Multi-temporal Spectral Analysis to Quantify and Monitor Post-Wildfire Changes to Hillslope and Channel Topography

Abstract:

Post-wildfire sediment transport processes, such as channel scour, dry ravel, and rill/gully formation, can cause extensive modification to burned landscapes. While these processes contribute to large sediment fluxes, post-fire hazards, and wide-spread landscape change, they are difficult to quantify and monitor, because they 1) are highly variable in extent and magnitude and 2) often occur at relatively small spatial scales, on the order of centimeters to tens of meters. Spectral analysis provides a new tool for characterizing post-wildfire landscapes and landscape change by identifying spectral frequency signatures associated with topographic features. To demonstrate the usefulness of this tool for evaluating post-wildfire erosional changes, we present spectral analysis results for a multi-temporal, terrestrial LiDAR dataset from a basin burned in 2011 by the Horseshoe 2 Fire in the Chiricahua Mountains, Arizona. We present interpretation of spectral signatures, observations of landscape changes through time, comparisons of rates of landscape change between hillslope and channel areas, and discussion of implications for post-wildfire processes in the basin.