Terrestrial laser scanner (TLS) integrates precise range and angular measurements to construct a three-dimensional representation of the target object in the form of a point cloud. In forestry, TLS allows precise measurement of tree dimensions, canopy structure, and forest density, which are essential for understanding growth patterns, and biomass estimation. Quantitative Structural Modelling (QSM) of point cloud data has been widely used for structural parameter retrieval and volume estimation of trees. In this study, we demonstrate QSM to retrieve tree structural parameters from point cloud data acquired in the Indian Western Himalayan region. The target forest vegetation was comprised of native Himalayan tree species viz. Pinus roxburghii, Cedrus deodara, Shorea robusta and Quercus floribunda. The difficulty of estimating Himalayan forest structure parameters arises from topographical variations. Rugged terrain limits positions for LiDAR scanning and complicate the generation of accurate Digital Terrain Models (DTM). Therefore, several acquisition factors determine the preciseness of the forest parameters estimated from TLS data, such as sensor specifications, scanning and processing technique, topography, and the characteristics of target forest vegetation.