The paper’s goals is to present the EU-funded project “UnderTheSands: Ancient irrigation detection and analysis using advanced remote sensing methods” (HORIZON-MSCA-2021-PF-01-101062705).   

UnderTheSands aims to identify irrigation networks and examine their temporal dynamics using four study areas in Turkmenistan, Iran, and Iraq. The project aims to apply BigData in archaeological research via Google Earth Engine (GEE) cloud computing environment and FAIR research principles. Remote sensing, terrain analysis, hybrid machine learning and deep learning techniques, archaeomorphology, spatial correlation indices, historical research, and other spatial data sources are all part of the project’s methodology.  

An extended battery of satellite-based datasets will be employed including Sentinel 2 multispectral imagery and Sentinel 1 synthetic aperture radar. On top of that, we will use TanDEM-X data, which will allow us to achieve an excellent spatial resolution and improve the reconstruction of the irrigation network. Due to the diversified environmental characteristics of the areas chosen, we will create a novel workflow for the extensive analysis of irrigation networks. This workflow can then be applied to any other region with resembling traits.   

The paper will outline the project objectives and discuss the research issues on ancient irrigation we encountered during the project’s first year. The preliminary results of remote sensing and terrain micro-relief analysis will be presented.