Studying the Construction of Floor Mosaics in the Roman Villa of Pisões (Portugal) Using Noninvasive Methods: High-Resolution 3D GPR and Photogrammetry

Over the past decade, high-resolution noninvasive sensors have been widely used in explorations of the first few meters underground at archaeological sites. However, remote sensing actions aimed at the study of structural elements that require a very high resolution are rare. In this study, layer characterization of the floor mosaic substrate of the Pisões Roman archaeological site was carried out. This work was performed with two noninvasive techniques: 3D ground penetrating radar (3D GPR) operating with a 1.6 GHz central frequency antenna, which is a very high-resolution geophysical method, and photogrammetry with imagery obtained by an unmanned aerial vehicle (UAV), which is a very high-resolution optical method. The first method allows penetration up to 30–40 cm depth and 3D models can be obtained, and with the second method, very high detail surface images and digital surface models can be obtained. In this study, we analyze a combination of data from both sensors to study a portion of the floor mosaic of the Pisões Roman Villa (Beja, Portugal) to obtain evidence of the inner structure. In this context, we have detected the main structural levels of the Roman mosaic and some internal characteristics, such as etched guides, internal cracking, and detection of higher humidity areas. The methodology that we introduce in this work can be referenced for the documentation of ancient pavements and may be used prior to carrying out preservation activities. Additionally, we intend to show that a Roman mosaic, understood as an archaeological structure, does not consist of only beautiful superficial drawings defined by the tesserae, but these mosaics are much more complex elements that must be considered in their entirety for preservation.

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Unmanned Aerial Vehicle (UAV) time-lapse monitoring of the instability processes affecting Varano Hill: A case study of the ancient Roman site of Villa Arianna

10.5194/egusphere-egu21-1110 ◽

2021 ◽

Author(s):

Renato Somma ◽

Alfredo Trocciola ◽

Daniele Spizzichino ◽

Alessandro Fedele ◽

Gabriele Leoni ◽

...

Keyword(s):

High Resolution ◽

Spatial Data ◽

Morphological Evolution ◽

Archaeological Site ◽

Pilot Project ◽

Time Lapse ◽

3D Models ◽

Slope Instability ◽

Test Case ◽

Slope Instabilities

<p>The archaeological site of Villa Arianna - located on Varano Hill, south of Vesuvius - offer tantalizing information regarding first-century AD resilience to hydrogeological risk. Additionally, the site provides an important test case for mitigation efforts of current and future geo-hazard. Villa Arianna, notable in particular for its wall frescoes, is part of a complex of Roman villas built between 89 BC and AD 79 in the ancient coastal resort area of Stabiae. This villa complex is located on a morphological terrace that separates the ruins from the present-day urban center of Castellammare di Stabia. The Varano hill is formed of alternating pyroclastic deposits, from the Vesuvius Complex, and alluvial sediments, from the Sarno River. The area, in AD 79, was completely covered by PDCs from the Plinian eruption of Vesuvius. Due to the geomorphological structure the slope is prone to slope instability phenomena that are mainly represented by earth and debris flows, usually triggered by heavy rainfall. The susceptibility is worsened by changes in hydraulic and land-use conditions mainly caused by lack of maintenance of mitigation works. Villa Arianna is the subject of a joint pilot project of the INGV-ENEA-ISPRA that includes non-invasive monitoring techniques such as the use of UAVs to study the areas of the slope at higher risk of instability. The project, in particular, seeks to implement innovative mitigation solutions that are non-destructive to the cultural heritage. UAVs represent the fastest way to produce high-resolution 3D models of large sites and allow archaeologists to collect accurate spatial data that can be used for 3D GIS analyses. Through this pilot project, we have used detailed 3D models and high-resolution ortho-images for new analyses and documentation of the site and to map the slope instabilities that threatens the Villa Arianna site. Through multi-temporal analyses of different data acquisitions, we intend to define the detailed morphological evolution of the entire Varano slope. These analyses will allow us to highlight priority areas for future low-impact mitigation interventions.</p>

