4
RGB Combination Technique
The RGB combination technique enables the allocation of
three distinct type bands the red, green, and blue channels.
According to colour variance, depending on single channel
values, the RGB composite help to understand the satellites
data (Safianou et al., 2024).
The application of the spectral technique of band com-
bination followed the combinations defined by the authors
Mamani (2017, cited in Caiza, 2018) and Tommaso et al.
(2005, cited in Caiza, 2018) that were applied with the
purpose of making a general mapping of areas with clay
minerals and oxides.
Mamani (2017) establishes the combination: RGB 943
– For mapping oxides – Areas with pale yellow oxides.
Tommaso et al. (2005) establishes the combination:
RGB 461 – For mapping clay minerals and oxides – Areas
with purple-toned clays, and areas with pale yellow oxides
Band Ratio Technique
Since the spectral responses of rocks are similar, differenti-
ating between lithologies becomes challenging. Therefore,
we use techniques or methods that help us discriminate
among them. One such method is the use of band ratios,
which, as the name suggests, involves a division pixel by
pixel between the digital numbers (DN) stored in two or
more bands of the same image. This method helps us dis-
criminate between two materials with very different reflec-
tive behaviors in those two bands. The results will involve
pixels with the greatest difference in reflectance between the
two spectral bands (Rodríguez, 2008).
Regarding the band ratio technique, the ratios defined
by Santillán (2022) and Testa (2018) were followed (See
Table 1).
SWIR Lithological Identification Index Technique
The application of the third technique is related to the
Ninomiya indices (2003), which allow to reinforce the
response of those alteration zones with respect to the previ-
ous processing techniques, which is carried out by means of
RGB band products and ratios (See Table 2).
Spectral Mapping by the SAM method (Spectral Angle
Mapper)
The core aspect of extracting mineral information using
remote sensing techniques is the spectral response charac-
teristics. Different minerals display unique spectral prop-
erties due to variations in their internal structures. These
properties are evident in their absorption and reflection
behaviors across the near-infrared, short-wave infrared, and
Figure 3. Procedure for investigation Regarding the methodology used to determine
Table 1. Band Ratio techniques
Band Ratio Features Reference
4/6 Argillic to phyllic (illite, sericite,
muscovite)
(Santillán,
2022)
4/5 Advanced Argillic (kaolinite,
dickite, pyrophyllite and alunite)
(Santillán,
2022)
5/8 Propylitic (chlorite, epidote,
calcite)
(Santillán,
2022)
2/1 Fe3+ absorption (hematite and
goethite)
(Testa, 2018)
RGB Combination Technique
The RGB combination technique enables the allocation of
three distinct type bands the red, green, and blue channels.
According to colour variance, depending on single channel
values, the RGB composite help to understand the satellites
data (Safianou et al., 2024).
The application of the spectral technique of band com-
bination followed the combinations defined by the authors
Mamani (2017, cited in Caiza, 2018) and Tommaso et al.
(2005, cited in Caiza, 2018) that were applied with the
purpose of making a general mapping of areas with clay
minerals and oxides.
Mamani (2017) establishes the combination: RGB 943
– For mapping oxides – Areas with pale yellow oxides.
Tommaso et al. (2005) establishes the combination:
RGB 461 – For mapping clay minerals and oxides – Areas
with purple-toned clays, and areas with pale yellow oxides
Band Ratio Technique
Since the spectral responses of rocks are similar, differenti-
ating between lithologies becomes challenging. Therefore,
we use techniques or methods that help us discriminate
among them. One such method is the use of band ratios,
which, as the name suggests, involves a division pixel by
pixel between the digital numbers (DN) stored in two or
more bands of the same image. This method helps us dis-
criminate between two materials with very different reflec-
tive behaviors in those two bands. The results will involve
pixels with the greatest difference in reflectance between the
two spectral bands (Rodríguez, 2008).
Regarding the band ratio technique, the ratios defined
by Santillán (2022) and Testa (2018) were followed (See
Table 1).
SWIR Lithological Identification Index Technique
The application of the third technique is related to the
Ninomiya indices (2003), which allow to reinforce the
response of those alteration zones with respect to the previ-
ous processing techniques, which is carried out by means of
RGB band products and ratios (See Table 2).
Spectral Mapping by the SAM method (Spectral Angle
Mapper)
The core aspect of extracting mineral information using
remote sensing techniques is the spectral response charac-
teristics. Different minerals display unique spectral prop-
erties due to variations in their internal structures. These
properties are evident in their absorption and reflection
behaviors across the near-infrared, short-wave infrared, and
Figure 3. Procedure for investigation Regarding the methodology used to determine
Table 1. Band Ratio techniques
Band Ratio Features Reference
4/6 Argillic to phyllic (illite, sericite,
muscovite)
(Santillán,
2022)
4/5 Advanced Argillic (kaolinite,
dickite, pyrophyllite and alunite)
(Santillán,
2022)
5/8 Propylitic (chlorite, epidote,
calcite)
(Santillán,
2022)
2/1 Fe3+ absorption (hematite and
goethite)
(Testa, 2018)