Comparative analysis of index-based and land cover-based C-factor estimation under wildfire disturbance in Western Greece

Wildfires are major disturbances in Mediterranean landscapes, significantly increasing soil erosion risk by removing protective vegetation cover and disrupting sediment regulation functions at the catchment scale. Regarding post-fire erosion risk, uncertainty remains in how different cover-management (C) factor estimation methods influence predicted soil loss. This study investigates the spatiotemporal variability of the C-factor following three major wildfire events (2007, 2022, and 2024) in the Pinios Dam drainage basin, Western Greece, by comparing static land cover-based (CORINE) assignments and dynamic index-based (NDVI, EVI, PVI, SAVI) C-factor values. Burn severity was assessed using the differenced Normalized Burn Ratio (dNBR) while RUSLE factors R, K, LS, and P were held constant to isolate the sensitivity of alternative C-factor formulations under controlled baseline conditions. All methods showed post-fire increase in C-factor values, with the 2007 wildfire showing the most severe impacts. NDVI-based C-factor estimates demonstrated the strongest response to vegetation loss, EVI- and PVI-based estimates also captured post-fire changes but more conservatively, while SAVI-based estimates were consistently higher but less variable. In contrast, land cover-based estimates reflected the general pattern of post-fire vegetation cover reduction but failed to represent the spatial variability associated with differing burn severity. By linking C-factor behavior to burn severity gradients and quantifying the resulting differences in predicted soil loss, this study provides a comparative evaluation of the sensitivity of commonly used vegetation indices for post-fire change detection, a methodological evaluation of static versus dynamic C-factor representations, and a transferable cloud-based workflow for post-fire erosion assessment in Mediterranean environments. • Impact of three major wildfires on soil erosion was quantified using burn severity and multiple C-factor methods in RUSLE model. • Pre- and post-fire land cover-based (CORINE) C-factors were compared with dynamic index-based C-factors derived from NDVI, EVI, PVI and SAVI. • Index-based C-factors exhibit stronger responsiveness to burn severity gradients and spatio-temporal variability of C-factor than land cover-based method. • Propose an adaptable remote-sensing and cloud-based framework for C-factor estimates that enables robust post-fire erosion assessment.