On the Use of Google Earth Engine and Sentinel Data to Detect 'Lost' Sections of Ancient Roads. The Case of Via Appia

The currently available tools and services as open and free cloud resources to process big satellite data opened up a new frontier of possibilities and applications including archeological research. These new research opportunities also pose several challenges to be faced, as, for example, the data processing and interpretation. This letter is about the assessment of different methods and data sources to support a visual interpretation of EO imagery. Multitemporal Sentinel 1 and Sentinel 2 data sets have been processed to assess their capability in the detection of buried archeological remains related to some lost sections of the ancient Via Appia road (herein selected as case study). The very subtle and nonpermanent features linked to buried archeological remains can be captured using multitemporal (intra- and inter-year) satellite acquisitions, but this requires strong hardware infrastructures or cloud facilities, today also available as open and free tools as Google Earth Engine (GEE). In this study, a total of 2948 Sentinel 1 and 743 Sentinel 2 images were selected (from February 2017 to August 2020) and processed using GEE to enhance and unveil archeological features. Outputs obtained from both Sentinel 1 and Sentinel 2 have been successfully compared with in situ analysis and high-resolution Google Earth images

A multifrequency and multisensor approach for the study and the restoration of monuments: the case of the Cathedral of Matera

Abstract. In this paper we propose an integrated approach to diagnostic prospecting applied to the cathedral of Matera, in Southern Italy. In particular, we have performed both an ultrasonic tomography and a high frequency GPR prospecting on some pillars of the Church to investigate about possible structural yielding and a GPR prospecting at lower frequencies on the floor, where also a linear inversion algorithm has been applied to the data

SAR Sentinel 1 imaging and detection of palaeo-landscape features in the mediterranean area

The use of satellite radar in landscape archaeology offers great potential for manifold applications, such as the detection of ancient landscape features and anthropogenic transformations. Compared to optical data, the use and interpretation of radar imaging for archaeological investigations is more complex, due to many reasons including that: (i) ancient landscape features and anthropogenic transformations provide subtle signals, which are (ii) often covered by noise; and, (iii) only detectable in specific soil characteristics, moisture content, vegetation phenomenology, and meteorological parameters. In this paper, we assessed the capability of SAR Sentinel 1 in the imaging and detection of palaeo-landscape features in the Mediterranean area of Tavoliere delle Puglie. For the purpose of our investigations, a significant test site (larger than 200 km2) was selected in the Foggia Province (South of Italy) as this area has been characterized for millennia by human frequentation starting from (at least) the Neolithic. The results from the Sentinel 1 (S-1) data were successfully compared with independent data sets, and the comparison clearly showed an excellent match between the S-1 based outputs and ancient anthropogenic transformations and landscape features

Google earth engine as multi-sensor open-source tool for supporting the preservation of archaeological areas: The case study of flood and fire mapping in metaponto, italy

In recent years, the impact of Climate change, anthropogenic and natural hazards (such as earthquakes, landslides, floods, tsunamis, fires) has dramatically increased and adversely affected modern and past human buildings including outstanding cultural properties and UNESCO heritage sites. Research about protection/monitoring of cultural heritage is crucial to preserve our cultural properties and (with them also) our history and identity. This paper is focused on the use of the open-source Google Earth Engine tool herein used to analyze flood and fire events which affected the area of Metaponto (southern Italy), near the homonymous Greek-Roman archaeological site. The use of the Google Earth Engine has allowed the supervised and unsupervised classification of areas affected by flooding (2013–2020) and fire (2017) in the past years, obtaining remarkable results and useful information for setting up strategies to mitigate damage and support the preservation of areas and landscape rich in cultural and natural heritage

Water adsorption on amorphous silica surfaces: A Car-Parrinello simulation study

A combination of classical molecular dynamics (MD) and ab initio Car-Parrinello molecular dynamics (CPMD) simulations is used to investigate the adsorption of water on a free amorphous silica surface. From the classical MD SiO_2 configurations with a free surface are generated which are then used as starting configurations for the CPMD.We study the reaction of a water molecule with a two-membered ring at the temperature T=300K. We show that the result of this reaction is the formation of two silanol groups on the surface. The activation energy of the reaction is estimated and it is shown that the reaction is exothermic.Comment: 12 pages, 6 figures, to be published in J. Phys.: Condens. Matte

Multi-Scale Monitoring of Rupestrian Heritage: Methodological Approach and Application to a Case Study

Most of the artistic heritage in the Mediterranean basin is hosted in rupestrian hypogeum whose peculiarity is given by the presence of at least one open side, which makes them particularly sensitive to meteorological conditions. This makes mandatory the monitoring of both indoor and outdoor environmental parameters to analyze the cause–effect relationship between microclimatic inside and outside the hypogeum. The paper proposes a spatial and temporal multi-scale methodological approach applied to a rupestrian church in Matera, which hosts precious wall paintings, particularly vulnerable to the effects of environmental parameters. The approach is based on the analysis of data acquired by three platforms: indoor, close-range outdoor, and outdoor data from a meteorological station and weather forecast from the COSMO 5 model. The method allowed to characterize the relationships between the indoor and outdoor parameters at different spatial and temporal scales. The results showed a significant correlation between the parameters, thus opening new opportunities for the monitoring of the rupestrian heritage based on the use of data systematically available, such as those from meteorological stations and meteorological forecast