Exploiting satellite SAR for archaeological prospection and heritage site protection

Optical and Synthetic Aperture Radar (SAR) remote sensing has a long history of use and reached a good level of maturity in archaeological and cultural heritage applications, yet further advances are viable through the exploitation of novel sensor data and imaging modes, big data and high-performance computing, advanced and automated analysis methods. This paper showcases the main research avenues in this field, with a focus on archaeological prospection and heritage site protection. Six demonstration use-cases with a wealth of heritage asset types (e.g. excavated and still buried archaeological features, standing monuments, natural reserves, burial mounds, paleo-channels) and respective scientific research objectives are presented: the Ostia-Portus area and the wider Province of Rome (Italy), the city of Wuhan and the Jiuzhaigou National Park (China), and the Siberian “Valley of the Kings” (Russia). Input data encompass both archive and newly tasked medium to very high-resolution imagery acquired over the last decade from satellite (e.g. Copernicus Sentinels and ESA Third Party Missions) and aerial (e.g. Unmanned Aerial Vehicles, UAV) platforms, as well as field-based evidence and ground truth, auxiliary topographic data, Digital Elevation Models (DEM), and monitoring data from geodetic campaigns and networks. The novel results achieved for the use-cases contribute to the discussion on the advantages and limitations of optical and SAR-based archaeological and heritage applications aimed to detect buried and sub-surface archaeological assets across rural and semi-vegetated landscapes, identify threats to cultural heritage assets due to ground instability and urban development in large metropolises, and monitor post-disaster impacts in natural reserves

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

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

Automated detection of archaeological mounds using machine-learning classification of multisensor and multitemporal satellite data.

This paper presents an innovative multisensor, multitemporal machine-learning approach using remote sensing big data for the detection of archaeological mounds in Cholistan (Pakistan). The Cholistan Desert presents one of the largest concentrations of Indus Civilization sites (from ca 3300 to 1500 BC). Cholistan has figured prominently in theories about changes in water availability, the rise and decline of the Indus Civilization, and the transformation of fertile monsoonal alluvial plains into an extremely arid margin. This paper implements a multisensor, multitemporal machine-learning approach for the remote detection of archaeological mounds. A classifier algorithm that employs a large-scale collection of synthetic-aperture radar and multispectral images has been implemented in Google Earth Engine, resulting in an accurate probability map for mound-like signatures across an area that covers ca 36,000 km2 The results show that the area presents many more archaeological mounds than previously recorded, extending south and east into the desert, which has major implications for understanding the archaeological significance of the region. The detection of small (30 ha) suggests that there were continuous shifts in settlement location. These shifts are likely to reflect responses to a dynamic and changing hydrological network and the influence of the progressive northward advance of the desert in a long-term process that culminated in the abandonment of much of the settled area during the Late Harappan period.ER

D6.6: 7 conference papers

The Deliverable 6.6 with the title “7 conference papers”, is part of WP6 “Dissemination and Exploitation” of Athena project with a basic aim to knowledge sharing, network development and exposure to an international environment. Three conference attendances were foreseen (e.g. CAA; SPIE; EARSeL) within the project duration whereas more than 30 posters and oral presentations were presented during the project in the conferences such as: SPIE 2016, SPIE 2018, EUROMED 2016, EUROMED 2018, EGU 2016, EGU 2017, EGU 2018, RSCy2016, RSCy 2017, RSCy 2018, etc

New technologies for the conservation and preservation of cultural heritage through a bibliometric analysis

