Objective  The forest gaps caused by natural disturbance are the main driving force of the natural forest regeneration and the distribution, shape and extent of forest gaps can affect a series of ecological factors, such as sun light and soil moisture. The identification and characterization of forest gaps are of significance for understanding the dynamic changes of forests.

  Method  The remote sensing of UAV can quickly obtain the three-dimensional spatial information of the forest. The study site is located in the UAV flight coverage at the Puer Sun River Reserve in Yunnan Province of southwestern China. The canopy height model (CHM) was derived from the point cloud data of UAV LiDAR . The fixed threshold method, relative height threshold method and object-oriented classification were used to identify forest gaps in CHM. The reference data from visual interpretation of images were used for accuracy assessment of forest gap identification. Finally, the best method was selected to describe the spatial characteristics of forest gaps.

  Result  The experimental result showed that the overall accuracy of the fixed threshold method was 92.00%, which was higher than the relative height threshold method (66.00%) and object-oriented classification method (88.00%). The forest gaps in the study site area were mainly small and medium gaps, showing that there were fewer disturbance events. The average shape index of forest gaps in the study site was 1.97 and most of them with small shape index and less obvious edge effect. The spatial distribution of the gap was aggregation.

  Conclusion  The spatial distribution of forest gaps and its spatial characteristics in small-scale subtropical natural forests can be mapped by UAV LiDAR data and the fixed threshold method.