XRF and 3D Modelling on a Composite Etruscan Helmet

Joshua Emmitt,Andrew Mcalister,Neda Bawden,Jeremy Armstrong

doi:10.3390/app11178026

Abstract

The presentation of X-ray fluorescence data (XRF) assays is commonly restricted to tables or graphical representations. While the latter may sometimes be in a 3D format, they have yet to incorporate the actual objects they are from. The presentation of multiple XRF assays on a 3D model allows for more accessible presentation of data, particularly for composite objects, and aids in their interpretation. We present a method to display and interpolate assay data on 3D models using the PyVista Python package. This creates a texture of the object that displays the relative differences in elemental composition. A crested helmet from Tomb 1036 from the Casale del Fosso necropolis, Veii, Italy, is used to exemplify this method. The results of the analysis are presented and show variation in composition across the helmet, which also corresponds with macroscopic and decorrelation stretching analyses.

Highlights

The application of photogrammetry for the purpose of creating 3D models is widely applied in archaeology and heritage studies [1,2]
3D modelling and portable X-ray fluorescence (pXRF) are readily applied on their own, the potential to combine them to enhance interpretation is largely unexplored
The results are assessed with decorrelation stretching of the photogrammetry model texture to further assist in the interpretation of the manufacture of an Etruscan crested helmet

Summary

Introduction

The application of photogrammetry for the purpose of creating 3D models is widely applied in archaeology and heritage studies [1,2]. Tomb 1036 from the Casale del Fosso necropolis, located to the northwest of the plateau (Figure 1), dates to between 750 and 731 BCE and was excavated in 1915. Sci. 2021, 11, x FOR PEER REVIEW the Casale del Fosso necropolis, located to the northwest of the plateau (Figure 1), dates to between 750 and 731 BCE and was excavated in 1915. This grave was, from its initial adnidscthoveepreyr,cuenivdeedrsqtuoaolditytoobf etheexgcerapvtieognoaol ddsu.eThtoe bconthtetxhtewsatyslae soifngbluerinalhaunmdatihoennbuumribale,r wahnedrethtehepebrocdeiyvwedasqudaelpitoysiotfedthiengtoraavfeosgsoao, dors.pTithgercaovnet,eixnt awwasoaodsienngbleoixnwhuhmicahtiaolnsobcuornia-l, tawinheedregtrhaevebgoodoydws.aTshdeegproasvietegdoiondtso iancflousdsae,doar sppiteagrr,aavep,ainr oaf wswooorddesn, abo‘mx awceh’i,cahpaalisro ocfocnotmaipnoedsitger‘asvheieglodos’d,ss.eTvhereagl rlaavrgeegeomodbsoisnsceldudbreodnazespdeiasrc,sapplaaciredofosvweor rtdhse,bao‘dmya,caen’,datphaisir hoeflmcoemt. Decorrelation stretching was undertaken on the 3D model texture to potentially provide another means of identifying the various components of the helmet

Photogrammetry

Decorrelation Stretch

Discussion

Conclusions