# Improved Application of Hyperspectral Analysis to Rock Art Panels from El Castillo Cave (Spain)
## 4 Conclusions  
The presented methodology allows us to extend our knowledge of rock art and its documentation. The cave has been studied by different researchers who used different techniques throughout history since it was discovered in 1903. The reviewing of the rock art panels has produced an increase of six motifs where, previously, only one had been documented. Nowadays, recording methodologies involving rock art have to be non-intrusive to prevent the panels from being damaged when the data is recorded. The present research shows that integrating geomatics methods is key to reaching an accurate, global, comprehensive and synoptic vision of rock art, and it guarantees it can be repeated over time. It makes it possible to obtain information about non-visible regions of the electromagnetic spectrum. The proposed workflow makes the documentation process more sustainable for the cave, because it reduces the time spent inside it, and it avoids the use of targets, increasing the accuracy of control points by up to 2 mm; and, what is more important still, it is possible to have them throughout the panel, thus improving the robustness of the model. Most figures located inside cavities are subject to natural and artificial processes that cause the loss of coloring matter or the erosion of engraved surfaces, so the motifs can often be read with little definition. Applying the present methodology has made it possible to precisely define the original morphology of some painted motifs in different colours (and probably of different chemical composition). It is possible to accurately define the contours of the figures, to precisely recognize anatomical parts or areas of specific figures and, to obtain images that represent a highly reliable reconstruction of the original painting. In this way, figures difficult to see can be \"reconstructed\" and, thus, allow precise formal studies, or even serve as an efficient support for the production of facsimiles. In this case study, four topics of interest were presented: (a) Recognition of figures, (b) characterization of the coloring matters, (c) study of the state of conservation, and (d) analysis of the technical process. The results show it is possible to clearly differentiate mineralogical compositions, and coloring matter; something that is of great importance and must be studied in depth in the future. The main tool provided by hyperspectral data is the possibility of documenting the conservation of a motif, discriminating veiled areas, leached areas, flaking and any other taphanomic action to which the figure is subjected. They can deteriorate the coloring matter, hindering the interpretation of the motifs due to the decrease in signal strength. It has also been possible to accurately reveal the morphology of motifs, painted in different colors (and, therefore, using different chemical compositions), being possible to create cartography of each figure and the conservation problems associated with them. In rock art studies, usually conditioned by the state of conservation of the figures, reading superimpositions between strokes or figures is one of the fundamental problems. The method presented has made it possible to recognize overlaps of different pigments even below the calcite layer. PPI analysis and SAM classifications have permitted to obtain a map with fully interpreted classified information where each pixel has been assigned a thematic value. This makes it possible to read the line composition of motifs, allowing us to reconstruct the overlaying of lines in relation to the coloring matter. The presented methodology can generate rigorous documentation regarding the conservation of a motif, and the mapping of veiled and leached areas to create a reliable thematic cartography. It can therefore be concluded that hyperspectral remote sensing has a high potential in rock art applications when technical analysis, management and conservation of cultural heritage studies are performed. Conceptualization: V.B. and S.R. ; methodology: V.B. and E.C. ; software: V.B. and E.C.