistical analysis of the data. The ANOVA test for data samples 
                         between Caatinga reflectance and A. sisala classes showed distinct 
                         values, with significance less than p=<0.0001, thereby 
                         demonstrating that areas can be classified from the SAVI IV. The 
                         SAVI IV L = 0.5 presented the best results, with an accuracy of 
                         98.37% of the pixels classified, reaching a Kappa coefficient of 
                         97.7%.",
  conference-location = "Jo{\~a}o Pessoa",
      conference-year = "25-29 abr. 2015",
                 isbn = "978-85-17-0076-8",
                label = "1202",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3JM4EMN",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3JM4EMN",
           targetfile = "p1202.pdf",
                 type = "Geoprocessamento e aplica{\c{c}}{\~o}es",
        urlaccessdate = "09 maio 2024"
}