Cloud top height (CTH) is an important parameter monitored in atmospheric observations, which has a significant impact on weather prediction, climate models, and flight services. CTH is typically obtained via three ways, namely, satellite, radiosonde, and ground-based radar, with their corresponding strengths and weaknesses. Traditionally, many studies have focused on independent comparison and analysis of CTHs retrieved from different observations. The researches on how to improve the reliability of the CTH by integrating multiple cloud measurements are rare in the literature despite the significance of this strategy to practical meteorological forecast and disaster prevention improvement. An integration technique of different CTHs retrieved from Fengyun 2 (FY-2) meteorological satellite, radiosonde, and ground-based millimeter wavelength cloud radar observations by using Bayesian decision theory is proposed in this study. A dataset is collected in Beijing, China for 12 months from June 2015 to May 2016 to validate the integration effect. Experimental results show that the integration observations improve the accuracy of single observations. Integration observations are more closely correlated with “true” CTH observations than the single observations. These all show the effectiveness of the proposed multiple source data integration strategy.