Descrizione del progetto
Reprimere le razzie dei siti archeologici
L’impennata di scavi illegali nei siti archeologici e il conseguente traffico di oggetti antichi, che rappresenta un’industria da diversi miliardi di euro, hanno preso piede in concomitanza, ad esempio, dei tumulti in Medio Oriente. Inoltre, il saccheggio dei siti archeologici è peggiorato durante la pandemia di COVID-19. Il progetto OPTIMAL, finanziato dall’UE, realizzerà un mezzo automatico di individuazione delle attività di saccheggio, sfruttando un approccio di apprendimento automatico basato sul trasporto ottimale per il rilevamento automatico di razzie presenti e passate direttamente sulle serie temporali dei LiDAR aerei. Inoltre, il progetto metterà insieme una serie di dati LiDAR rendendoli disponibili al pubblico, affinché vengano utilizzati gratuitamente per il rilevamento di attività illegali.
Obiettivo
"Illegal excavation of archaeological sites aimed at collecting historical material culture (""looting"") is a pressing problem on a global scale. The global upsurge of in the illegal excavation of cultural heritage sites (e.g. in connection to turmoils in Middle East or due to the impossibility of monitoring inaccessible areas, like in South America) and the subsequent trafficking of antiquities, exacerbated by the Covid lockdown, calls for the timely development of automatic means for identifying looting activities. The OPTIMAL (OPtimal Transport for Identifying Marauder Activities on LiDAR) project aims to tackle this challenge by developing an efficient and principled Machine Learning (ML) approach based on Optimal Transport to automatically detect looting (past and present) directly on airborne Light Detection And Ranging (LiDAR) point cloud time-series. OPTIMAL proposes, for the first time, the use of LiDAR for monitoring and assessing the damages of looting based on LiDAR’s unique ability to penetrate forest canopies and enabling to see a range of looting-related features under the canopy (e.g. shape and depth of the lootings pits) that otherwise would remain hidden due to vegetation covers. OPTIMAL will create and make publicly available the first multi-temporal LiDAR dataset for illegal activities’ identification to foster the interest of MLs researchers in developing new methods to tackle challenges in landscape archaeology and to evaluate the developed ML approach. Results of this interdisciplinary research will be widely disseminated within Cultural Heritage, Remote Sensing and Machine Learning communities and to others that can exploit OPTIMAL’s results. A communication strategy will be designed to ignite enthusiasm for technological advancements for the protection of our Heritage."
Campo scientifico
- natural sciencescomputer and information sciencesartificial intelligencecomputer vision
- engineering and technologyenvironmental engineeringremote sensing
- humanitieshistory and archaeologyarchaeology
- natural sciencesmathematicsapplied mathematicsstatistics and probability
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Parole chiave
Programma(i)
Argomento(i)
Meccanismo di finanziamento
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)Coordinatore
16163 Genova
Italia