Abstract
Currently, most mapping tasks are carried out using remote sensing data such as satellite imageries and LIDAR point clouds. This paper presents the integration of a QuickBird imagery set (both pan and multispectral) and LIDAR DEM generated from a LIDAR point cloud for mapping the straight-line. A number of image processing techniques were applied to pan image to generate a straight-line. Then, a supervised classification was performed on the multispectral image followed by a raster to vector conversion to extract another line. A third line was created from the LIDAR data using a set of processing algorithms. The three lines are weighted and pixels belonging to all of them were grouped to fit a final straight-line. In order to evaluate the results, we manually extracted the corresponding line from the pan image and compared points belonging to both lines. Differences averaged about 1.37 meters.