Lênio S. Galvão

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We used two hyperspectral sensors at two different scales to test their potential to estimate biophysical properties of grazed pastures in Rondônia in the Brazilian Amazon. Using a field spectrometer, ten remotely sensed measurements (i.e., two vegetation indices, four fractions of spectral mixture analysis, and four spectral absorption features) were(More)
This paper focuses on the application of Extreme Learning Machines (ELM) to the classification of remote sensing hyperspectral data. The specific aim of the work is to obtain accurate thematic maps of soybean crops, which have proven to be difficult to identify by automated procedures. The classification process carried out is as follows: First, spectral(More)
Irrigation-induced salinization is an important land degradation process that affects crop yield in the Brazilian semi-arid region, and gypsum has been used as a corrective measure for saline soils. Fluvent soil samples (180) were treated with increasing levels of salinization of NaCl, MgCl 2 and CaCl 2. The salinity was gauged using electrical conductivity(More)
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