In a new groundbreaking study, multiple computational methods are integrated for the first time in a single research to map historical hydrological networks and identify new archaeological sites in the Indus River basin, achieving unprecedented detail.
Alluvial floodplains have played a significant role in the development and transformation of urban agrarian-based societies. The interaction between human societies and riverine environments has left behind a valuable archaeological record. However, accessing this record can be challenging due to the dynamic nature of alluvial floodplains and the hydrological processes that shaped them. Additionally, these floodplains are often targeted for urban and agricultural expansion, posing risks to both cultural heritage and the environment if not managed carefully.
To address these challenges, a new study combines historical cartography and remote sensing techniques to identify potential archaeological sites and river palaeochannels. This approach is crucial in reconstructing settlement patterns across different historical periods and understanding their relationship with hydrological networks.
Various computational methods, including algorithms and machine learning-based approaches developed at GIAP (ICAC), have been employed effectively in this research. These methods enhance the visualization of different landscape features and process large amounts of data. For the first time, these methods have been integrated into a single study focused on a section of the Indus River basin.
Through this integrated approach, researchers have been able to map the historical hydrological network with unprecedented detail. Furthermore, they have identified numerous potential archaeological sites that were previously unknown (see featured image at the top of the article). By analyzing these datasets and combining them with existing field-based research, the study sheds light on the interpretation of the archaeological record. It also demonstrates how remote sensing approaches can inform future research, heritage documentation, management, and preservation efforts.
The targeted analysis of the datasets, in conjunction with previous field-based research, reveals preliminary insights into the impact of long-term processes on historical landscapes and their significance for studying settlement patterns across various historical periods. The integrated approach, encompassing historical cartography, remote sensing, and computational methods, showcases its potential to advance archaeological research.
Full reference:
Garcia-Molsosa, A., Orengo, H.A. & Petrie, C.A. Reconstructing long-term settlement histories on complex alluvial floodplains by integrating historical map analysis and remote-sensing: an archaeological analysis of the landscape of the Indus River Basin. Herit Sci 11, 141 (2023). https://doi.org/10.1186/s40494-023-00985-6
Funding:
Arnau Garcia-Molsosa is Ramón y Cajal Fellow (Funded by the Spanish Ministry of Science, contract RYC2021-034341-I) at the Catalan Institute of Classical Archaeology. Hèctor A. Orengo is an ICREA Research Professor at the Catalan Institute of Classical Archaeology. Cameron A. Petrie is Professor of South Asian and Iranian Archaeology at the University of Cambridge. The research presented here was developed in the context of the Maria Skłodowska-Curie Action WaMStrIn project (MSCA grant agreement No. 746446).
Work on the SoI maps from Haryana in India was carried out as part of the Land, Water and Settlement and TwoRains projects (funded by the ERC under the European Union’s Horizon 2020 research and innovation programme, grant agreement 648609).
This research and the writing of the paper continued with funding from the UKRI’s Global Challenges Research Fund’s TIGR2ESS project (BB/P027970/1). These were both collaborative endeavours involving researchers from the University of Cambridge and the Department of AIHC and Archaeology at Banaras Hindu University, under the direction of Prof. Petrie and Prof. R. N. Singh.
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 REA can be held responsible for them.
