Abstract
Abstract: The objective of this work was to simulate the bands of the WorldView-2 sensor from laboratory specters, in order to study its potential to detect iron oxides, besides proposing a spectral index based on the depth of the spectral feature (RHGtPf). The iron index (IFe) and the hematite index (IHm), developed by Madeira Netto for bands of Landsat TM-5 sensor, were adjusted for WorldView-2 to test the potential of the new yellow band. The results showed that the yellow band degrades to 2% compared to the red one. This is due to fact that mineral quantification and identification are in the absorption feature, not in the reflectance one, and it is only improved in the visualization of color. A new spectral index, the RHGtPF, based on the depth feature with the continuum-removed spectra, was proposed, since the new bands of the WorldView-2 sensor - the coastal blue and yellow bands - allow a better individualization of the absorption features for goethite and hematite separately. The new index is statistically similar to the ratio Hm / Gt + Hm; however, it is not similar to the mineralogical relation obtained with Munsell colors.
Highlights
Introduction2011; Gerighausen et al, 2012), and by means of hyperspectral systems (Baptista et al, 2011)
The objective of this work was to simulate the bands of the WorldView-2 sensor from laboratory specters, in order to study its potential to detect iron oxides, besides proposing a spectral index based on the depth of the spectral feature (RHGtPf)
The analyses show that, with the use of the yellow band (SWV3) in the ferric index, the correlation with IFe(TM5) degrades by only 2%, compared to the one obtained with the red band (SWV5)
Summary
2011; Gerighausen et al, 2012), and by means of hyperspectral systems (Baptista et al, 2011) This clay fraction is represented mainly by iron oxides (hematite and goethite), aluminum oxides (gibbsite), and clay minerals 1:1 group (kaolinite) present mainly in the Oxisols (Schaefer et al, 2008). The hematite/goethite mineralogical relation can be studied with remote sensing data, both multiand hyperspectral ones, that seek to spatialize the pedohydric character of an area, characterizing it as oxidation or oxidation of Fe+3 The visible region is the most important for iron color visualization in iron oxides, other absorption characteristics can be used in other portions of the spectrum for the quantification of iron oxides
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