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The urban road network extraction process can be simplified by firstly detecting regions corresponding to streets, allowing asubstantial reduction of the search area. As a result, the extraction process is benefited in two aspects: the computational complexityand the reliability. This paper aims at detecting street regions using only data obtained by Laser Scanner Systems. A sequence ofstandard image processing techniques is used to process height and intensity laser scanner data. A normalized Digital Surface Modelis derived from height laser scanner data, from which regions corresponding to aboveground objects (mainly trees and buildings) aredetected. Next, detected tree regions are eliminated from the aboveground regions, remaining only buildings. Then, morphologicaloperators are applied in order to obtain elongated street ribbons and homogeneous block regions. Street regions are also detected inthe intensity image. The results obtained from the radiometric and geometric laser scanner data are combined, allowing theelimination of non-street regions and the improvement of the geometry of region boundaries. The experimental results showed thatthe methodology proved to be efficient to detect street regions

the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences

STREET REGION DETECTION FROM NORMALIZED DIGITAL SURFACE MODEL AND LASER DATA INTENSITY IMAGE