Archaeological Prospection最新文献

LiDAR data are quite commonly used for the analysis of archaeological landscapes over large areas in order to identify a wide range of cultural features. Open access datasets provided by regional or national services are very suitable for this medium/large scale exploration, but they often fail in the identification of more subtle microtopographical features at a site scale. Airborne Laser Scanning (ALS) with higher resolution LiDAR coverage can fill this gap, offering valuable clues about the internal spatial organization of ancient settlements. In this paper, we offer a representative example of this casuistry focused on Iron Age fortified sites (hillforts) in the Southwest of the Iberian Peninsula. The process of capture and processing of LiDAR data combined with results of photogrammetric flights is explained. An analysis based on the application of visualization methods designed for archaeological investigation was made, in order to extract as much information as possible. From this point onwards, automatic and semiautomatic detection techniques were developed in order to recognize regular patterns that could eventually help in the reconstruction of the urban landscape of the sites. Finally, the results are combined with other nondestructive methods in order to provide a reliable diagnostic about the cultural interpretation of the features we have detected.

The paper presents the results of a noninvasive geophysical search for 19th-century underground tanks located in the former Austrian imperial barracks complex of Archduke Rudolf in Krakow (Poland). The location of the tanks was necessary to assess their condition for safety reasons. Complementary geophysical methods in terms of field conditions and data acquisition, that is, magnetometry, ground penetrating radar (GPR) and electrical resistivity tomography (ERT), were used to locate the tanks. Interdisciplinary surveys made it possible to identify the subsurface structure, locate sewage settling tanks and verify archival documentation. The paper presents the problems that arise in imaging underground structures using applied geophysical methods. The aim of the study was also to assess the effectiveness of these methods in subsurface identification, including 2D, 2.5D and 3D ERT surveys. The applied sequence of measurements (magnetometric, GPR and ERT) proved to be correct and the most effective. It allowed for narrowing down the research area. Magnetometric measurements allowed for the location of iron elements related to the construction of the tanks. GPR measurements determined their range. The ERT results showed that 2D and 2.5D surveys conducted in the parallel-line arrangement are as effective in determining the location of an anomalous object as the 3D orthogonal-line arrangement. The 3D method enabled the identification of additional anomalies not detected by the 2.5D method. From the point of view of the practicality of both techniques, the 2.5D method turned out to be better than the 3D method, due to the simplicity of the fieldwork, lower spatial and hardware requirements, a greater depth range and lower complexity of data acquisition and processing.

The integrated use of remote sensing (RS) techniques, vertical magnetic gradient (VMG) and electrical resistivity tomography (ERT) measurements, and, in particular, combined analysis of 2D and 3D data, can provide a viable option for the identification of targets of interest at complicated archaeological sites. In this regard, a case study is Kom C at the archaeological site of Buto (Tell El Fara'in) in the northern Nile Delta (Egypt), where satellite data (Google Earth, Landsat 8 and OrbView-3), VMG and ERT measurements were collected prior to site excavation. In this particular case, soil salinity in the buried structures, a lack of contrast in magnetic susceptibility and electrical resistivity, as well as the orientation, complex spatial distribution and overlapping of the architectural elements, all contributed to a number of anomalies that were difficult to interpret using only 2D results. Initially, the archaeological remains were identified as being made of mud-brick based on land surface temperature (LST) estimated from thermal bands (Bands 10 and 11) in Landsat 8. Then, the high-resolution satellite data, as well as the VMG and ERT (2D, quasi-3D and full 3D resistivity models), were integrated to produce a comprehensive map of buried archaeological features. Excavations by Kafrelsheikh University in collaboration with the Ministry of Tourism and Antiquities recovered archaeological remains, including architectural elements that were perhaps used for official or administrative purposes or pottery-making workshops during the Late Roman period (between the 4th and 7th century ce). The direct comparison of geophysical results to archaeological evidence from the excavation enabled a robust interpretation of geophysical anomalies visible in the horizontal resistivity depth slice and magnetic maps. As a whole, this case study highlights the value of combining satellite data with the analysis of 2D data and 3D views of geophysical surveys to better understand the real distribution of buried archaeological remains at similar complex sites.

The archaeological zone of Mitla has an invaluable place within the Mexican cultural heritage. This pre-Hispanic city concentrated the political and religious power of the central valleys of Oaxaca, south of Mexico, mainly during the Postclassic period. However, despite its great cultural importance and considering the risk to its monuments due to the high seismicity of the region, very few studies have focused on the systematic exploration of the subsoil of this area. The present research aimed to characterize the subsoil of one of the architectural compounds of the archaeological zone, the Group of the Columns, aiming to identify possible underground elements such as architectural structures, tunnels or tombs. For that purpose, three non-invasive geophysical methods were applied, ground penetrating radar (GPR), electrical resistivity tomography (ERT) and ambient noise tomography (ANT). In the palace, all three methods showed the presence of a substructure below the Hall of the Columns. In the Plaza of the Columns, the GPR detected anthropogenic walls and platforms at different depths that suggest a different configuration of the square and a more prolonged occupation of this group. The results open the discussion about the temporality of the first construction of this architectural group.

Due to saving time and manpower, automatic and semi-automatic methods can be used to identify and analyse ancient artefacts. Such methods are usually among the studies of neural networks and machine learning systems, which are carried out using remote sensing data and are completely based on spatial information. In the present research, the aim is to detect archaeological phenomena in the landscape of the historical city of Zuzan using convolutional neural network and object detection using the YOLO v8 algorithm, which uses aerial images from the 1960s and 1990s as input data. The most important steps of this method are: training and learning model, image pre-processing, feature extraction and feature labelling are implemented to provide an automatic pattern recognition system for recognizing archaeological phenomena in an urban landscape. The training data set consists of old aerial images in which features such as the city wall (fence), Citadel and Aqueduct (Qanat) are labelled. The results of CNN training with aerial images of the 60s and 90s and Yolo modelling show the detection of feature such as the aqueduct with 69% accuracy, the city wall with 91% accuracy and the citadel with 100% accuracy.