Spectral behavior of the soil it's a term used to define the interactions of the electromagnetic radiation with the different types of soil and intrinsicfactors between them, likethephysico-chemicalproperties. With the advance of techniques and technology, the remote sensing has been a very helpful tool for mapping the soils through the spectroscopy of reflectance. With the advance of new sensors systems, there's a need to investigate their potentials for spatial discrimination of the objects, for example, the mineral constituentsof a soil spot. The goal of this study was to investigate the potentials of WorlView 2 in detecting iron oxides, due to the presence of new bands, when compared to the Landsat TM5 sensor, especially in the range of visible light, which are the main spectral features of this minerals. The rates developed by Madeira Netto (1993), IFeand the IHm were rewritten with the yellow band and red band of the WorlView 2and, with the results, it was proved that the better discretization of iron's oxides identification are linked to the feature of absorption and not to the reflection, and with that the yellow band helps only the preview of the soil's hue. It was proposed the RHGtPF's rates that it's based in outgoing removal and in it depth of feature and it was statically compared with the chemistry relation Hm/Hm+Gt made by Madeira Netto (1993) and the RHGt munsell by parameters of the soil's colors. It was noticed that the relation Hm/Hm+Gt and the new indication are similar to each other, but the RHGt munsell and the new indication are different to each other. Algorithms, like Spectral AngleMapper (SAM) and Linear Spectral Unmixing (LSU), were studied as well to classify the iron oxides with the data of WorldView 2. The SAM'sresults was satisfactory because it named correctly both minerals. The LSU's results shows that the correlation between both minerals it's reverse because of the chemical and geomorphological diference in the environment. The RHGtPF's rate was compared with the Hm/Hm+Gt relation estimated from the LSU's percentage data. The correlation coefficient was strong and positive and found the possibility of iron's oxides quantification and identification by the new spectral indication.