Ground Penetrating Radar (GPR) attribute analysis for archaeological prospection

2013 ◽  
Vol 97 ◽  
pp. 107-117 ◽  
Author(s):  
Wenke Zhao ◽  
Emanuele Forte ◽  
Michele Pipan ◽  
Gang Tian
Keyword(s):  
Ground Penetrating Radar ◽  
Archaeological Prospection ◽  
Attribute Analysis ◽  
Ground Penetrating

scholarly journals Integrating Geophysical and Photographic Data to Visualize the Quarried Structures of the Roman Town of Bassianae

2021 ◽  
Vol 13 (12) ◽  
pp. 2384
Author(s):  
Roland Filzwieser ◽  
Vujadin Ivanišević ◽  
Geert J. Verhoeven ◽  
Christian Gugl ◽  
Klaus Löcker ◽  
...  
Keyword(s):  
Ground Penetrating Radar ◽  
Urban Infrastructure ◽  
Aerial Photographs ◽  
Surface Model ◽  
Data Sets ◽  
Buried Structures ◽  
Archaeological Prospection ◽  
Ground Penetrating ◽  
Geophysical Prospection ◽  
Strong Agreement

Large parts of the urban layout of the abandoned Roman town of Bassianae (in present-day Serbia) are still discernible on the surface today due to the deliberate and targeted quarrying of the Roman foundations. In 2014, all of the town's intramural (and some extramural) areas were surveyed using aerial photography, ground-penetrating radar, and magnetometry to analyze the site's topography and to map remaining buried structures. The surveys showed a strong agreement between the digital surface model derived from the aerial photographs and the geophysical prospection data. However, many structures could only be detected by one method, underlining the benefits of a complementary archaeological prospection approach using multiple methods. This article presents the results of the extensive surveys and their comprehensive integrative interpretation, discussing Bassianae's ground plan and urban infrastructure. Starting with an overview of this Roman town's research history, we present the details of the triple prospection approach, followed by the processing, integrative analysis, and interpretation of the acquired data sets. Finally, this newly gained information is contrasted with a plan of Roman Bassianae compiled in 1935.

Large-area high-resolution ground-penetrating radar measurements for archaeological prospection

2018 ◽  
Vol 25 (3) ◽  
pp. 171-195 ◽  
Author(s):  
Immo Trinks ◽  
Alois Hinterleitner ◽  
Wolfgang Neubauer ◽  
Erich Nau ◽  
Klaus Löcker ◽  
...  
Keyword(s):  
High Resolution ◽  
Ground Penetrating Radar ◽  
Large Area ◽  
Archaeological Prospection ◽  
Radar Measurements ◽  
Ground Penetrating

scholarly journals ARCHAEOLOGICAL PROSPECTION IN SOUTHEASTERN PARÁ STATE, BRAZIL USING GEOPHYSICAL METHODS: A CASE STUDY OF SÍTIO DOMINGOS

2013 ◽  
Vol 31 (3) ◽  
pp. 515 ◽  
Author(s):  
José Gouvêa Luiz ◽  
Edithe Da Silva Pereira
Keyword(s):  
Ground Penetrating Radar ◽  
Geophysical Methods ◽  
Main Tool ◽  
Archaeological Site ◽  
Magnetic Anomalies ◽  
Archaeological Excavation ◽  
Archaeological Prospection ◽  
Magnetic Resistivity ◽  
Ground Penetrating

ABSTRACT. Magnetic, resistivity and ground-penetrating radar (GPR) methods were applied to Sítio Domingos, a Brazilian archaeological site located in Pará State, to find objects buried by an ancient civilization that may have inhabited the site. Archaeological excavations based on the locations of magnetic anomalies reveal a concentration of ceramic fragments and pots. The correlation between the resistivity models and the soil profile of the study area suggests that the resistivity range of 2000 to 2500 ohm-m represents the archaeological occupation layer. Several anomalous features detected by GPR are correlated with magnetic anomalies. However, when these features are analyzed independently of the magnetic anomalies, they do not conclusively represent the objects being searched. Therefore, GPR is not recommended as the main tool for archaeological prospection in the study area.Keywords: magnetometry, electrical resistivity, GPR, archaeological excavation. RESUMO. Os métodos magnético, resistividade e radar de penetração no solo (GPR) foram aplicados no Sítio Domingos, um sítio arqueológico brasileiro localizado no Estado do Pará, para encontrar objetos enterrados por uma civilização antiga que pode ter habitado a região. Escavações arqueológicas com base nos locais de anomalias magnéticas revelaram uma concentração de fragmentos de cerâmica e vasos. A correlação entre os modelos de resistividade e do perfil do solo da área de estudo sugere que a faixa de resistividade de 2000-2500 ohm-m representa a camada de ocupação arqueológica. V´arias feições anômalas detectadas pelo GPR são correlacionáveis com anomalias magnéticas. No entanto, quando essas feições são analisadas independente das anomalias magnéticas, elas não representam de forma conclusiva os objetos que est~so sendo procurados. Portanto, o GPR não é recomendado como a principal ferramenta de prospecção arqueológica na área de estudo.Palavras-chave: magnetometria, resistividade elétrica, GPR, escavação arqueológica.

