摘要 : The goal of our study was to separate managed and unmanaged bamboo (Phyllostachys pubescens) forests based on the height and density of bamboo stems using LiDAR data. Based on 95% confidence intervals of the height of managed and ... 展开 The goal of our study was to separate managed and unmanaged bamboo (Phyllostachys pubescens) forests based on the height and density of bamboo stems using LiDAR data. Based on 95% confidence intervals of the height of managed and unmanaged bamboo obtained during field surveys, stem height was classified as either "managed stem zone," "transitional zone," or "unmanaged stem zone." Using the digital canopy height model (DCHM, mesh size = 1.0 m) obtained from the LiDAR data for these three zones, bambooforests successfully classified to "managed forests", "extensively managed forests" and "unmanaged forests". Density analysis was conducted using the marker-controlled watershed segmentation algorithm utilizing treetops obtained using the local maxima detection method (LM) with a circular window with a 1.0-m radius. Stem number obtained through LiDAR was compared to that obtained during field surveys by calculating the extraction rate. Stem numbers were underestimated in every management status category; with an increase in stem density, crown size decreased, which eventually lead to a low extraction rate. Because the estimated crown size of managed and unmanaged stems were approximately 1.0 m and 0.8 m, respectively, the DCHM with mesh size < 0.5 m and a circular window size for LM with <1.0 m radius are required to classify the bamboo forest based on their management status. 收起