Dongting Lake, a vital freshwater lake in China with substantial ecological, economic, and social significance, has fractional vegetation coverage (FVC) as a core indicator of regional ecological balance. To characterize the ecosystem’s health and support targeted protection, this study analyzed FVC’s spatio-temporal evolution and associated spatial factors in the Dongting Lake ecological restoration area using 2005–2020 MODIS imagery, integrating the dimidiate pixel model, slope trend analysis, and geographic detector model (noting the latter quantifies spatial explanatory power but not direct ecological causality). Results revealed distinct FVC heterogeneity: 2011 had the poorest vegetation (mean FVC = 0.60), while 2005, 2010, and 2012 showed higher FVC (mean = 0.65); summer exhibited the most vigorous growth due to favorable hydrothermal conditions. Slope was the dominant single factor with the highest spatial explanatory power for FVC (q = 0.50), its distribution strongly associated with soil moisture and erosion. The slope–soil moisture interaction had the strongest joint spatial explanatory power (q = 0.625), reflecting topographic–hydrological synergistic spatial association, implying slope may indirectly modulate vegetation water availability (inferred from spatial correlation, not causality). The slope–DEM interaction (q = 0.534) confirmed combined topographic explanatory effects. Overall, 70.3% of the region saw significant FVC improvement (notably in spring) from 2005 to 2020, with degradation in February, March, and December. Slope emerged as a key factor consistent with interannual and seasonal FVC variations. These findings provide a reliable scientific basis for targeted wetland restoration, emphasizing enhanced vegetation management in summer, autumn, and the growing season. Limitations include: MODIS’s 250 m resolution leading to mixed-pixel effects in fragmented wetlands, limited validation coverage of extreme habitats and single-year verification, and the Geodetector model’s reliance on spatial stratification and factor independence assumptions (deviating from wetland’s continuous factor variation) that preclude causal inference.
Fu et al. (Fri,) studied this question.