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UAVs showed great efficiency on scanning bridge decks surface by taking asingle shot or through stitching a couple of overlaid still images. Ifpotential surface deficits are identified through aerial images, subsequentground inspections can be scheduled. This two-phase inspection procedure showedgreat potentials on increasing field inspection productivity. Since aerial andground inspection images are taken at different scales, a tool to properly fusethese multi-scale images is needed for improving the current bridge deckcondition monitoring practice. In response to this need a data fusion platformis introduced in this study. Using this proposed platform multi-scale imagestaken by different inspection devices can be fused through geo-referencing. Aspart of the platform, a web-based user interface is developed to organize andvisualize those images with inspection notes under users queries. Forillustration purpose, a case study involving multi-scale optical and infraredimages from UAV and ground inspector, and its implementation using the proposedplatform is presented.

A Data Fusion Platform for Supporting Bridge Deck Condition Monitoring by Merging Aerial and Ground Inspection Imagery