Interferometric Synthetic Aperture Radar (InSAR) has transformed the observation of earthquakes, volcanic unrest, land subsidence, glacier motion, and slope instability. By comparing the phase of radar signals acquired at different times, it can reveal surface displacement over large areas with remarkable sensitivity.

Yet an interferogram does not contain deformation alone. Orbital inaccuracies, topographic residuals, temporal decorrelation, tropospheric delay, and ionospheric disturbances can all contribute to the measured phase. Without adequate separation, an atmospheric or instrumental artefact may be interpreted as genuine ground movement.

Ionospheric contamination is especially important for long-wavelength radar systems. Variations in free-electron density can introduce broad phase gradients, streaks, azimuth shifts, and spatially variable distortions. These effects are often strongest in L-band observations, although C-band interferograms can also be affected during disturbed ionospheric conditions or when subtle, long-wavelength deformation is being analysed.

Split-spectrum interferometry offers a physically grounded response. The radar bandwidth is divided into separate frequency sub-bands, and the resulting interferograms are compared. Because deformation-related phase and ionospheric phase scale differently with frequency, their contributions can be separated.

The principle is elegant, but the result is not automatically reliable. Sub-band design, coherence, filtering, unwrapping, sensor characteristics, and validation choices all influence the correction. This perspective argues that the next major advance should be a common framework for reporting, validating, and comparing split-spectrum results across sensors, acquisition modes, and environments.

Split-spectrum interferometry is one of the most physically grounded approaches for separating dispersive ionospheric effects from non-dispersive InSAR phase. Its importance will grow as long-wavelength radar missions expand the spatial and temporal coverage of deformation observations.

Methodological maturity, however, cannot be judged only by the number of correction algorithms. A mature method also requires transparent parameter reporting, uncertainty propagation, independent validation, and reproducibility across sensors and environments.

The strongest opportunity for the InSAR community is therefore not simply another split-spectrum variant. It is a shared standard through which present and future methods can be compared. A corrected interferogram should be accompanied not only by a cleaner phase pattern, but also by evidence explaining why that pattern can be trusted.