Permafrost is a key indicator of global climate change and hence considered an Essential Climate Variable. Current studies show a warming trend of permafrost globally, which induces widespread permafrost thaw, leading to near-surface permafrost loss at local to regional scales and impacting ecosystems, hydrological systems, greenhouse gas emissions, and infrastructure stability. Permafrost thaw can unfold slowly from gradual top-down thawing and deepening of the active layer but also rapidly from abrupt thawing of ice-rich permafrost, involving processes such as thermokarst formation, lake drainage, retrogressive thaw slumps and coastal erosion. Many of these processes impact landscapes irreversibly, while posing a particular threat to infrastructure and livelihoods of people in the Arctic. Permafrost is defined as the thermal state of the subsurface, hence Earth Observation methods have limitations in assessing permafrost directly. However, the state of the subsurface is strongly connected to surface conditions and influenced by changes in the atmosphere, biosphere, geosphere, and cryosphere. Therefore, examining changes in the surface state will help identify local to regional trends and impacts on the thermal state of permafrost. Hence, the aim of this study in progress is to investigate changes in the surface state by assessing potential positive and negative trends in variables impacting permafrost and thus identifying areas that are vulnerable to permafrost thaw by developing a permafrost vulnerability framework using a comparative index. EO-based datasets provide relevant variables impacting the surface state and obtain trends and changes from homogenised long-term datasets. These globally available datasets include land surface temperature, land cover, snow cover, fire, albedo, soil moisture, and information on the freeze/thaw state, which are ECVs too. Furthermore, a modelled permafrost_cci product is available from the ESA CCI+ Permafrost project, which reveals changes and trends in ground temperature and active layer thickness for the last two decades and serves as link between modelled and EO-based permafrost thaw assessments. So far, a combined assessment of all these permafrost-relevant products to better understand, quantify, and project permafrost thaw and its potential trajectories is still missing. We conducted spatiotemporal variability and decadal trend analyses of all the individual ECVs for the panarctic permafrost region and identified statistically significant positive and negative feedbacks. The first individual results show interesting spatially different trends in the panarctic, for example that the snow water equivalent increased in eastern Yakutia and Chukotka in Russia and in the same time period decreased in most parts of Alaska. In a next step, we will combine the positive and negative feedbacks in a vulnerability framework, reflecting the impact they pose on permafrost. This will help to identify prevailing regional trends in the surface state not only from individual variables but their coupled feedback on the thermal state of the permafrost. Our EO-based assessment of permafrost vulnerability uses existing and available datasets to further improve our understanding on permafrost thaw in the near future. It will build a foundation for a wide range of studies focusing on permafrost-thaw and its impacts, such as hydrological change, infrastructure stability, ecosystem change, or greenhouse gas emissions.