Abstract: Chlorophyll is an important parameter to evaluate plant growth status.In order to establish the model for estimating the chlorophyll content of maize at different growth stages, the influence of soil and atmosphere and the applicability of satellite remote sensing images were considered.Taking summer maize as the research object, the estimation model of chlorophyll content in elongation stage, filling stage, milk stage and maturity stage was established.The coefficient of determination(R²) and root mean square error (RMSE) were used as evaluation and test indexes.The model was validated based on Planet Labs remote sensing satellite (PL) data and field trip data.It showed that: the Green atmospherically resistant vegetation index(GARI) established the best model for estimating the chlorophyll content of maize at elongation stage and milk stage.In the filling stage, the model based on Green Normalized Differential Vegetation Index(GNDVI) has the best result.The optimal model of the maturity stage was based on the Normalized Differential Vegetation Index (NDVI). Value of R² of these models in the four growth stages were 0.76, 0.85, 0.84 and 0.88, respectively, and the models accuracy was 80%, 90%, 90% and 90%, respectively.Therefore, this model can be used to estimate rapidly and efficiently the chlorophyll content of maize in field scaleand provide theoretical basis for crop growth, quality evaluation and yield estimation.