Abstract: Using TLS to measure forest parameters (tree height,DBH and tree density,etc.) can not only save manpower, but also improve work efficiency, which has been a fast and effective way to obtain geometric parameters of trees now. A semiautomatic way was employed to extract the individual tree parameters from TLS observations in this paper. Specifically, the noises and “flyingpoints” in the original point clouds were first filtered out by means of intensity and shape deviations between the received echo pulses and the emitted pulses, followed by registration of all stations data, and elimination of partial foliage points and other nontrunk points via the filtering method of different targets echo. Diluting and merging all stations data, horizontal stratification of the merged point clouds to generate the grayscale images were also involved in the current analysis. Using the Hough transform method to estimate locations and DBHs of individual trees, redetecting those fewer results from the Hough transform by means of the ellipse fitting algorithms were also elaborated. Finally, locations, DBHs and heights of individual trees were derived from combining the detection results of Hough transform and ones of ellipse fitting. The average accuracy of individual trees in five multiscans test plots was identified at 72.16%. Comparing the extracted individual tree locations, DBHs and heights with the ground truths, a high consistency between the two data sets was obtained. The RMSEs of DBHs and tree heights in five multiscans plots were 2.38, 2.55, 3.58, 2.21 and 1.92 cm, and 4.31, 3.87, 2.34, 5.00 and 3.47 m respectively.