@InProceedings{FontenelliGalCouDemMag:2017:CoMéSe,
               author = "Fontenelli, Julyane Vieira and Gallo, Bruna Cristina and Coutinho, 
                         Marcos Ant{\^o}nio Neris and Dematt{\^e}, Jos{\'e} Alexandre 
                         Melo and Magalh{\~a}es, Paulo S{\'e}rgio Graziano",
                title = "Combina{\c{c}}{\~a}o de m{\'e}todos de sensoriamento proximal e 
                         par{\^a}metros topogr{\'a}ficos para caracteriza{\c{c}}{\~a}o 
                         da variabilidade espacial do solo",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "5233--5240",
         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 = "The characterization of the spatial variability of production 
                         factors is essential for the management localized of productive 
                         areas, as required for precision agriculture (PA). Thus, the 
                         hypothesis of the work is that variations in topographic 
                         attributes cause significant changes in the apparent electrical 
                         conductivity and spectral characteristics of the soil, providing 
                         the use of relief as an information plan in the sampling directed 
                         to the construction of spectral models of soil attributes. The 
                         objective of this study was to evaluate the use of the apparent 
                         electrical conductivity of the soil to targeted the calibration 
                         samples of the spectral models to quantify the physical and 
                         chemical attributes of the soil and its relation with the 
                         variation of the topographic parameters in the field. For that, 34 
                         soil samples were collected at 0-0.20 m depth, in an area of 100 
                         ha, belonging to the Santa F{\'e} mill, in Tabatinga, State of 
                         S{\~a}o Paulo, Brazil. Soil spectra were measured using a 
                         commercially available spectrophotometer FieldSpec 4, in the range 
                         of 350 2500 nm (Vis - NIR -SWIR), with three replicates for each 
                         sample. The topographic data were obtained from the DEM - 
                         Topodata. Then, using radiometric information, principal component 
                         analysis (PCA) and regression models were generated by partial 
                         least squares (PLS) as multivariate analysis technique to 
                         correlate wavelength information with each constituent and to 
                         estimate the soil attributes. The physical and chemical soil 
                         properties vary along the slope, this differentiation was detected 
                         via electromagnetic spectrum. It appears that the DRS can assist 
                         in determining soil properties and knowledge of the soil spatial 
                         variability, adding new information to management practices in 
                         precision agriculture.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "59903",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PSM4G7",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSM4G7",
           targetfile = "59903.pdf",
                 type = "Radiometria e sensores",
        urlaccessdate = "27 abr. 2024"
}