This paper is focused on the characterization of GNSS signals reception environment by estimating the percentage of visible sky. A new segmentation technique based on a color watershed using an adaptive combination of color and texture information is proposed. This information is represented by two morphological gradients, a classical color gradient and a texture gradient based on co-occurrence matrices. The segmented images are then used as input for a k-means classifier in order to determine the percentage of visible sky in fisheye images. The obtained classification results are evaluated to demonstrate the effectiveness and the reliability of the proposed approach.