CSTAAR - Computational Solutions for Terrestrial and Aquatic Archaeological Research Revenue

About CSTAAR - Computational Solutions for Terrestrial and Aquatic Archaeological Research

CSTAAR (Computational Solutions for Terrestrial and Aquatic Archaeological Research) CSTAAR is an independent research initiative focused on enhancing and streamlining digital workflows in archaeology through programming, computational tools, and emerging technologies. Mission CSTAAR aims to improve efficiency, reproducibility, and scalability of digital processes in archaeology by integrating: Data analysis and automation Earth Observation (EO) technologies Machine Learning (ML) and Deep Learning (DL) Digital documentation and 3D data processing Big data analysis and visualization The project addresses both terrestrial and underwater contexts, with a strong emphasis on methodological development and the creation of reusable, open-source tools. Areas of Focus Automation of archaeological workflows (e.g., digitization of analog documentation, data processing, GIS workflows) EO-based analysis for site detection and environmental context (Sentinel-2, EnMAP, LULC, Object/Site Detection, OBIA, SDB, seabed classification) Machine learning pipelines for pattern recognition and segmentation Big data processing and analysis of multispectral/hyperspectral, DEM, and geospatial datasets 3D documentation and interactive visualisation Communication and presentation of results using modern data viz methods Goals Enable archaeologists to adopt efficient, scalable, and transparent digital workflows Bridge the gap between traditional fieldwork and computational analysis Create an ecosystem of open-source tools and workflows that are well-documented and adaptable

View contact profiles from CSTAAR - Computational Solutions for Terrestrial and Aquatic Archaeological Research