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Ground-penetrating radar imaging reveals glacier's drainage network in 3D

The Cryosphere ◽

10.5194/tc-15-3975-2021 ◽

2021 ◽

Vol 15 (8) ◽

pp. 3975-3988

Author(s):

Gregory Church ◽

Andreas Bauder ◽

Melchior Grab ◽

Hansruedi Maurer

Keyword(s):

High Resolution ◽

Ground Penetrating Radar ◽

Radar Imaging ◽

Drainage Network ◽

Direct Impact ◽

3D Images ◽

Drainage Networks ◽

Glacier Dynamics ◽

3D Gpr ◽

Ground Penetrating

Abstract. Hydrological systems of glaciers have a direct impact on the glacier dynamics. Since the 1950s, geophysical studies have provided insights into these hydrological systems. Unfortunately, such studies were predominantly conducted using 2D acquisitions along a few profiles, thus failing to provide spatially unaliased 3D images of englacial and subglacial water pathways. The latter has likely resulted in flawed constraints for the hydrological modelling of glacier drainage networks. Here, we present 3D ground-penetrating radar (GPR) results that provide high-resolution 3D images of an alpine glacier's drainage network. Our results confirm a long-standing englacial hydrology theory stating that englacial conduits flow around glacial overdeepenings rather than directly over the overdeepening. Furthermore, these results also show exciting new opportunities for high-resolution 3D GPR studies of glaciers.

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Photogrammetric processing and application of multi-temporal satellite imagery stereopairs

Geodesy and Cartography ◽

10.22389/0016-7126-2021-974-8-36-44 ◽

2021 ◽

Vol 974 (8) ◽

pp. 36-44

Author(s):

R.V. Permyakov

Keyword(s):

High Resolution ◽

Satellite Imagery ◽

Weather Conditions ◽

3D Models ◽

High Resolution Imagery ◽

Multi Temporal ◽

Unfavourable Weather ◽

High Resolution Satellite Imagery ◽

Very High Resolution Imagery ◽

Very High

Stereopairs of very-high resolution satellite imagery constitute one of the key high-accurate data sources on heights. A stereophotogrammetric technique is a key method of processing these data. Despite that a number of spacecrafts gathering very-high-resolution imagery in a stereo mode constantly increases, the area of the Earth regularly covered by such data and stored in the archives of RSD operators remains relatively small and, as a rule, is limited only to large urban agglomerations. The new collection may not suit the customer for several reasons. Firstly, the materials of the new stereo collection are more expensive than those of the archived one. Secondly, due to unfavourable weather conditions and a busy schedule of satellites, the completion of the new collection may go beyond the deadline specified by the customer. Well known and brand-new criteria to form multi-temporal, stereopairs are analyzed. The specific of photogrammetric processing multi-temporal stereopairs is demonstrated. Application of multi-temporal stereopairs is described. In conclusion it is confirmed that 3D-models and high accurate DTMs can be generated basing on stereo models from multi-temporal satellite imagery in the absence of the following data

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Very-high-resolution mapping of river-immersed topography by remote sensing

Progress in Physical Geography Earth and Environment ◽

10.1177/0309133308096030 ◽

2008 ◽

Vol 32 (4) ◽

pp. 403-419 ◽

Cited By ~ 72

Author(s):

Denis Feurer ◽

Jean-Stéphane Bailly ◽

Christian Puech ◽

Yann Le Coarer ◽

Alain A. Viau

Keyword(s):

