A novel remote sensing index for monitoring shrub encroachment into grasslands

Grassland shrub encroachment is a widespread issue in global arid and semi-arid regions, posing a great threat to ecological environments and livestock production. Accurate shrub cover estimation is crucial for assessing encroachment extent and dynamics, particularly in severely impacted typical steppes. However, monitoring this process using coarse-resolution satellite sensors is challenging due to the typically low stature of shrubs and their intermixed growth with herbaceous vegetation. To address this, the Typical Steppe Shrub Encroachment Index (SSEI) was developed by mathematically transforming and integrating optical and Synthetic Aperture Radar (SAR) remote sensing features sensitive to shrub coverage. The SSEI leverages phenological differences between shrubs and herbaceous vegetation to identify the optimal monitoring window, effectively enhancing the weak signal of shrubs. Results show that the SSEI, achieves a significantly higher correlation (R = 0.76, p < 0.01, n = 758) and lower bias (RMSE = 3.5%, MAE = 2.75%) with shrub cover than individual remote sensing features and exhibits better sensitivity to changes in shrub cover. This index enables accurate discrimination between shrub-encroached grasslands and shrub-free grasslands when shrub cover reaches ≥10%. Furthermore, the relative vegetation volume scattering q-factor was introduced to complement the SSEI, effectively distinguishing shrub-encroached areas from haymaking fields via a simple threshold. This study demonstrates the value of fusing optical and microwave data for shrub cover extracting in heterogeneous landscapes at coarse resolutions. Requiring no training samples or complex parameterization, the SSEI provides a practical tool for large-scale monitoring of grassland shrub encroachment.