Abstract: Zhejiang Province is a key area in China’s strategic development layout with high forest coverage but low productivity, therefore, it is of great significance to explore the dynamics of fractional vegetation cover (FVC) and the driving forces for regional ecological restoration and sustainable development. Landsat Collection 2 data on the Google Earth Engine platform being the basis, the NDVI maximum synthesis method, pixel dichotomy method, and Sen trend analysis and Mann-Kendall test were adopted to investigate the spatiotemporal dynamics of FVC in Zhejiang Province from the year 2000 to 2022. The optimal parameter geographic detector model was employed to quantitatively analyze the driving factors of FVC, and the transition matrix and land use change map were incorporated to explore the relationship between land use and FVC dynamics, aiming to provide a scientific basis for regional ecological protection and management. The results showed that: (1) Temporally, the FVC in the study area showed a fluctuating upward trend from 2000 to 2022, with a growth rate of 0.30% per year. (2) Spatially, the overall vegetation coverage in Zhejiang Province was generally in a better condition, dominated by medium-high and high FVC. Areas with significant and extremely significant improvement in FVC accounted for 10.28% and 25.34% respectively, while those with significant and extremely significant degradation accounted for 3.28% and 4.35%, respectively. The changing trend of FVC had obvious spatial heterogeneity: Areas with high elevation and steep slopes generally had higher FVC and significant improvement, whereas the northern plains of Zhejiang Province, coastal areas, and areas along the Qujiang River and Jinhua River usually had lower FVC and significant degradation.(3) Analysis of driving factors revealed that the impact of anthropogenic factors was stronger than that of natural factors, in which land use type, nighttime light index, elevation and slope were the dominant factors affecting FVC, with q values all exceeding 0.28. (4) The interaction analysis demonstrated that the interaction between land use types and other factors played a dominant role, with q values greater than 0.53. The interaction between land use types and nighttime light index had the strongest influence, with a q value reaching 0.553. This study revealed the types or ranges of driving factors most suitable for vegetation growth in the study area. (5) The land use change analysis revealed that the conversion of cropland to impervious surfaces was most prominent, with its spatial distribution closely coinciding with areas of extremely significant degradation in FVC, which demonstrated that urban expansion was the primary driving force of regional vegetation degradation, concurrently, bidirectional conversion between cropland and forestland was observed.