On-Site VIS-NIR Spectral Reflectance and Colour Measurements—A Fast and Inexpensive Alternative for Delineating Sediment Layers Quantitatively? A Case Study from a Monumental Bronze Age Burial Mound (Seddin, Germany)

Abstract

Quantitative sediment analyses performed in the laboratory are often used throughout archaeological excavations to critically reflect on-site stratigraphic delineation. Established methods are, however, often time-consuming and expensive. Recent studies suggest that systematic image analysis can objectivise the delineation of stratigraphic layers based on fast quantitative spectral measurements. The presented study examines how these assumptions prevail when compared to modern techniques of sediment analysis. We examine an archaeological cross-section at a Bronze Age burial mound near Seddin (administrative district Prignitz, Brandenburg, Germany), consisting of several layers of construction-related material. Using detailed on-site descriptions supported by quantitatively measured sediment properties as a measure of quality, we compare clustering results of (i) extensive colour measurements conducted with an RGB and a multispectral camera during fieldwork, as well as (ii) selectively sampled sedimentological data and (iii) visible and near infrared (VIS-NIR) hyperspectral data, both acquired in the laboratory. Furthermore, the influence of colour transformation to the CIELAB colour space (Commission Internationale de l’Eclairage) and the possibilities of predicting soil organic carbon (SOC) based on image data are examined. Our results indicate that quantitative spectral measurements, while still experimental, can be used to delineate stratigraphic layers in a similar manner to traditional sedimentological data. The proposed processing steps further improved our results. Quantitative colour measurements should therefore be included in the current workflow of archaeological excavations.

Towards timing and stratigraphy of the Bronze Age burial mound royal tomb (Königsgrab) of Seddin (Brandenburg, northeastern Germany)

“…This interpretation is supported by the particular signature of the values, i.e., the TC values decrease with increasing depth, which is a typical feature of soil development. The results of Haburaj et al (2020) support this interpretation, too. They study the upper part of the same excavation trench and combine data from RGB and multispectral cameras, visible and near-infrared hyperspectral data, and geochemical data.…”

“…They study the upper part of the same excavation trench and combine data from RGB and multispectral cameras, visible and near-infrared hyperspectral data, and geochemical data. Their image classifications show that soil organic carbon is mainly increased in layers 24, 21, and 14 (according to the layer counting presented here) and that these layers run more or less horizontally along the entire width of the excavation trench (Haburaj et al, 2020). Even though these arguments support the interpretation of initial in situ accumulation of organic matter, inherited sediment properties from reworked material cannot be excluded.…”

Coupling spectral imaging and laboratory analyses to digitally map sediment parameters and stratigraphic layers in Yeha, Ethiopia

“…Nonetheless, we see the main reason for the poor performance of the hyperspectral data of EVI in the lighting situation during image acquisition: the adjacent walls of the trench are situated directly left and right of the captured part of profile EVI. Similar to the shadow cast by adjacent trench walls as described by Haburaj et al 2019 [13], the walls in profile EVI most likely reflected and scattered the artificial light differently between single measurements due to changing lamp positions and caused the observed distortions in the hyperspectral image data of profile EVI.…”

“…Various studies suggest the transformation of spectral data prior to processing [13,[43][44][45][46]. We therefore created the following datasets as input for the regression analyses: (i) the RGB data, (ii) the CIELAB data derived from the RGB data, and (iii) the pre-processed hyperspectral data (480-830 nm, 10 nm steps).…”

“…However, the studies of Steffens and Buddenbaum 2012 [ 6 ] and Hobley et al 2018 [ 7 ] were carried out under controlled laboratory conditions. Transferability of the proposed method into a less controlled environment has been examined by Zhang and Hartemink 2019 [ 12 ] and Haburaj et al 2020 [ 13 ], who show that RGB imaging and multispectral imaging are also suitable tools to map stratigraphic layers under fieldwork conditions. Zhang and Hartemink 2019 [ 12 ] examined the extrapolation of SOC content, pH values, grain size composition and weathering indices based on the RGB image data of a soil profile that was captured on-site.…”