Digital Photogrammetry for Long-Term Monitoring

Digital photogrammetry has established itself as an effective tool for documenting cultural heritage in the twenty-first century. With portable equipment and a relatively short amount of time, an incredible amount of surface data can be captured for an object and stored as point clouds. This richness of data raises questions of whether it should be used for analytical purposes in addition to documentation. This thesis researches using close-range, digital photogrammetry to describe physical change over time. The image sets were captured, point clouds created in Agisoft, and analyzed using CloudCompare to identify any dislocations. Three-dimensional changes that are not easily measured or observed were chosen as the focus of this research and they were broken into three typologies: cracking, erosion, and warping. Each was recreated using a proxy experiment and gave different degrees of analytical data for The degree to which these changes can be detected will drive what sort of analytical conclusions can be drawn. This comparative photogrammetry can identify areas of change that may be easily ignored by the humane eye due to their slow, gradual rate of change. When these two points in time are compared directly in the form of two high resolution point clouds, minute changes become discreet and take shape. Once the shape becomes a pattern, material condition could begin to be speculated. With two well executed data sets, it is possible to detect and visualize the changes between two experimental models. The challenge lies in understanding how CloudCompare understands these changes and then translating that language into analytical decisions about the condition of the material. The speed, ease, and relatively low cost of photogrammetry makes it very effective at homing in on areas of concern.