Detection and thinning of street trees for calculation of morphological parameters using mobile laser scanner data

Abstract

Trees are an important component of our ecosystem and play a crucial role in maintaining environmental quality. They are also essential for maintaining the aesthetic beauty of a landscape. Typically, in case of road broadening, large number of trees are purged. Thus proper monitoring, planning and maintenance of health and growth rate of the trees are required in order to save them. Mobile laser scanning facilitates the mapping of road side objects at a high speed. In this research, an automated method for street trees detection, thinning the interior points of detected trees and calculation of morphological parameters using Mobile Laser Scanner (MLS) data is proposed. The method has been divided into three phases. The first phase detects the street trees from input MLS point cloud data while the second phase deals with the findings of exterior points of detected trees by using the three-dimensional slicing. In the last phase, morphological parameters are calculated for each tree. Proposed method is tested at a MLS data. Completeness and correctness of the method for detection of street trees are 97.85% and 96.80%, respectively.