A Streamlining Remote Sensing and Digitalization Process for Bridge Inspection

Abstract

One of the major challenges that prohibited the wide application of remote sensing photogrammetry in modern bridge inspection is the lack of advanced sensing platforms with a data analysis process. This study explores remote sensing for bridge inspection with a suite of unmanned aerial system (UAS) platforms accompanied by a follow-up digitization process for bridge inspection. To fully inspect a bridge of interest, a team of four complementary remote sensing UASs and equipment is employed, including a confined-space-specific Elios2 drone for bridge underdeck inspection, a DJI M600 equipped with LiDAR, thermal and hyperspectral sensors for above bridge deck sensing, an Anafi Parrot for side and above bridge deck RGB imaging, and a supplementary hand-held high-resolution camera for drone-inaccessible and highpriority areas. The digitized bridge inspection results cover multiple aspects of the bridge, including an interactive digital object represented by a dense point cloud, RGB images to reflect any visible surface deterioration (such as cracks, spalling, corrosion, and efflorescence), thermal images to reflect bridge deck near-subsurface delamination, and hyperspectral images to reflect any invisible bridge surface change. The digitized bridge model provides a comprehensive but intuitive digital representation of the inspected bridge. Compared to traditional bridge inspection practices with descriptive and subjective results, remote sensing photogrammetry shows great potential in efficient and consistent bridge inspection with fine details, which is believed to be necessary for reliable bridge condition assessment and long-term bridge health monitoring.