The forest canopy structure parameters play a crucial role in global ecological assessments and are important factors influencing the redistribution of solar radiation. LAI-NOS is an automatic observation system for Leaf Area Index（LAI） based on digital hemispherical photography. To test the applicability of LAI-NOS to different forest types and further explore its capability in estimating other canopy structure parameters, this research focused on typical forest types at the Qianyanzhou Subtropical Forest Ecosystem Research Station of the Chinese Academy of Sciences. Continuous observation data of vegetation canopy structure parameters through-out a complete vegetation growth cycle were obtained. Canopy structure parameters such as gap fraction, leaf area index, and clumping index were calculated based on the digital hemispherical photography. The results showed that the parameter estimation results were generally consistent with the growth patterns of the four forest types. The study demonstrated that continuous automatic observation of forest canopy structure parameters based on LAI-NOS is a feasible and effective method, which can provide important data support for forest ecosystem research and management.