Alpine snowpack dynamics are crucial to hydropower generation, irrigation, winter tourism, and avalanche and flood forecasting. The ability to predict snowpack fluctuations is essential for ensuring economic stability and public safety in both alpine and downstream regions. However, current snowpack monitoring techniques are labor-intensive and provide only sparse, large-scale data, which limits the capacity to capture rapid and localized changes. This poses a significant challenge in addressing key operational needs. Cryospheric scientists have therefore identified the collection of spatiotemporal data on snowpack variability, particularly along elevation gradients, as a top research priority. The overall aim of the CABLE-SENS3 project is thus to develop an innovative snowpack monitoring system that addresses these challenges. The project proposes to use passive RFID tags, combined with an aerial RFID reader mounted on a cable car, to continuously monitor snowpack properties across large elevation gradients. This approach offers a breakthrough by merging high-resolution spatial and temporal data—something current methods cannot achieve simultaneously. Additionally, the proposed system is non-invasive, overcoming the limitations of traditional methods that rely on low-frequency or intrusive measurements. Incorporating technologies such as photogrammetry and microwave geophysics will enable the system to measure variables like snow water equivalent (SWE), liquid water content (LWC), and snow depth. By deploying RFID tags across large, often inaccessible areas, and conducting frequent aerial surveys, the project will generate unprecedented spatiotemporal data on snowpack dynamics. Such data will be invaluable to stakeholders such as hydropower companies, ski resorts, and avalanche safety services, who increasingly depend on data-driven decision-making. Moreover, the project will provide critical data to address many scientific questions related to the impacts of cli