［Objective］ The spatiotemporal variation trends and driving factors of fractional vegetation cover （FVC） in Jiangsu Province from 2013 to 2022 were investigated， in order to provide a scientific reference for comprehensively understanding vegetation coverage and guiding macro-level policy adjustments in the province. ［Methods］ Based on the Google Earth Engine platform， the pixel dichotomy model was applied to estimate FVC. Sen’s trend analysis， Mann-Kendall significance test， the coefficient of variation， and the Hurst index were employed to systematically analyze the spatiotemporal trends and characteristics of FVC. A univariate linear regression model was constructed using FVC and night light index as variables， followed by residual analysis to quantify the driving factors of FVC changes and their contribution rates. ［Results］ From 2013 to 2022， the annual average FVC in Jiangsu Province was 0.648， with year-to-year variation showing a fluctuating downward trend but still predominantly consisting of very high and high FVC types. Areas with a decreasing FVC trend accounted for 51.85% of the study area， whereas areas with an increasing trend accounted for 45.91%. The average coefficient of variation was 0.16， and the average Hurst index was 0.56. Climate change and human activities jointly drove FVC changes in 58% of the total area. Human activities made a positive contribution to FVC changes in 86.53% of the regions， whereas climate change had a positive impact in 71.47% of the regions. ［Conclusion］ From 2013 to 2022， Jiangsu Province generally exhibited good vegetation coverage， with a gradually stabilizing downward trend and low overall fluctuation. The change trends were primarily weakly persistent， followed by weakly anti-persistent trends， showing an alternating distribution with coexisting degradation and improvement. Northern and central Jiangsu had significantly higher FVC than southern Jiangsu but also experienced more severe vegetation degradation. The primary drivers of FVC changes were the combined effects of climate change and human activities， with human activities generally contributing more than climate change.