This research is on investigating the interpretation of sensor data obtained from three-dimensional scans of structures using laser scanners. Laser scanner capabilities have advanced significantly recently and have gained more recognition as a tool for application in numerous fields. My research focuses on developing the foundation towards the use of imaging and laser scanning for structural engineering applications, including structural health monitoring, post-hazard response and damage assessment of structures. More specifically, the use of high-resolution three-dimensional terrestrial laser scanners and associated mapped images as tools to capture geometric range data of complex scenes, where the objective is to establish a process for extracting important information from raw laser-scanned data sets such as the location, orientation and size of objects in a scene, have been being investigated. Existing point cloud processing algorithms have been extended and used for processing range data in order to identify objects in a scene. As a first step, detection and quantification moderate damage states that exist within a structure have been being investigated through augmenting/replacing the current visual inspection methods. Second, for damage that induces larger deformations, but where the initial topology of the structure has not changed appreciably, damage detection techniques based on assessment of the geometry before and after the deformation occurs have been being developed. Key goal of this research is to establish strategies for automated damage detection that will provide, when coupled with corroborating analyses, dramatically new capabilities for ascertaining the current state of a structure.