Forest management practices and policies exert strong impacts on the spatio-temporal variations of forest disturbance in Hunan Province, China over the last three decades

Forest disturbance has a profound impact on the ecological function of forests. Although there are already global forest disturbance products, how accurate and whether they can be further improved remains to be seen. Moreover, due to the scarcity of disturbance characteristics (location, size, severity) data, the uncertainty of carbon estimation and the bottleneck of sustainable forest management are formed. In this study, Hunan was used as the research area to explore the most suitable detection methods for subtropical forest disturbance. We used the LandTrendr algorithm to generate a forest disturbance dataset from 1991 to 2021 and analyzed their spatio-temporal variation and disturbance characteristics. The overall accuracy of forest disturbance monitoring in Hunan Province was 86.39%, which was higher than that of Global Forest Change (GFC) products (82.89%). A total of 11103.25 km2 of forest has been disturbed in Hunan Province over the past 30 years, which represents 10.54% of the total forest area. Over the period 1991-2021, the disturbance area generally increased first and then decreased but varies greatly across regions. The maximum disturbance rate of Changsha city occurred in the period from 2006 to 2010 at 0.95%, while that of Zhangjiajie City is only 0.15%, appeared in the period from 2011 to 2015. Both patch size and severity of forest disturbances have shown a gradual upward trend, and the proportion of disturbance events with large areas and high severity is increasing. This study explored suitable spectral index combination for change detection, and then revealed the spatio-temporal characteristics of forest disturbance in the study area, providing important spatio-temporal information of disturbance regime change that is critical for near-real-time adaptive forest management.