Traditional drought indices mainly consider a single factor and often cannot comprehensively reflect the drought condition.Based on data of MODIS and CLDAS (CMA Land Data Assimilation System),a daily scale integrated drought monitoring model was established by Gradient Boosting Machine (GBM) with multiple influencing factors and drought index as independent variables and comprehensive meteorological drought index (CI) as dependent variable.It was researched by taking drought in North China from 2015 to 2018 as a case.The results show that the model monitoring results are significantly correlated with the calculated CI values of the observation stations.The coefficient of determination is 0.945 and 0.655,and the Root Mean Square Error (RMSE) is 0.033 and 0.082 for training and test sets,respectively,indicating the high accuracy of the proposed integrated drought monitoring model.The consistency rate between the model monitored CI and calculated CI values is above 65%,and the correlation coefficient with Standard Precipitation Evapotranspiration Index (SPEI) and Relative Soil Moisture (RSM) is 0.68 and 0.6,respectively,showing its capacity to reflect both the meteorological drought and the agricultural drought.Monitoring of typical drought condition shows that the integrated drought monitoring model can accurately identify the drought occurrence,and represent the situation of comprehensive drought via considering various drought influencing factors.