Monitoring of post-fire forest recovery under different restoration treatments based on time-series ALOS/PALSAR data

Post-fire forest regeneration is crucial to both ecological studies and forest management. Three restoration treatments, namely natural regeneration (NR), artificial regeneration (AR), and artificial promotion (AP), were adopted in the Greater Hinggan Mountain area of China after a serious fire occurred on May 6, 1987. NR means recovering naturally without any intervention, AR comprises salvage logging followed by complete planting, while AP includes regeneration by removing dead trees, weeding, and digging some pits to promote seed germination. The objective of this study was to detect and compare the effects of the three restoration treatments based on ALOS/PALSAR data. The four PALSAR images were pre-processed to acquire the backscattering coefficients. Then the coefficients in both HH and HV polarization were examined and two radar vegetation indices were derived and evaluated, based on which, the post-fire forest dynamics under different restoration treatments were detected and compared. The results showed that the forests under NR presented a completely different recovery trajectory with those under the other two treatments. This study indicated the effects of different restoration treatments, as well as demonstrated the applicability and efficiency of SAR techniques in forest monitoring and post-fire management.