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.

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As anywhere else, GIS is an essential tool in Galician archaeological research for examining and analysing spatial data. This is something quite clear in megalithic studies where in the last years these methods have been used for contrasting hypotheses regarding locational preferences drawn from fieldwork. As such, in this paper, a study of locational patterns of the megalithic sites located in the flattened top territories of A Serra do Barbanza (Galicia, NW Spain) is carried out. Using a site-predictive modelling approach, several environmental covariates were analysed to see their role in the distribution of mounds. Next, we study the clustering of megaliths via second-order modelling. The results obtained led us to conclude that the distribution of sites shows an aggregation at very local scales, a trend that can only be explained by intended site spacing dynamics that may have taken place over millennia. Using significance testing via Monte Carlo Simulation, the outcomes of this research allowed us to identify possible preferences regarding the selection of particular landscapes for the location of

ResumenEl Lidar aéreo se ha constituido en la última década como una de las herramientas más interesantes para la prospección arqueológica, puesto que permite, entre otras cosas, analizar el terreno con gran detalle obviando la vegetación. Planteamos un ejemplo de las posibilidades que para el Megalitismo la tecnología Lidar puede proporcionar. Para ello, hemos elegido la necrópolis megalítica del Monte de Santa Mariña (provincia de Lugo, Galicia), que cuenta con una treintena de monumentos catalogados. Para el estudio del terreno se ha procedido a diseñar una metodología de prospección arqueológica basada en datos Lidar que, gracias a diferentes análisis visuales propuestos, han permitido situar los monumentos correctamente e incluso encontrar uno nuevo. Palabras claveLidar, Sistemas de Información Geográfica, Megalitismo, Santa Mariña. AbstractOver the last decade, the aerial Lidar has been constituted as one of the most interesting tools for the archaeological survey, because it allows, among other things, to analyze the field in detail, specially obviating the vegetation. Thus, we propose an example of the possibilities that Lidar technology could provide in the case of Megalithic culture. Furthermore, we have chosen the megalithic necropolis of Monte de Santa Mariña (Lugo, Galicia), which had some thirty-four monuments officially cataloged. Consequently, before starting the archaeological survey we have planned a methodology based on Lidar data. In fact, thanks to the study of different types of visual analysis proposed by some authors, we were able to identify correctly the whole of all the monuments and even find a new one.