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Designing roads and pavements is essential due to their role in transportation and communication infrastructure facilities in modern urban communities. Hence, it is crucial to evaluate the pavement durability conditions under the daily normal use of road validity. Monitoring/recording distortions of road surfaces, such as cracks and potholes, is the key factor of observing the surface evolution prior to launching the maintenance operation. One of the most recent technologies is the "Digital Close Range Photogrammetry" (DCRP), which is considered as an appropriate method for digitizing textured surfaces. In this research study, the obtained results showed a monitoring accuracy of less than a millimeter, which can lead to achieving the highest representation of the observed road surface without in situ (physical) measurements. Four to eight digital oriented stereo-images were found very sufficient to produce three-dimensional smart point cloud, as an application of the Scale Invariant Feature Transform (SIFT) algorithm. Five random pothole samples were chosen through a particular road and a longitudinal crack. Their severity levels were assessed through the photogrammetric technique, and an ortho photo, contour map, Digital Surface Model, and Digital Elevation Model were developed.