It is difficult to detect city cloverleaf

which is arised from shortcomings in traditional remote sensing image and the lack of appropriate methods. This paper presents an effective approach to extract city cloverleaf interchange footprints and boundary based on laser scanning data. We developed a plane-based approach to segment the data in the profile area and built a point o rganization structure called advanced scanline profile neighborhood system to identify the seed points. Alpha-shape algorithm was introduced to segment the seed points and generate the point sets boundaries. The cloverleaf interchange boundary was located by three-dimensional contour analysis based on model description. The complete cloverleaf footprints were determined by region-growing algorithm in the end

and meanwhile

the final cloverleaf boundary was obtained. The experiment was performed on the LiDAR data collected on a urban city. The result shows integrity and validly of our function that can get accurate length

width and morphology measurements comparing with the manual measurements from the high resolution ortho image.