Remote Sensing ◽

High Resolution ◽

Large Scale ◽

Aerial Image ◽

Depth Measurement ◽

Very High Spatial Resolution ◽

Remote Sensing Techniques ◽

Logarithmic Relationship ◽

Ground Penetrating ◽

Very High

Remote sensing has been used to map river bathymetry for several decades. Non-contact methods are necessary in several cases: inaccessible rivers, large-scale depth mapping, very shallow rivers. The remote sensing techniques used for river bathymetry are reviewed. Frequently, these techniques have been developed for marine environment and have then been transposed to riverine environments. These techniques can be divided into two types: active remote sensing, such as ground penetrating radar and bathymetric lidar; or passive remote sensing, such as through-water photogrammetry and radiometric models. This last technique — which consists of finding a logarithmic relationship between river depth and image values — appears to be the most used. Fewer references exist for the other techniques, but lidar is an emerging technique. For each depth measurement method, we detail the physical principles and then a review of the results obtained in the field. This review shows a lack of data for very shallow rivers, where a very high spatial resolution is needed. Moreover, the cost related to aerial image acquisition is often huge. Hence we propose an application of two techniques, radiometric models and through-water photogrammetry, with very- high-resolution passive optical imagery, light platforms, and off-the-shelf cameras. We show that, in the case of the radiometric models, measurement is possible with a spatial filtering of about 1 m and a homogeneous river bottom. In contrast, with through-water photogrammetry, fine ground resolution and bottom textures are necessary.

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Very-high-resolution electrical resistivity imaging of buried foundations of a Roman villa near Nonnweiler, Germany

Archaeological Prospection ◽

10.1002/arp.1703 ◽

2018 ◽

Vol 25 (3) ◽

pp. 209-218 ◽

Cited By ~ 3

Author(s):

Osamah Saad Al-Saadi ◽

Volkmar Schmidt ◽

Michael Becken ◽

Thomas Fritsch

Keyword(s):

Electrical Resistivity ◽

High Resolution ◽

Electrical Resistivity Imaging ◽

Resistivity Imaging ◽

Roman Villa ◽

Very High

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The Effectiveness of Large-Scale, High-Resolution Ground-Penetrating Radar Surveys and Trial Trenching for Archaeological Site Evaluations—A Comparative Study from Two Sites in Norway

Remote Sensing ◽

10.3390/rs12091408 ◽

2020 ◽

Vol 12 (9) ◽

pp. 1408 ◽

Cited By ~ 1

Author(s):

Lars Gustavsen ◽

Arne Anderson Stamnes ◽

Silje Elisabeth Fretheim ◽

Lars Erik Gjerpe ◽

Erich Nau

Keyword(s):

High Resolution ◽

Ground Penetrating Radar ◽

Large Scale ◽

Archaeological Site ◽

Heritage Management ◽

Detection Rates ◽

Complementary Method ◽

Advantages And Disadvantages ◽

A Site ◽

Ground Penetrating

The use of large-scale, high-resolution ground-penetrating radar surveys has increasingly become a part of Norwegian cultural heritage management as a complementary method to trial trenching surveys to detect and delineate archaeological sites. The aim of this article is to collect, interpret and compare large-scale, high-resolution ground-penetrating radar (GPR) survey data with results from trial trenching and subsequent large-scale excavations, and to extract descriptive and spatial statistics on detection rates and precision for both evaluation methods. This, in turn, is used to assess the advantages and disadvantages of both conventional, intrusive methods and large-scale GPR surveys. Neither method proved to be flawless, and while the trial trenching had a better overall detection rate, organic and charcoal rich features were nearly just as easily detected by both methods. Similarly, the spatial representability was similar, even though the total detection rates were lower with the GPR. This can be used as an argument in advance of integrating full-coverage GPR results into a site evaluation scheme, preferably in combination with other methods. Overall, these analyses have highlighted drawbacks and possibilities in both methods that are important contributions in understanding how to use them and integrate them in future site evaluations.

