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

作者:Chen, W (Chen, Wei)[ 1,2 ] ; Jiang, HZ (Jiang, Houzhi)[ 1 ] ; Moriya, K (Moriya, Kazuyuki)[ 2 ] ; Sakai, T (Sakai, Tetsuro)[ 2 ] ; Cao, CX (Cao, Chunxiang)[ 1 ]

NEW FORESTS

卷: 49  期: 1  页: 105-121

DOI: 10.1007/s11056-017-9608-2

出版年: JAN 2018

摘要

Post-fire forest regeneration is crucial to forest management. Three different restoration treatments including 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 is a control treatment where recovery occurs naturally without intervention, AR comprises salvage logging followed by planting, while AP includes regeneration by removing dead trees, weeding, and tidying to promote seed germination. In this study, the objective was to detect and compare the effects of the three restoration treatments using radar indices derived from ALOS/PALSAR data. Four time-series SAR 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 compared to those under the other two treatments. This difference could be characterized by both the backscattering intensity in HH and HV polarization and two radar indices. This study indicated the effects of different restoration treatments, as well as demonstrated the applicability and efficiency of radar remote sensing techniques in forest monitoring and management.

通讯作者地址: Chen, W (通讯作者)

Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, POB 9718-13,Datun Rd, Beijing 100101, Peoples R China.

通讯作者地址: Chen, W (通讯作者)

Kyoto Univ, Grad Sch Informat, Dept Social Informat, Biosphere Informat Lab, Kyoto 6068501, Japan.

地址:

[ 1 ] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, POB 9718-13,Datun Rd, Beijing 100101, Peoples R China

[ 2 ] Kyoto Univ, Grad Sch Informat, Dept Social Informat, Biosphere Informat Lab, Kyoto 6068501, Japan