Beyond the scale. Building formal approaches for the study of spatial patterns in Galician moundscapes (NW Iberian Peninsula)

In Galicia, works that studied the megalithic locational patterns developed only fieldwork-based approaches. As a result, the locational criteria were defined using ideas through a direct analysis at field, and never have been quantified and modelled with GIS methods until nowadays. In this work, a GIS methodology and a point pattern approach for the study of megalithic locational patterns is carried out. Starting from the definition of locational factors managed by literature, a number of first and second order properties were converted into spatial variables. From this point, specific regularities among the distribution of sites were established, which allows to determine trends in Galician megalithic occupation and open new possibilities of analysis in the study of Galician megalithic landscapes

Tailoring 3D modelling techniques for epigraphic texts restitution. Case studies in deteriorated roman inscriptions

Digital Image Modelling is becoming a standard approach in epigraphic studies, mostly expressed in the diffusion practice of research groups which want their materials being publicly accessible. However, there is an important lack of works which seek for the use of 3D tools to improve the epigraphic analysis and text reading. Therefore, this paper attempts to show the application of Photogrammetry Structure from Motion and Digital Image Modelling to 3D record and analyse inscriptions that are in poor state of preservation, aiming to resolve some text-restitution problems and contribute towards the definition of new methodologies in Roman epigraphy

Modelling mobility and visibility dynamics in Galician megalithic moundscapes. The case of Monte de Santa Marina and its surroundings (Sarria's region, Lugo)

This paper aims to analyse two traditional forms of association of the megaliths with the landscape, such as the natural mobility and the visibility of the landscape. Several analytical approaches based on Geographic Information Systems and Spatial Statistics are applied over the megalithic barrow landscape of Monte de Santa Mariña (Sarria’s region, Lugo) and its surroundings (NW of the Iberian Peninsula). Starting from the creation of a simulation model of natural movement and the analysis of the visibility of sites, the relevance of the potential transit routes as a locational variable is checked, as well as the role that visibility of these monuments may have played regarding these routes. Subsequently, the visual prominence of the monuments with background terrain is also analysed, being able to observe the existence of common tendencies in different necropoleis of this megalithic complex concerning the size of the visual basin. The results allow us to consider the existence of an important relation between the megalithic monuments and the natural passage through the territory, with unequal trends on the visual impact of the megalith, regarding the relation with other sites and the whole territory in which the necropolis is located, which seems to indicate the necessity to reconsider the traditional discourse using these regional trends

Digital imaging techniques for recording and analysing prehistoric rock art panels in Galicia (NW Iberia)

Several works have highlighted the relevance of 3D modelling techniques for the study of rock art, especially in case of deteriorated state of preservation. This paper presents a methodological approach to accurate document two Bronze Age rock art panels in Galicia (Spain), using photogrammetry SfM. The main aim is to show the application of digital enhancement techniques which have allowed the accurate depiction of the motifs and the correction of previous calques, focusing on the application of the exaggerated shading as a novel analytical method

Locational preferences and spatial arrangement in the barrow landscape of Serra do Barbanza (North-western Iberia)

As anywhere else around the world, GIS is an essential tool in Galician Archaeology (NW Spain) when examining and analysing spatial data. This is also true for the study of mounds in that area, since spatial analysis and statistics have become increasingly used for contrasting hypotheses regarding the locational preferences of these monuments, usually inferred from observations made during fieldwork or taken from studies conducted elsewhere. Drawing on this basis, in this paper, we have analysed the locational patterns of the tumuli of the upper tracts of the Serra do Barbanza (Galicia, NW Spain). Using a site-predictive modelling approach, several environmental covariates were analysed in order to explore their potential role in explaining the distribution of prehistoric mounds in the area. Subsequently, we studied the clustering of these monuments via second-order modelling. Our results suggest that tumuli in the Serra do Barbanza tended to cluster on a very local scale, a trend that can only be explained by intended site spacing strategies that may have taken place over millennia. Finally, by using significance testing via Monte Carlo Simulation, we have modelled both the effect of possible preferences regarding the location of mounds and the potential impact of tradition, with pre-existent megaliths possibly fostering the construction of more monuments in the nearby areas