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Spatial Representation of GPR Data—Accuracy of Asphalt Layers Thickness Mapping

Remote Sensing ◽

10.3390/rs13050864 ◽

2021 ◽

Vol 13 (5) ◽

pp. 864

Author(s):

Šime Bezina ◽

Ivica Stančerić ◽

Josipa Domitrović ◽

Tatjana Rukavina

Keyword(s):

Layer Thickness ◽

Relative Error ◽

Spatial Representation ◽

3D Model ◽

3D Models ◽

Average Relative Error ◽

3D Gpr ◽

Additional Processing ◽

Ground Penetrating ◽

Pavement Thickness

Information on pavement layer thickness is very important for determining bearing capacity, estimating remaining life and strengthening planning. Ground-penetrating radar (GPR) is a nondestructive testing (NDT) method used for determining the continuous pavement layer thickness in the travel direction. The data obtained with GPR in one survey line is suitable for the needs of repair and rehabilitation planning of roads and highways, but not for wider traffic areas such as airfield pavements. Spatial representation of pavement thickness is more useful for airfield pavements but requires a 3D model. In the absence of 3D GPR, a 3D model of pavement thickness can be created by additional processing of GPR data obtained from multiple survey lines. Five 3D models of asphalt pavements were created to determine how different numbers of survey lines affect their accuracy. The distance between survey lines ranges from 1 to 5 m. The accuracy of the 3D models is determined by comparing the asphalt layer thickness on the model with the values measured on 22 cores. The results, as expected, show that the highest accuracy is achieved for the 3D model created with a distance of 1 m between survey lines, with an average relative error of up to 1.5%. The lowest accuracy was obtained for the 3D model created with a distance of 4 m between the survey lines, with an average relative error of 7.4%.

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Automatic Shadow Detection in Urban Very-High-Resolution Images Using Existing 3D Models for Free Training

Remote Sensing ◽

10.3390/rs11010072 ◽

2019 ◽

Vol 11 (1) ◽

pp. 72 ◽

Cited By ~ 5

Author(s):

Kaixuan Zhou ◽

Roderik Lindenbergh ◽

Ben Gorte

Keyword(s):

High Resolution ◽

Image Interpretation ◽

3D Models ◽

Shadow Detection ◽

Acquisition Time ◽

Support Vector ◽

K Nearest Neighbors ◽

Tree Construction ◽

Training Samples ◽

Very High

Up-to-date 3D city models are needed for many applications. Very-high-resolution (VHR) images with rich geometric and spectral information and a high update rate are increasingly applied for the purpose of updating 3D models. Shadow detection is the primary step for image interpretation, as shadow causes radiometric distortions. In addition, shadow itself is valuable geometric information. However, shadows are often complicated and environment-dependent. Supervised learning is considered to perform well in detecting shadows when training samples selected from these images are available. Unfortunately, manual labeling of images is expensive. Existing 3D models have been used to reconstruct shadows to provide free, computer-generated training samples, i.e., samples free from intensive manual labeling. However, accurate shadow reconstruction for large 3D models consisting of millions of triangles is either difficult or time-consuming. In addition, due to inaccuracy and incompleteness of the model, and different acquisition time between 3D models and images, mislabeling refers to training samples that are shadows but labeled as non-shadows and vice versa. We propose a ray-tracing approach with an effective KD tree construction to feasibly reconstruct accurate shadows for a large 3D model. An adaptive erosion approach is first provided to remove mislabeling effects near shadow boundaries. Next, a comparative study considering four classification methods, quadratic discriminant analysis (QDA) fusion, support vector machine (SVM), K nearest neighbors (KNN) and Random forest (RF), is performed to select the best classification method with respect to capturing the complicated properties of shadows and robustness to mislabeling. The experiments are performed on Dutch Amersfoort data with around 20% mislabels and the Toronto benchmark by simulating mislabels from inverting shadows to non-shadows. RF is tested to give robust and best results with 95.38% overall accuracy (OA) and a value of 0.9 for kappa coefficient (KC) for Amersfoort and around 96% OA and 0.92 KC for Toronto benchmarks when no more than 50% of shadows are inverted. QDA fusion and KNN are tested to be robust to mislabels but their capability to capture complicated properties of shadows is worse than RF. SVM is tested to have a good capability to separate shadow and non-shadows but is largely affected by mislabeled samples. It is shown that RF with free-training samples from existing 3D models is an automatic, effective, and robust approach for shadow detection from VHR images.

