Introduction Power facility construction significantly disturbs surrounding ecosystems, and vegetation recovery in temperate regions follows distinct seasonal rhythms whose characterization is essential for informed ecological management. This study aims to quantify seasonal vegetation dynamics around a 500 kV transmission corridor in North China, characterize spatial heterogeneity patterns across disturbance gradients, and elucidate the climate-driven mechanisms governing these processes. Methods A typical 500 kV transmission corridor in North China (2024–2025) was selected, integrating MODIS MOD13Q1 data (250 m, 16-day), Landsat 8 imagery (30 m), meteorological data, and ground validation. The study area was divided into Tower Base Zone (TBZ), Transmission Corridor Zone (TCZ), and Reference Zone (RZ). Vegetation recovery status was quantified using fractional vegetation coverage (FVC), aboveground biomass (AGB), and Shannon diversity index. Two-way ANOVA, redundancy analysis (RDA), and Geodetector model were employed to analyze driving mechanisms. Results Vegetation recovery showed significant seasonal rhythms: summer NDVI (0.58–0.72), biomass (180–265 g/m 2 ), and Shannon index (1.58–2.05) were 2.8, 9.5, and 3.6 times higher than winter values, respectively. Spatial heterogeneity exhibited a stable gradient (RZ TCZ TBZ), with reference zone NDVI 23%–38% higher than tower base zone, showing largest difference in winter (55.6%) and smallest in summer (24.1%). Spring greening rate in TBZ was only 58% of RZ and delayed by 7–10 days; autumn NDVI declined at −0.012 to −0.015/day. Precipitation-season interaction explained 89.4% of vegetation dynamics, with precipitation contributing 42.3% and interaction q-value reaching 0.82. Marginal contribution rate of precipitation was 65%–75% in spring-summer. Discussion Vegetation recovery around power transmission facilities is jointly regulated by phenological rhythms, resource availability, and disturbance patterns, exhibiting season-space coupled dynamics. These findings support a seasonal adaptive management framework encompassing spring seeding, summer optimized clearing, autumn litter protection, and winter evaluation, with MODIS seasonal monitoring integrated into ecological early warning systems.
Wang et al. (2026) studied this question.