%0 Conference Proceedings
%4 sid.inpe.br/marte2/2017/10.27.14.05.38
%2 sid.inpe.br/marte2/2017/10.27.14.05.39
%@isbn 978-85-17-00088-1
%F 59903
%T Combinação de métodos de sensoriamento proximal e parâmetros topográficos para caracterização da variabilidade espacial do solo
%D 2017
%A Fontenelli, Julyane Vieira,
%A Gallo, Bruna Cristina,
%A Coutinho, Marcos Antônio Neris,
%A Demattê, José Alexandre Melo,
%A Magalhães, Paulo Sérgio Graziano,
%@electronicmailaddress julyane.fontenelli@feagri.unicamp.br
%E Gherardi, Douglas Francisco Marcolino,
%E Aragão, Luiz Eduardo Oliveira e Cruz de,
%B Simpósio Brasileiro de Sensoriamento Remoto, 18 (SBSR)
%C Santos
%8 28-31 maio 2017
%I Instituto Nacional de Pesquisas Espaciais (INPE)
%J São José dos Campos
%P 5233-5240
%S Anais
%1 Instituto Nacional de Pesquisas Espaciais (INPE)
%X 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 Fé mill, in Tabatinga, State of São 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.
%9 Radiometria e sensores
%@language pt
%3 59903.pdf