To address the reduced spatial consistency and temporal comparability of land surface temperature(LST)products caused by view zenith angle(VZA)effects under single-angle geostationary thermal infrared observations,this study proposes an angular normalization method for LST over forest and grassland areas.Taking the integrated observatory network for land surface processes in the Heihe River Basin as the study area,this study utilized Fengyun-4 B(FY-4B)LST products,viewing geometry parameters,and multi-dimensional surface features.Based on a directional emissivity model and the spectral response function of the sensor,LST was first converted into thermal radiance.A Light Gradient Boosting Machine(LightGBM)model was then employed to establish the nonlinear relationship between thermal radiance,viewing geometry,and surface properties.The observed VZA was replaced with a near-nadir reference angle while the other surface features remained unchanged,to obtain reference thermal radiance under a unified viewing condition.To reduce the influence of cross-sensor differences on validation results,near-nadir Landsat-8/9 thermal infrared data were introduced and used as an independent reference after cross-sensor bias correction.The results showed that:1)The model effectively characterized the combined response of thermal radiance to viewing geometry and surface properties,with root-mean-square error(RMSE)values of 0.241 and 0.263 and coefficients of determination(R²)of 0.972 and 0.966 for the training and validation datasets,respectively,while the bias values were close to zero;2)After cross-sensor bias correction,the consistency between FY-4B and Landsat reference thermal radiance was substantially improved,with RMSE decreasing from 0.421 to 0.221,bias decreasing from 0.204 to 0.020,and R² increasing from 0.193 to 0.777;3)In the multi-date experiments from 27 to 29 August 2023,the scatter distribution of the angular-normalized FY-4B thermal radiance and corrected Landsat reference radiance converged towards the 1∶1 line,and RMSE values were markedly reduced,with larger correction magnitudes observed in areas with greater VZA;and 4)The International Geosphere-Biosphere Programme(IGBP)land-cover grouping analysis indicated that types with more complex canopy structures and stronger spatial heterogeneity,such as dense grassland and forest,showed more evident accuracy improvements after angular normalization,whereas relatively homogeneous surfaces such as bare land exhibited limited improvement,indicating that the correction effect of this method is consistent with the strength of the thermal radiance directionality of different land cover types.The LST angular normalization method does not require synchronous multi-angle observation data.It can effectively weaken the angular effects in FY-4B LST products while maintaining the basic stability of the LST spatial pattern,providing a feasible technical approach for multi-temporal analysis and quantitative applications of geostationary thermal infrared data.