Hyperspectral imaging (HSI) is an advanced non-destructive evaluation (NDE) technique with significant potential for the Structural Health Monitoring (SHM) of civil infrastructure, particularly aging bridges. By capturing detailed spectral signatures, HSI can identify material degradation, such as efflorescence and moisture, which are often precursors to structural decay and invisible to standard visual inspection. However, a critical barrier to the practical application of HSI is the requisite for robust data pre-processing. Raw sensor data must be corrected for geometric distortions and radiometrically calibrated to produce physically meaningful surface reflectance. This thesis confronts a primary challenge encountered in field-based SHM: a catastrophic failure of the standard Empirical Line Calibration (ELC) workflow, which, upon investigation, was traced to a combination of band-to-band geometric misregistration and metadata-handling errors in the reference spectral libraries.