Phenology-Optimized Drought Index Reveals the Spatio-Temporal Patterns of Vegetation Health and Its Attribution on the Loess Plateau

Frequent droughts pose a severe threat to the ecological health and sustainable development of the Loess Plateau (LP). The accurate assessment of the impact of drought on vegetation is crucial for diagnosing ecological health. Traditional drought assessment methods often rely on coarse estimations based on averages of vegetation drought indices, overlooking the spatial differentiation of complex vegetation phenology. This study proposes a vegetative drought assessment method that considers vegetation phenological characteristics using MODIS EVI and LST data products. First, the start and end of the growing season timepoints were extracted from the Enhanced Vegetation Index (EVI) using Savitzky-Golay (S-G) filtering and the dynamic threshold method, determining the growing-time window for each pixel. Next, the Vegetation Health Index (VHI) series was calculated and extracted for each pixel within the growing season. The mean value of the VHI series was then used to construct the Growing Season Health Index (GSHI). Based on the GSHI, the long-term vegetation drought characteristics at LP were revealed. Finally, we integrated the Optimal Parameters-based Geographical Detector (OPGD) to identify and quantify the multiple driving forces of vegetation drought. The results showed that: (1) the spatio-temporal difference of vegetation phenology on the LP was significant, exhibiting distinct zonal characteristics; (2) the spatial distribution of growing season drought on the LP presented a "humid southeast, arid northwest" pattern, with the early 21st century being a period of high drought occurrence; (3) drought has been alleviated in large-scale natural areas, but the local drought effect under urbanization is intensifying; and (4) meteorology and topography influence vegetation drought by regulating water redistribution, while the drought effect of human activities is intensifying.