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Integrated data analysis at an archaeological site: A case study using 3D GPR, magnetic, and high-resolution topographic data

Geophysics ◽

10.1190/1.3460432 ◽

2010 ◽

Vol 75 (4) ◽

pp. B169-B176 ◽

Cited By ~ 30

Author(s):

Urs Böniger ◽

Jens Tronicke

Keyword(s):

High Resolution ◽

Data Acquisition ◽

Digital Terrain Model ◽

Positional Information ◽

Archaeological Site ◽

Geophysical Data ◽

Integrated Analysis ◽

Topographic Data ◽

3D Gpr ◽

Difficult Terrain

We have collected magnetic, 3D ground-penetrating-radar (GPR), and topographic data at an archaeological site within the Palace Garden of Paretz, Germany. The survey site covers an area of approximately [Formula: see text] across a hill structure (dips of up to 15°) that is partly covered by trees. The primary goal of this study was to detect and locate the remains of ancient architectural elements, which, from historical records, were expected to be buried in the subsurface at this site. To acquire our geophysical data, we used a recently developed surveying approach that combines the magnetic and GPR instrument with a tracking total station (TTS). Besides efficient data acquisition, this approach provides positional information at an accuracy within the centimeter range. At the Paretz field site, this information was critical for processing and analyzing our geophysical data (in particular, GPR data) and enabled us to generate a high-resolution digital terrain model (DTM) of the surveyed area. Integrated analysis and interpretation based on composite images of the magnetic, 3D GPR, and high-resolution DTM data as well as selected attributes derived from these data sets allowed us to outline the remains of an artificial grotto and temple. Our work illustrates the benefit of using multiple surveying technologies, analyzing and interpreting the resulting data in an integrated fashion. It further demonstrates how modern surveying solutions allow for efficient, accurate data acquisition even in difficult terrain.

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GPR Clutter Reflection Noise-Filtering through Singular Value Decomposition in the Bidimensional Spectral Domain

Remote Sensing ◽

10.3390/rs13102005 ◽

2021 ◽

Vol 13 (10) ◽

pp. 2005

Author(s):

Rui Jorge Oliveira ◽

Bento Caldeira ◽

Teresa Teixidó ◽

José Fernando Borges

Keyword(s):

Singular Value Decomposition ◽

Singular Value ◽

Spectral Domain ◽

Roman Villa ◽

Useful Signal ◽

3D Gpr ◽

Effective Signal ◽

Value Decomposition ◽

Ground Penetrating

Usually, in ground-penetrating radar (GPR) datasets, the user defines the limits between the useful signal and the noise through standard filtering to isolate the effective signal as much as possible. However, there are true reflections that mask the coherent reflectors that can be considered noise. In archaeological sites these clutter reflections are caused by scattering with origin in subsurface elements (e.g., isolated masonry, ceramic objects, and archaeological collapses). Its elimination is difficult because the wavelet parameters similar to coherent reflections and there is a risk of creating artefacts. In this study, a procedure to filter the clutter reflection noise (CRN) from GPR datasets is presented. The CRN filter is a singular value decomposition-based method (SVD), applied in the 2D spectral domain. This CRN filtering was tested in a dataset obtained from a controlled laboratory environment, to establish a mathematical control of this algorithm. Additionally, it has been applied in a 3D-GPR dataset acquired in the Roman villa of Horta da Torre (Fronteira, Portugal), which is an uncontrolled environment. The results show an increase in the quality of archaeological GPR planimetry that was verified via archaeological excavation.

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