Detection of Buried Roman Wall Remains in Ground‐penetrating Radar Data using Template Matching

Abstract

Whereas in the last decades the acquisition and processing of archaeological ground-penetrating radar (GPR) data have become mature, the interpretation is still challenging. Manual delineation in three dimensions is time consuming, and often the determination of an isosurface value is not straightforward. This paper presents a method designed specifically for the extraction of buried linear features such as wall foundations, based on template matching. First, the three-dimensional (3D) GPR data cube is synthesized into a two-dimensional (2D) slice. To achieve this, an energy slice based on a sufficiently large time window may often be appropriate, although in this study a combination with other attributes, for example based on phase symmetry, made weak anomalies more distinct. In the next step, we compute the 2D normalized cross-correlation of the composite 2D slice and a number of templates with dimensions similar to the walls in the data set. Of the resulting correlation matrices, the highest correlation coefficient is kept for each pixel, if it exceeds a certain threshold. In this way, wall foundations are successfully mapped, but also many false detections are produced. The latter are greatly reduced in number by using a size threshold and discarding isolated features. The remaining regions are enclosed in bounding boxes, which after vertical extrusion can be used as a simplified 3D representation of the wall structures, and for the creation of a filtered isosurface. For the evaluation of our results, a manual interpretation was used. In the 2D case (i.e. when comparing the total area of the automatically mapped structures versus the manually delineated ones), both the detection rate and the correctness were~77%. Slightly lower rates (~71%) were obtained in the 3D case (i.e. comparing volumes). Our method was applied to the GPR survey of a Roman villa in Kent, UK.

Ground-penetrating radar survey at Falerii Novi: a new approach to the study of Roman cities

“…This can be achieved by matching linear templates to an image (Verdonck 2016): a predefined model, representative of the (linear) shape and the dimensions of the targeted wall structures, is slid across a GPR time-slice. Where the template matches the GPR image, the presence of walls can be expected.…”

Geophysical Detection and Assessment of Leveled Mounds: An Example from the Upper Mississippi Valley

“…Anomalies are generally identified manually based on visual inspection, which is a tedious, time-consuming, and inconsistent process. As the scale of remote sensing investigations has increased, semiautomated and automated approaches to feature and site detection have been developed for aerial and satellite imagery (De Laet et al 2007; Lasaponara et al 2016; Trier et al 2009), airborne lidar data (Davis et al 2019; Schneider et al 2015; Trier and Pilø 2012; Trier et al 2015, 2019; Verhagen and Drǎguţ 2012), and ground-based geophysical data (Panagiotakis et al 2011; Pasolli et al 2009; Verdonck 2016). Despite potential benefits, use of such methods for archaeological applications remains infrequent (Bennett et al 2014; Opitz and Herrmann 2018).…”

Searching for Viking Age Fortresses with Automatic Landscape Classification and Feature Detection

“…This produces an array of the same dimensions as the target image where each pixel is scored, according to its similarity to the template. Template matching has been successfully applied to detect archaeological features in ALS [35][36][37], satellite imagery [37], and geophysical survey data [38,39]. For this, an implementation of Lewis's [40] method was used with procedurally generated rings with radii of 20 to 150 m and a width of 1 pixel.…”