Hybrid MSRM-Based Deep Learning and Multitemporal Sentinel 2-Based Machine Learning Algorithm Detects Near 10k Archaeological Tumuli in North-Western Iberia

This paper presents an algorithm for large-scale automatic detection of burial mounds, one of the most common types of archaeological sites globally, using LiDAR and multispectral satellite data. Although previous attempts were able to detect a good proportion of the known mounds in a given area, they still presented high numbers of false positives and low precision values. Our proposed approach combines random forest for soil classification using multitemporal multispectral Sentinel-2 data and a deep learning model using YOLOv3 on LiDAR data previously pre-processed using a multi–scale relief model. The resulting algorithm significantly improves previous attempts with a detection rate of 89.5%, an average precision of 66.75%, a recall value of 0.64 and a precision of 0.97, which allowed, with a small set of training data, the detection of 10,527 burial mounds over an area of near 30,000 km2, the largest in which such an approach has ever been applied. The open code and platforms employed to develop the algorithm allow this method to be applied anywhere LiDAR data or high-resolution digital terrain models are available

Hybrid MSRM-based deep learning and multitemporal Sentinel 2-based machine learning algorithm detects near 10k archaeological tumuli in north-western Iberia

This is the final version. Available on open access from MDPI via the DOI in this record.Data Availability Statement: All relevant material has been made available as Supplementary MaterialsThis paper presents an algorithm for large-scale automatic detection of burial mounds, one of the most common types of archaeological sites globally, using LiDAR and multispectral satellite data. Although previous attempts were able to detect a good proportion of the known mounds in a given area, they still presented high numbers of false positives and low precision values. Our proposed approach combines random forest for soil classification using multitemporal multispectral Sentinel-2 data and a deep learning model using YOLOv3 on LiDAR data previously pre-processed using a multi–scale relief model. The resulting algorithm significantly improves previous attempts with a detection rate of 89.5%, an average precision of 66.75%, a recall value of 0.64 and a precision of 0.97, which allowed, with a small set of training data, the detection of 10,527 burial mounds over an area of near 30,000 km2, the largest in which such an approach has ever been applied. The open code and platforms employed to develop the algorithm allow this method to be applied anywhere LiDAR data or high-resolution digital terrain models are available.European Union Horizon 2020Spanish Ministry of Science, Innovation and UniversitiesFundación BBV

Supplementary data and R code for the paper: 'The Spatial Structure of Galician Megalithic Landscapes (NW Iberia): A Case Study from the Monte Penide Region'

Archaeological data and R Code (RMarkDown) are provided

Supplementary data and R code for the paper: 'The Spatial Structure of Galician Megalithic Landscapes (NW Iberia): A Case Study from the Monte Penide Region'

Archaeological data and R Code (RMarkDown) are provided.THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV

The spatial structure of Galician megalithic landscapes (NW iberia): A case study from the Monte Penide region

It is well known that Neolithic megalithic landscapes are the result of complex locational logics governing where communities chose to site their funerary monuments. These logics in turn respond to broader environmental and cultural affordances, and the relationship between these has been a major topic in the megalithic archaeological literature for the last few decades. Thanks to new approaches in spatial statistical modelling, there is now considerable opportunity to revisit traditional megalithic locational concepts from a more systematic point of view, not least in Galician studies (NW Iberian Peninsula). In the paper that follows, we apply such a modelling approach to a large set of megalithic monuments located in the south of Galicia (Monte Penide and surroundings) with a view to exploring locational choices, spatial hierarchy and territoriality in these funerary landscapes. The results indicate that the distribution of megalithic mounds in this region reflects a preference for locations with particular environmental properties, while at a more local scale the spacing of these mounds seems to reflect some kind of social partitioning of the landscape. Via spatial cluster analysis and a further novel method for testing site hierarchy, we conclude that the mound sizes within nine different mound clusters exhibits a non-random hierarchical structure, with a larger mound per group and smaller ones around that, and with what appears to be a preference for the large monument to be at or near the meeting point of several watersheds and upland ridge-routes