Versión aceptadaPurpose This study aims to analyze the impact of Artificial Intelligence (AI) and Machine Learning (ML) on heritage conservation and preservation, and to identify relevant future research trends, by applying scientometrics. Design/methodology/approach A total of 1646 articles, published between 1985 and 2021, concerning research on the application of ML and AI in cultural heritage was collected from the Scopus database and analyzed using bibliometric methodologies. Findings Our findings have shown that although there is a very important increase in academic literature in relation to AI and ML, publications that specifically deal with these issues in relation to cultural heritage and its conservation and preservation are significantly limited. Originality/value This study enriches the academic outline by highlighting the limited literature in this context and therefore the need to advance the study of AI and ML as key elements that support heritage researchers and practitioners in conservation and preservation work.Project WARMEST - loW Altitude Remote sensing for the Monitoring of the state of cultural hEritage Sites: building an integrated model for maintenance, is an H2020 Marie Curie Research and Innovation Staff Mobility Project (H2020- Marie Skłodowska-Curie Actions-RISE-2017), online at https://warmestproject.eu

Earth Observation in the EMMENA Region: Scoping Review of Current Applications and Knowledge Gaps

Earth observation (EO) techniques have significantly evolved over time, covering a wide range of applications in different domains. The scope of this study is to review the research conducted on EO in the Eastern Mediterranean, Middle East, and North Africa (EMMENA) region and to identify the main knowledge gaps. We searched through the Web of Science database for papers published between 2018 and 2022 for EO studies in the EMMENA. We categorized the papers in the following thematic areas: atmosphere, water, agriculture, land, disaster risk reduction (DRR), cultural heritage, energy, marine safety and security (MSS), and big Earth data (BED); 6647 papers were found with the highest number of publications in the thematic areas of BED (27%) and land (22%). Most of the EMMENA countries are surrounded by sea, yet there was a very small number of studies on MSS (0.9% of total number of papers). This study detected a gap in fundamental research in the BED thematic area. Other future needs identified by this study are the limited availability of very high-resolution and near-real-time remote sensing data, the lack of harmonized methodologies and the need for further development of models, algorithms, early warning systems, and services

Integrated Remote Sensing to Assess Disease Control: Evidence from Flat Island Quarantine Station, Mauritius

This article presents an integrated approach used in archaeology and heritage studies to examine health and disease management during the colonial period in the Indian Ocean. Long-distance labor migrations had dire health consequences to both immigrants and host populations. Focusing on the quarantine station on Flat Island, Mauritius, this study analyzes a historical social setting and natural environment that were radically altered due to the implementation of health management. Using aerial and satellite imagery, digital elevation models, RTK and total station raw data, 3D modeling, and GIS mapping, we reconstructed the spatial organization and the built landscape of this institution to assess the gap between the benefits claimed by European colonizers and the actual effects on immigrant health conditions through the promotion of public health practice

The Cyrenaica Coastal Survey Project: documenting endangered maritime heritage in Libya

This paper introduces the Cyrenaica Coastal Survey (CCS), a collaborative project between the Maritime Endangered Archaeology project and the Department of Antiquities (DoA) Cyrenaica in partnership with the Universities of Al Bayda and Benghazi in Libya. Since the Arab Spring in 2011 and the subsequent civil unrest in Libya, heritage professionals, the DoA, and various individuals interested in heritage have struggled to safeguard heritage sites across the country, as policies and laws that protected archaeological sites were no longer reinforced and adhered to in the wake of the revolution. This lack of finances, capacity, and governmental support led to an unprecedented loss of archaeological sites since 2011. The CCS survey records the current condition of maritime sites along the Cyrenaican coast. The project focuses on the smaller, lesser known, coastal heritage sites that are not as well studied as the much larger classical period port towns of Apollonia, Tocra, or Ptolemais. This article will focus on the results of the first phase of the project between ancient Phycus (modern Zawiet el-Hamama) and Kainopolis (modern Al-Ogla). The results of the first stage of the Cyrenaica Coastal Survey provides a snapshot of the damages and threats that coastal heritage faces in Libya, most notably (often unregulated) building activities, clearance, sand mining, and coastal erosion. Furthermore, this article highlights the importance of remote collaboration between UK institutions, in-country partners, and heritage authorities, especially in countries where the discipline of maritime archaeology has been established more recently