Remote sensing of hydrothermal alteration in active volcanic environments: A critical review and integrated analysis of Lastarria volcano

Hydrothermal alteration is a key process in active volcanic systems, influencing edifice stability, fluid circulation, degassing pathways, and volcanic hazards. Remote sensing is widely used to map hydrothermal alteration; however, many approaches treat alteration-related surfaces as static targets, so their reliability, transferability, and process significance in active volcanic environments remain insufficiently evaluated. This study synthesizes commonly used remote sensing approaches and examines the behavior and interpretive implications of representative outputs at Lastarria volcano, which is an arid, high-altitude, vegetation-free system with active fumarolic fields. We compare visual interpretation, VNIR-SWIR reflectance products, pixel-based and sub-pixel mapping outputs, UAV thermal infrared observations, and LiDAR-derived surface-state information. The results show that visual interpretation, reflectance-based products, and pixel-based or sub-pixel outputs delineate broad alteration-related patterns, but their extent, internal structure, and interpretive meaning vary with methodological choices, surface mixing, and environmental surface states. Thermal infrared observations constrain apparent surface-temperature anomalies and fumarole-proximal activity, whereas LiDAR-derived products provide complementary information on surface state, morphology, and roughness. These observations do not converge on a single alteration representation; instead, they capture different aspects of the volcanic-hydrothermal system. Environmental, climatic, and surface controls, including exposure state, moisture, surface reworking, and seasonality, further limit direct transferability among volcanic settings. We suggest that remote sensing of hydrothermal alteration in active volcanic environments should move from deterministic mapping toward process-oriented and uncertainty-aware interpretation, with temporal persistence, spatial coherence, process plausibility, and independent support providing a basis for future multi-temporal analysis and monitoring.