Using mathematical morphology on LiDAR data to extract information from urban vegetation

Accurate delineation of individual tree crowns in human settlement is of vital importance to decision-making in environmental management. Increasing availability of LiDAR data and applications of mathematical morphology imply a paradigm shift in tree crown delineation. This paper introduces a new approach based on “mathematical morphology on grey-level images” that enables such delineation. We consider a LiDAR data set as a grey-level image in which the indexes are the (x,y) locations on the grid and in which each value is the corresponding height of the point acquired by using the LiDAR sensor (i.e. top of the tree at the (x,y) location). We have applied this approach to a large data set in the frame of a partnership with a Hungarian University, and the results we obtain are closely related to what can be seen on a 3D visualization of the LiDAR data set.