GIAP expands the team on Remote Sensing and Archaeobotany!

This month, GIAP (ICAC) welcomed two new postdoctoral researchers to the team! We are very glad to present Patricia Vandorpe and Pangambam Sendash Singh, who will be working with us until 2024:

Patricia Vandorpe

Dr. Vandorpe completed her PhD in 2010 at the University of Basel (Switzerland), where she has since worked as a research associate. Her main research interests are plant economy and environment in Roman times as well as methodological issues in archaeobotany. After her PhD she conducted several smaller research projects such as combining the study of seeds and fruits with other proxy data (pollen analysis and ancient DNA) as well as a larger research project focusing on vegetable offerings in Roman cremation graves in Switzerland. In her current position, Patricia carries out archaeobotanical research from all time periods mainly from Switzerland.

PlantNetGem: Exploring the process of urbanisation in the Roman provinces of Germania through the study of food plant commerce (HORIZON-MSCA-2021-PF-01-101063192)
1 November 2022 – 31 October 2024

The arrival of the Romans in large parts of current Europe had a major impact on society, with the creation of a new transport network and the development of cities being two of the most significant and lasting changes. However, so far, little work has been done to quantify and understand their connection, how this developed and its lasting consequences. 

Through the study of imported/introduced food plants into the provinces of Germania in the Roman period, PlantNetGem aims to contribute to a better understanding of foodways and the role of transport and commerce in the development of the population nuclei in this area. It will apply a novel, interdisciplinary approach, combining archaeobotany, computational archaeology and data science through practical training by the supervisory team that pioneered part of the proposed methodology. The project will start by creating a geodatabase where archaeobotanical and archaeological information from the study area will be stored. 

These will provide the analytical basis to identify which food plants arrived and when, who had access to these and the reasons why. Network science will be applied to reconstruct settlement connectivity in relation to a) their access to the introduced food plants, and b) their position within and access to the Roman transport network. 

Agent-Based Modelling and statistical analyses will be applied to further allow testing hypotheses concerning settlement position and hierarchy in relation to commerce to ultimately evaluate the role of the ancient transport network in the distribution and importance of urban centres and analyse to which degree these patterns have endured in time up to the modern period. PlantNetGem builds upon the candidate’s solid expertise and involves training on big data management, network analysis, agent based modelling and associated geostatistical analysis.

Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Executive Agency (REA). Neither the European Union nor the granting authority can be held responsible for them.

 Pangambam Sendash Singh

Dr. Pangambam Sendash Singh (Ph.D.) is a postdoctoral researcher in the Landscape Archeology research group (GIAP) of the ICAC. His research area includes Computational Intelligence, Deep Learning and its applications in Multispectral and Hyperspectral Image Analysis. He completed his Master’s and Ph.D. in Computer Science from Banaras Hindu University, India. His doctoral thesis focused on developing new machine learning based approaches to improve the performance of a few important hyperspectral imaging applications in diverse domains.

Full list of Publications:

Project abstract

Dr. Singh will investigate novel machine learning algorithms to automatically detect archaeological sites from the information available on data provided by different and complementary satellite sensors. Based on previous results in the topic of archaeological site detection (Orengo et al. 2020), this new development will update previous research with deep learning techniques, new sources of information, more scenarios, exhaustive validation and it will finally be deployed in a cloud infrastructure to disseminate these new tools among the archaeological community.

The context of this project is an ongoing collaboration between the Catalan Institute of Classical Archaeology (ICAC) at Tarragona and the Computer Vision Center (CVC-UAB) at Barcelona. The contract is linked to the project “Mapping Archaeological Heritage in South Asia” (MAHSA) funded by the Arcadia Fund and developed as a collaboration between the University of Cambridge (UCam), The University Pompeu Fabra (UPF) and the Catalan Institute of Classical Archaeology (ICAC). 

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