International Journal of Applied Earth Observations and Geoinformation (Aug 2023)
Using Landsat time series and bi-temporal GEDI to compare spectral and structural vegetation responses after fire
Abstract
Passive and active spaceborne remote sensing technologies play a key role in monitoring forests across large areas, particularly when combining the advantages of both sensor technologies. This study investigates the link between spectral and structural change metrics following forest fire disturbance, collected from Landsat satellites and the Global Ecosystem Dynamics Investigation (GEDI) mission, respectively. The relationships were analysed across 1849 GEDI sampling locations (footprints), spread across south-east Australian forests. To assess structural change on the footprint level, simulated pre-fire GEDI observations were compared with real GEDI observations from one year after the fires. Results show relatively strong fire responses across Landsat spectral indices, with a median decline to between 46.1 % (Normalised Burn Ratio 2) and 77 % (Normalised Difference Vegetation Index) of pre-fire levels. GEDI’s structural change metrics demonstrated a markedly different response, with most showing an even more pronounced decline. In contrast, canopy height demonstrated a less substantial decline, dropping to 82.7 %. Results also suggest that fire severity and forest type impact the fire response of some of the examined spectral and structural metrics. In particular, taller forests and increased fire severity were associated with a more pronounced post-fire decline. The findings of this study highlight the large variation of forest structural responses to fire and their divergence from spectral change metrics, and emphasise the potential of integrating GEDI observations into wall-to-wall spectral forest change monitoring. The concept of bi-temporal GEDI observations as demonstrated in this study is promising, as it captures both pre- and post-disturbance structure on the footprint level and might enhance modelling of forest structural change in future approaches.