scholarly journals Archaeological Prospection with Motorised Multichannel Ground-Penetrating Radar Arrays on Snow-Covered Areas in Norway

2019 ◽  
Vol 11 (21) ◽  
pp. 2485 ◽  
Author(s):  
Manuel Gabler ◽  
Immo Trinks ◽  
Erich Nau ◽  
Alois Hinterleitner ◽  
Knut Paasche ◽  
...  
Keyword(s):  
Snow Cover ◽  
Ground Penetrating Radar ◽  
Winter Season ◽  
Heritage Management ◽  
Winter Period ◽  
Archaeological Prospection ◽  
Different Temperatures ◽  
Agricultural Use ◽  
Snow Conditions ◽  
Ground Penetrating

The technical advancements of the past decade have rendered motorised, high-resolution ground-penetrating radar (GPR) investigations increasingly popular for archaeological research and cultural heritage management in Norway. However, the agricultural use of most survey areas limits the time available for fieldwork in spring and autumn and thus reduces the method’s potential. An extension of the fieldwork period into the winter season would be desirable. The project “Arkeologi i veien?” aimed to develop practical solutions for efficient motorised GPR surveys on snow and to evaluate to what extent the thickness of the snow cover affects data quality. Four sites with known archaeological remains in the ground have been investigated under snowless conditions and with snow cover. The comparative data analysis showed that GPR surveys can result in useful data even on areas covered with one metre of snow. This study shows that different temperatures and resulting variable snow conditions can have a strong effect on the quality of the generated GPR data. The possibility for GPR measurements on snow offers the opportunity to extend fieldwork into the winter period without conflicting with the growing season; however, local weather and snow conditions have to be closely observed in order to obtain useful prospection data.

scholarly journals Remote Sensing Materials for a Preliminary Archaeological Evaluation of the Giove Countryside (Terni, Italy)

2020 ◽  
Vol 12 (12) ◽  
pp. 2023 ◽  
Author(s):  
Pier Matteo Barone ◽  
Elizabeth Wueste ◽  
Richard Hodges
Keyword(s):  
Remote Sensing ◽  
Unmanned Aerial Vehicle ◽  
Ground Penetrating Radar ◽  
Preliminary Evaluation ◽  
American University ◽  
Archaeological Prospection ◽  
Tiber River ◽  
Aerial Vehicle ◽  
University Of Rome ◽  
Ground Penetrating

A collaboration between the American University of Rome, the Municipality of Giove, and Soprintendenza Archeologia, Belle Arti e Paesaggio dellʼUmbria has resulted in an academic project aimed at a preliminary evaluation of a particular area along the Tiber river that straddles the border between Umbria and Lazio. Archaeological prospection methods, such as Unmanned Aerial Vehicle (UAV)-based remote sensing, ground-penetrating radar (GPR), and photogrammetry, have made it possible to better study the landscape with respect to not only the changes the area has undergone recently, but also its evolution during the Roman and Medieval periods, while keeping the main communication route represented by the Tiber river as its fulcrum.

scholarly journals Working with Gaussian Random Noise for Multi-Sensor Archaeological Prospection: Fusion of Ground Penetrating Radar Depth Slices and Ground Spectral Signatures from 0.00 m to 0.60 m below Ground Surface

2019 ◽  
Vol 11 (16) ◽  
pp. 1895 ◽  
Author(s):  
Agapiou ◽  
Sarris
Keyword(s):  
Regression Model ◽  
Normal Distribution ◽  
Ground Penetrating Radar ◽  
Regression Models ◽  
Random Noise ◽  
Ground Surface ◽  
Archaeological Prospection ◽  
Spectral Signatures ◽  
Ground Penetrating ◽  
The Impact

The integration of different remote sensing datasets acquired from optical and radar sensors can improve the overall performance and detection rate for mapping sub-surface archaeological remains. However, data fusion remains a challenge for archaeological prospection studies, since remotely sensed sensors have different instrument principles, operating in different wavelengths. Recent studies have demonstrated that some fusion modelling can be achieved under ideal measurement conditions (e.g., simultaneously measurements in no hazy days) using advance regression models, like those of the nonlinear Bayesian Neural Networks. This paper aims to go a step further and investigate the impact of noise in regression models, between datasets obtained from ground-penetrating radar (GPR) and portable field spectroradiometers. Initially, the GPR measurements provided three depth slices of 20 cm thickness, starting from 0.00 m up to 0.60 m below the ground surface while ground spectral signatures acquired from the spectroradiometer were processed to calculate 13 multispectral and 53 hyperspectral indices. Then, various levels of Gaussian random noise ranging from 0.1 to 0.5 of a normal distribution, with mean 0 and variance 1, were added at both GPR and spectral signatures datasets. Afterward, Bayesian Neural Network regression fitting was applied between the radar (GPR) versus the optical (spectral signatures) datasets. Different regression model strategies were implemented and presented in the paper. The overall results show that fusion with a noise level of up to 0.2 of the normal distribution does not dramatically drop the regression model between the radar and optical datasets (compared to the non-noisy data). Finally, anomalies appearing as strong reflectors in the GPR measurements, continue to provide an obvious contrast even with noisy regression modelling.

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