Mapping endangered cultural soilscapes in post-conflict regions through Big Earth Observation Data, artificial intelligence and geoarchaeological signatures

Informazioni relative al progetto

SIGNATURE

ID dell’accordo di sovvenzione: 101067100

DOI

10.3030/101067100

Progetto chiuso

Data della firma CE 4 Luglio 2022

Data di avvio 1 Agosto 2023

Data di completamento 31 Luglio 2025

Finanziato da

• Marie Skłodowska-Curie Actions (MSCA)

Costo totale

Nessun dato

Contributo UE

€ 181 152,96

Coordinato da

Institut Català d'Arqueologia Clàssica
Spain

Periodic Reporting for period 1 - SIGNATURE (Mapping endangered cultural soilscapes in post-conflict regions through Big Earth Observation Data, artificial intelligence and geoarchaeological signatures)

Periodo di rendicontazione: 2023-08-01 al 2025-07-31

Sintesi del contesto e degli obiettivi generali del progetto

The SIGNATURE project has focused on preserving endangered cultural soilscapes—the long-term human imprint in landscapes—across the Levant, particularly in the fertile alluvial plains of Lebanon’s Beqaa Valley and the southern Jordan River Valley. These landscapes have been shaped by millennia of human activity but face increasing threats from climate change, desertification, erosion, modern agriculture, settlement expansion, and ongoing political instability.

SIGNATURE aimed to document, characterise, and protect these fragile heritage sites by combining archaeological legacy data, historical maps, and multi-temporal satellite imagery with geoarchaeological analysis and advanced computational workflows. By investigating anthropogenic soils and landscape changes, the project provides evidence to monitor vulnerable archaeological locations, understand past land-use practices, and inform sustainable heritage management policies.

Lavoro eseguito dall’inizio del progetto fino alla fine del periodo coperto dalla relazione e principali risultati finora ottenuti

SIGNATURE integrated legacy archaeological datasets, historical topographic maps, and remote sensing imagery from CORONA, HEXAGON, Sentinel, and Landsat satellites. Key achievements include:
Revising Leon Marfoe’s 1979 survey of the Beqaa Valley, identifying 119 mound-like archaeological sites, and geo-correcting 75 locations for further analysis.


Developing R and JavaScript codes for automated correction, analysis, and integration of multi-source Earth Observation data in cloud-based platforms such as Google Earth Engine.


Conducting field campaigns in Lebanon (2023) and Jordan (2024–2025) to validate remote sensing results, relocate and reassess archaeological mounds, and collect geoarchaeological samples.


Detecting long-term land-use patterns and distinctive anthropogenic soil signatures through multi-temporal analyses, enabling the identification of archaeological features even when they are eroded or partially destroyed.

Progressi oltre lo stato dell’arte e potenziale impatto previsto (incluso l’impatto socioeconomico e le implicazioni sociali più ampie del progetto fino ad ora)

SIGNATURE has advanced archaeological remote sensing by integrating multi-sensor and multi-temporal datasets to detect subtle geoarchaeological features and monitor endangered landscapes. Results demonstrate the potential of combined Earth Observation and soil analyses to identify and preserve fragile heritage assets in post-conflict and semi-arid regions.

The project has established three international collaborations with the Directorate of Antiquities of Lebanon, the Department of Antiquities of Jordan, and the EAMENA project (Universities of Oxford and Durham, UK). These partnerships facilitate future joint field surveys and capacity-building in post-conflict regions.

Fieldwork and geoarchaeological sampling of tell archaeological sites in the Jordan River Valley.

Risk assessment of Leon Marfoe’s (1970s) tell locations in the Beqaa Valley, Lebanon, identifying ma

MODIS multitemporal soil signatures (EVI spectral index, yearly average for 2010-2023) showing mound

Reassessment of Leon Marfoe’s (1970s) tell locations in the Beqaa Valley, Lebanon, using geospatial