GPU-based pixel tracking of hillslope instabilities using multi-decadal optical satellite imagery in the Central Andes

The Central Andes are one of the most tectonically and geomorphologically active regions on Earth. The orographic barrier between the eastern foreland and the Central Andean plateau induces a strong East-West climatic gradient, with peak rainfall occurring on the steep eastward-facing slopes. Frequent rainstorms during the South American summer monsoon, coupled with fault-weakened lithologies, drive mass-movement processes including landslides and high-altitude periglacial creep. However, monitoring these instabilities over large areas and long time periods remains computationally expensive using traditional CPU-based methods.

We implemented a high-performance GPU-based workflow using sub-pixel optical image correlation to process 20-year time series using the Landsat 7, 8, and 9 data archive spanning from 22° to 27° S (12 Path/Row combinations) . The workflow consists of two main steps: (1) identification of areas of interest by oversampling the scenes before correlation at a coarse, but sufficiently dense step size, and (2) sub-pixel matching for refined displacement derivation within the detected regions. To ensure data integrity, we employ a pair selection process based on sun-elevation geometry and filters for cloud cover, snow, vegetation changes, and topographic shadows. Additionally, we applied a kinematic filter to exclude displacements inconsistent with hillslope aspect. By stacking multi-decadal imagery, we improved the signal-to-noise ratio and successfully detected velocities ranging from less than 0.5 m/yr to several meters per year. Our results highlight the extent of permafrost processes and the influence of the East-West climatic gradient on hillslope dynamics by capturing the transition from the humid foreland to the arid high-elevation plateaus. The stacking method effectively removed outlier signals caused by transient snow cover at higher elevations.

This 20-year record provides a vital baseline for understanding how Andean hillslope processes respond to a changing climate and how they depend on pre-existing, weakened lithologic conditions related to tectonic stresses. The GPU-accelerated framework enables a transition from localized monitoring to large-scale kinematic analysis in high-relief terrains.