 We present the point cloud slicing, PCS, algorithm, which is used to post-process point cloud data, PCD, from terrestrial laser scanning, TLS. This tool was tested for use in forest inventory applications in urban heterogeneous forests. It is based on a voxel data structure derived from TLS-PCD. Tree parameters such as diameter at breast height, DBH, tree height, basal area, and volume were retrieved using the methodology. Our results show that TLS-derived metrics explain 91.17 percent, root mean square error equals 9.1739 centimeters, P less than 0.001, of the variation in DBH at the individual tree level. Although the scanner generates a high-density PCD, only 57.27 percent, root mean square error equals 0.7543 m, P less than 0.001, accuracy was achieved for predicting tree heights in these very heterogeneous stands. Additionally, we developed a voxel-based TLS volume estimation method. Our results show that PCD generated from TLS single-location scans only captures 18 percent of the total tree volume. This article was authored by Elmonica Moscol and Guangjiang. We are article.tv, links in the description below.