 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%, 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%, root mean square error equals 0.7543m, 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% of the total tree volume. This article was authored by L. Monica Moskel and Wang Jing. We are article.tv, links in the description below.