Ensuring the structural integrity of bridge substructures is critical for the longevity of infrastructure and transportation safety. This session delves into cutting-edge methods for utilizing Light Detection and Ranging (LiDAR) technology to monitor and analyze highway substructure movements. Recent advancements in remote sensing have significantly improved data accuracy while reducing costs, enabling precise measurement of even the smallest surface changes over time. While many existing tools for processing LiDAR point cloud data facilitate ease of use, they often lack the precision needed to detect subtle shifts that signal potential issues. NYSDOT has developed methods to directly process XYZ-data in PTC Mathcad Prime, crafting custom algorithms to extract and analyze critical data from multiple scans. These methods allow for detailed surface modeling through segmentation, classification, filtering, and statistical techniques like linear regression and gradient descent.  These advanced methodologies are applied to assess the temporal behavior of bridge components such as abutments, piers, culverts, and walls in real-world examples that illustrate how NYSDOT has employed these techniques.