This paper is focused on the characterization of GNSS signals reception environment by estimation of the percentage of visible sky in real-time. On previous works (1, 2), a new segmentation technique based on a color watershed using an adaptive combination of color and texture information was proposed. This information was represented by two morphological gradients, a classical color gradient and a morphological texture gradient based on mathematical morphology or co-occurrence matrices. The segmented images were then classified into two regions: sky and not-sky. However, this approach has high computational cost and thus, cannot be applied in real-time. On this paper, we present this adaptive segmentation method with a texture gradient calculated by the Gabor filter and a region-tracking method based on a block-matching estimation. This last step reduces the execution time of the application in order to respect the real-time conditions. Since the application works for fish-eye images, a calibration and rectification method is required before tracking and is also presented on this paper. The calibration method presented is based on the straight line condition and thus does not use real word coordinates. This prevents measurement errors. The tracking results are compared to the results of the classification method (which has already been evaluated on previous works). The evaluation shows that the proposed method has a very low error and decreases the execution time by ten times.