Screws are the closest and most familiar mechanical elements of everyday life, and are generally used so widely that there is no machine without screws. Screws are used to make it easier to combine objects with objects, and are also used to transfer large forces from machines. The most influential factor in the coupling of these screws is the effective diameter. If the effective diameter is not accurate, the support cannot be finished or endured, leading to a major accident. The importance of these screws cannot be ignored, so in this study, the effective diameter was measured using the three-wire method, the screw micrometer method, and the projector method, and the one-way factor design method was applied to determine the exact method compared to the KS standard.

This study was to evaluate the utilization of terrestrial light detection and ranging for forest inventory in coniferous forests. Heights and diameter of the stand trees were measured manually using the traditional measurement method and the method using terrestrial LiDAR. The results of two methods were compared and analyzed to evaluate accuracy and feasibility. The terrestrial LiDAR used fixed and handy types to compare the accuracy between different operational methods. Comparative analyses used a paired t-test and Bland-Altman plot analysis. In the case of tree heights, the average of difference between the traditional method and terrestrial LiDAR for each plot was 0.81 m, -0.07 m, and 0.13 m for fixed type; 2.88 m, 1.19 m, and 0.93 m for the handy type. In the case of tree diameter at breast height, the average value of the difference between traditional methods and terrestrial LiDAR for each plot was 0.13 cm, -0.66 cm, and –0.03 cm for fixed type; 2.36 cm, 2.13 cm, and 1.92 cm for the handy type. The values from the method using the fixed type was highly consistent with that using the traditional measurement methods; the average difference was closer to zero. The crown density influences the precision of the height measurement using terrestrial LiDAR in coniferous forests. Therefore, future studies should focus on verifying the a