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In recent years, in situ monitoring of rock glacier displacement has become more challenging. Unstable slopes, higher probability of gravitational movement due to destabilization processes and rock fall are negatively impacting the accessibility of research sites. To maintain long-term time series, current monitoring techniques need to be adapted.One example of a research site affected by this is Äußeres Hochebenkar rock glacier (46°50'0"N, 11°0'30"E, Ötztal Alps, Austria). The rock glacier has been subject to velocity measurements since 1938, making it one of the longest time series worldwide. Differential Global Navigation Satellite System (dGNSS) measurements are carried out since 2007. Aside minor data gaps, velocity data have been available at annual resolution since 1997 from four cross sections and a longitudinal profile. Each profile consists of 6 to 12 individual block positions.For the majority of the time series, the flow velocity was hardly more than 1 m/a on average. Since 2018, an exponential increase of rock glacier motion has been observed in the lowest section, showing the destabilization of this part of the rock glacier. During the last three years, maximum displacement values at individual blocks increased from 20 m/a to almost 50 m/a in 2024 and 75 m/a in 2025.Accessing the block profiles in the destabilized section to carry out dGNESS measurements has become challenging. To ensure the continuity of the time-series, UAV surveys have been incorporated in the monitoring program. In 2024 and 2025, multitemporal optical imagery was acquired in addition to dGNSS data. High-resolution othormosaics and digital elevation models were derived from the UAV imagery using Structure-from-Motion (SfM) photogrammetry techniques. This enables the calculation of spatially distributed displacement vectors over the whole rock glacier from multitemporal hillshades using image correlation algorithms and provides alternative observations of block displacement.We present the displacement rates for the years 2024 and 2025 using the most recent workflow, comparing displacement rates from dGNSS measurements with those derived from mapping on high-resolution orthomosaics and image correlation of multitemporal hillshades. We show how dGNSS displacement can be complemented by and compared to UAV-based methods. We try to address the opportunities and uncertainties lying within these approaches for mountain landforms that are reacting quickly to environmental changes, assuming that more and more comparable cases will arise under current and future climatic conditions in high mountain regions.