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Street trees are one of useful urban facilities that reduce carbon dioxide and provide green space in urban areas. They are usually managed by local government, and it is effective to use aerial LIDAR data in order to acquire information such as the location, height and crown width of street tree systematically. In this research, algorithm was proposed that improves the accuracy of extracting top points of street trees and separates the region of individual street trees from aerial LIDAR data. In order to verify the proposed algorithm, a simulated aerial LIDAR data that exactly knows the number, height and crown width of street trees was created. As for the procedure of data processing, filtering that separates ground and non-ground points from LIDAR data was first conducted in order to separate the region of individual street trees. An estimated non-street tree points were then removed from non-ground points, and the top points of street trees were estimated. Region of individual street trees was determined by using the intersecting point of straight line that connects top point and ground point of street tree. Through the experiment by using simulated data, it was possible to refine wrongly estimated points occurred by determining tree tops and to determine the positional information, height, crown width of street trees through the determination of region of street trees.

Estimation of Individual Street Trees Using Simulated Airborne LIDAR Data