Quantifying post-fire shifts in woody-vegetation cover composition in Mediterranean pine forests using Landsat time series and regression-based unmixing

Abstract

Mediterranean forests are highly subjected to fire occurrence. Altered fire regimes resulting from changes in land use and climate may jeopardize their resilience to fire and induce changes in forest composition. Disentangling forest cover composition is therefore critical for understanding post-fire forest recovery dynamics. In this study, we demonstrate how fractional time series of different woody-vegetation types support the analysis of post-fire vegetation recovery in relation to the pre-fire situation for two burned areas in Mediterranean pine forests in Spain. We separately estimated tree, shrub and background (combining herbaceous, soil and rock) cover fractions on an annual basis (1990–2020) using Landsat Spectral-Temporal Metrics (STMs) and a regression-based unmixing approach. Our regression models effectively estimated fractions of the three cover types with Mean Absolute Errors ranging from 8.6% to 13.4% when comparing to a reference dataset derived from high-resolution orthophotos across 6 different years. Slightly overestimations of low cover fractions where found in tree and shrub cover fractions across the study sites. Despite these minor errors, time series of cover fractions revealed characteristic spatio-temporal patterns of different woody-vegetation types for burned and unburned areas. Based on the fractional cover estimates, we derived a Normalized Difference Tree-Shrub Fraction index (NDTSF) to contrast tree cover fraction relative to the shrub cover and map post-fire shifts in composition. Annual maps of NDTSF revealed a high spatial and temporal variability and a general dynamic towards the pre-fire cover composition in 79–80% of burned areas but a shift from tree to shrub dominance in 12.3–15.4% 26 years after fire. Our regression-based unmixing approach advances the analysis of post-fire recovery dynamics, unravelling shifts in forest composition that are of major concern to forest management.