The presentation abstract from Archaeo-Informatics 2024.

The Digital Elevation Model (DEM) is one of the core components of spatial analysis. And particularly historical or ancient topographical models are long-desired datasets for interpreting the archaeological contexts more accurately. The researchers have used topographical data collection, geo-radar, LiDAR, and remote sensing techniques to reconstruct coherent terrain models. However, it is questionable that these techniques are feasible for wider areas or projects with limited budgets. Nowadays, machine learning (ML) and computer-vision-assisted spatial analysis tools bring us new possibilities for this topic. The open-source tools like HEXIMAP (HEXagon IMagery Automated Pipeline) via OpenCV libraries allow us to generate 1970s topographical models from US Hexagon (KH-9) imageries. Thus, we aim to discuss the historical DEM generation methods in terms of their feasibility, interoperability, and sustainability for archaeological studies.

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