Abstract: In order to monitor the scope and extent of cultivated land damage caused by coal mining, the relationship between surface subsidence and vegetation growth was explored, and winter wheat planted in Xinzheng, Henan Province was selected as the research object. Unmanned Aerial Vehicle(UAV)laser radar combined with RTK technology was used to monitor coal mining subsidence, and the accuracy of surface elevation and subsidence data was verified. Vegetation indices and texture features were extracted based on UAV multi-spectral images, and Pearson correlation analysis was used for screening. Biomass inversion models were constructed using decision tree regression (DTR), random forest regression (RFR), and support vector regression (SVR) based on field-synchronous biomass data. The best model was selected based on the coefficient of determination (R²) and root mean square error (RMSE). The final spatial distribution inversion results of winter wheat biomass in the study area were obtained. The results show that: ① The selected vegetation indices and texture features were significantly correlated with biomass, and the combination of vegetation indices and texture features as input variables achieved the highest estimation accuracy. The SVR model had the highest prediction accuracy. ② Biomass in regions III (414–661 g/m²) and IV (662–822 g/m²) accounted for 66.4% of the total, indicating that most samples concentrated in the middle and high biomass range. The area with wheat biomass below 414 g/m² accounted for 25.93%, indicating that vegetation growth was severely affected by mining. ③ Under the influence of mining, a significant negative correlation was found between the subsidence value from the regreening to the jointing stage and the biomass of winter wheat at the jointing stage. The biomass of winter wheat decreased with the increase of subsidence values. When the subsidence of winter wheat from the regreening stage to the jointing stage exceeded 2.1 m, the biomass grade was grade I. The results of the study provide an important basis for the development of precise land reclamation and ecological restoration strategies and provide technical support for enhancing arable land production capacity in the coal-grain composite area.