Understanding and monitoring the dynamics of Arctic permafrost regions under climate change using EO & cloud computing: the contribution of EO-PERSIST project

• Main Authors: Petropoulos, George P., Karathanassi, Vassilia, Karamvasis, Kleanthis, Detsikas, Spyridon E., Dermosinoglou, Aikaterini
• Format: Book Part
• Language: unknown
• Published: Zenodo 2024
• Subjects: Arctic; Climate change; Global warming; permafrost
• Online Access: https://doi.org/10.5281/zenodo.11380235

Given the increasing challenges presented by climate change, understanding and monitoring the dynamics of permafrost regions in the Arctic have gained paramount importance. Permafrost, acritical component of the Arctic ecosystem, is highly susceptible to the effects of global warming,exerting profound impacts on both environmental and socioeconomic facets. In purview of it, the EO-PERSIST project is a 4 years MSCA staff exchanges project funded by EU aiming to leverage existing services, datasets, and innovative technologies to establish a consistently updated ecosystem with Earth Observation (EO)-based datasets suitable for permafrost applications. By harnessing advanced EO technologies, including innovative tools and datasets such as cloud platforms, and tapping into an extensive array of remote sensing datasets, EO-PERSIST aims to revolutionize the monitoring and assessment of permafrost dynamics. The project will promote methodological advancements in the field of permafrost by leveraging the huge volume of remote sensing (RS) datasets and providing indicators directly liked to socioeconomic effects from permafrost dynamics. EO-PERSIST will perform experimental analysis through five use cases, which will also serve as Key Performance Indicators (KPIs) of the system. As such, EO-PERSIST will establish a fertile environment for staff exchanges knowledge sharing, and know-how transfer. The present chapter aims to provide an overview of the project, introducing the project objectives in the context of the current state of the art. Furthermore, it offers an overview of the EO datasets suitable for use in permafrost studies in the Arctic region and it underlines the added value of cloud platforms and EO technology in this context. Finally, it addresses key societal challenges today linked to the study of socioeconomic impacts particularly in the European Arctic and it closes providing a vision of the expected contribution of the project to science and society.