Multi-Source Remote Sensing Data Reveal the Instability Evolution and Precursory Signals Before the Collapse of the Aru Glaciers on the Tibetan Plateau

Glacier collapse hazard events on the Tibetan Plateau have attracted increasing attention, and previous studies have documented substantial pre-collapse changes in the Aru glaciers, including dynamic acceleration, crevasse development, and glacier thickening. However, the relative effectiveness and temporal behavior of different remote sensing indicators for identifying collapse-related precursory signals have not been systematically compared within a common framework. Here, multi-source remote sensing datasets spanning 1990–2016 were integrated to compare glacier geometry, surface elevation change, glacier surface velocity (GSV), surface albedo, glacier surface temperature (GST), and Sentinel-1 SAR backscatter before the 2016 collapses of Aru 53 and Aru 50. Anomalies were quantified using standardized Z-scores, with |Z| > 1.96 and |Z| > 2.57 representing anomalous and strongly anomalous conditions, respectively. Both glaciers experienced upstream surface lowering and downstream thickening, followed by pronounced GSV acceleration toward collapse, consistent with previously reported dynamic and mass-redistribution changes. In contrast, surface albedo and GST exhibited long-term variations broadly consistent with regional climatic conditions but lacked distinctive collapse-related anomalies. Sentinel-1 observations revealed a contrasting response between the two glaciers: Aru 53 showed a progressive increase in σ0, reaching 0.70 dB at the glacier-wide scale and 1.15 dB within the collapse zone, whereas Aru 50 exhibited only limited changes. The spatial concentration of enhanced σ0 in Aru 53 coincided with areas of rapid crevasse development, suggesting that SAR backscatter provides complementary information on localized surface structural degradation. Overall, the comparison demonstrates distinct diagnostic sensitivities among remote sensing indicators: elevation redistribution and GSV acceleration characterize mass transport and dynamic instability, whereas SAR backscatter can provide additional information on localized surface structural degradation. These results support the use of indicator-specific anomaly responses rather than a single universal precursor criterion for assessing glacier instability.