YANG Chen, SHEN Runping, YU Dawei, et al. Forest disturbance monitoring based on the time-series trajectory of remote sensing index[J]. Journal of Remote Sensing, 2013,17(5):1246-1263.
YANG Chen, SHEN Runping, YU Dawei, et al. Forest disturbance monitoring based on the time-series trajectory of remote sensing index[J]. Journal of Remote Sensing, 2013,17(5):1246-1263. DOI: 10.11834/jrs.20132308.
which are major parts of the terrestrial biosphere
play an important role in terrestrial carbon cycling and storage. However
the accuracy of forest carbon-flux estimation is greatly influenced by the lack of forest disturbance data. Thus
we conduct a study in Wuning County in Southern China by adopting a time-series trajectory analysis technique to detect forest disturbances in 14 Landsat Thematic Mapper / Enhanced Thematic Mapper Plus images from 1986 to 2011. This technique not only identifies forest disturbance
but also provides vegetation recovery information. By analyzing the time-space disturbance characteristics of forest disturbance
we found that Wuning County has suffered from a significantly dramatic disturbance in the 1990s
most of which has occurred in low-elevation areas because of human activities. Compared with field observations
the Kappa coefficient of our disturbance products reaches 0. 80 with an overall accuracy of 89. 7%
thus indicating the significant potential of the technique for forest disturbance monitoring.