Evaluating Spatiotemporal Patterns of Post-Eruption Vegetation Recovery at Unzen Volcano, Japan, from Landsat Time Series

Abstract

Quantifying vegetation responses after natural disasters helps clarify complex relationships between vegetation and surface processes such as soil erosion. The heterogenous post-disaster landscape offers a naturally stratified environment for this study. Existing research tends to be frequently monitored but small-scale or sporadically monitored but large-scale. The availability of high-quality and free satellite imagery bridges this gap by offering continuous, longer-term observations at the landscape scale. Here we take advantage of a dense Landsat time series to investigate landscape-scale vegetation response rates and factors at Unzen volcano, Japan. We do this by first investigating differences between two popular vegetation indices—The Normalized Difference Vegetation Index (NDVI) and the Normalized Burn Ratio (NBR), when applied to recovery studies. We then apply pixel-wise regressions to quantify spatio-temporal vegetation response and regression tree analyses to investigate drivers of recovery. Our findings showed that simple linear-log functions best model recovery rates reflecting primary succession trajectories caused by extreme disturbance and damage. Regression tree analyses showed that despite secondary disturbances, vegetation recovery in both the short and long-term is still dominated by eruption disturbance type and elevation. Finally, compared to NDVI, NBR is a better indicator of structural vegetation regrowth for the early years of revegetation.

Keywords

• Landsat
• revegetation
• landscape disturbance
• vegetation indices
• GIS
• Unzen volcano