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This paper addresses the problem of road region detection in urban areas using an image classification approach. In order to\udminimize the spectral superposition of the road (asphalt) class with other classes, the Artificial Neural Networks (ANN) image\udclassification method was used to classify geometrically-integrated high-resolution RGB aerial and laser-derived images. The RGB\udimage was combined with different laser data layers and the ANN classification results showed that the radiometric and geometric\udlaser data allows a better detection of road pixel

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

ROAD REGION DETECTION IN URBAN AREAS COMBINING HIGH-RESOLUTION RGB IMAGE AND LASER SCANNING DATA IN A CLASSIFICATION FRAMEWORK