Developing a new disturbance index for tracking gradual change of forest ecosystems in the hilly red soil region of southern China using dense Landsat time series

Abstract

Gradual change is prevalent across the forest landscape and generates long-lasting effects for the landscape surface; thus, tracking long-term gradual change can effectively characterize forest change processes. The objective of this study was to establish a vegetation index for change monitoring so as to determine long-term gradual change processes of forest ecosystems in typical red soil areas. The study area was located in Hengyang City, Hunan Province, China. Landsat images, field survey, and auxiliary data were collected to devise a disturbance sensitive vegetation index (DSVI) as an indicator of forest change. Long-term (1985–2019) forest changes were detected using the LandTrendr algorithm on the Google Earth Engine (GEE), while three evaluation aspects of velocity, frequency, and variance were used to analyze the processes of forest gradual change in red soil regions. Results indicate that the DSVI is a suitable index for forest change detection due to its stronger sensitivity compared to other indexes. Further, it shows excellent change detection ability for different types of gradual changes, such as those caused by drought and significant soil erosion. Furthermore, 97.26% of the forests showed gradual change, and approximately 2/3 of monitored forests showed an increasing growth trend while 1/3 showed a decreasing trend. The dominant (28.33%) forest disturbance frequency indicated instability in red soil regions. Dispersion degree of forest variance was mainly low (48.46%) or medium (28.84%). This research establishes the DSVI as a promising method to track forest gradual change and contributes to a better understanding of gradual change processes of forest landscape over time.