Comment on: “Evaluating InSAR-derived rates of surface-elevation change along the central U.S. Gulf Coast” by Li et al. (2026)

Li et al. (2026) compare two InSAR-derived surface-elevation change datasets, reported by Ohenhen et al. (2024; hereafter O24) and Wang et al. (2024; hereafter W24) for the central U.S. Gulf Coast and report negligible pixel-by-pixel agreement outside urban areas, concluding that InSAR is unreliable in vegetated coastal settings for rates below 5 mm yr ⁻¹ . InSAR reproducibility is a timely and consequential question, and we share the paper's interest in resolving it, but much of the reported disagreement can be traced to how the comparison was constructed. The two datasets span non-overlapping observational windows (2007–2020 versus 2017–2020) in a system with documented non-stationary subsidence rates; validating each product against GNSS over its own window versus the other product's window shifts residual standard deviations by 19 %–22 %, indicating that epoch mismatch alone accounts for a meaningful share of the apparent disagreement. Three further methodological choices compound this effect: (1) spatial aggregation of the O24 dataset from its native 50 m to 1 km before comparison, a ∼400× reduction in pixel density that discards the sub-kilometer spatial structure the dataset was designed to resolve; (2) a progressively filtered GNSS validation network of only ∼ 20 stations concentrated in atypical, stable Pleistocene upland settings, versus O24's original validation across 157 stations spanning the full coastal domain; and (3) a 5 mm yr ⁻¹ caution threshold derived from inter-product disagreement rather than from principled, instrument-specific uncertainty quantification. We validate O24 at its native 50 m resolution against 88 GNSS stations from the Nevada Geodetic Laboratory within the Li et al. study domain, obtaining a residual standard deviation of 1.6 mm yr ⁻¹ , consistent with Ohenhen et al. (2024). We use this exchange as a starting point for a broader set of best practices for validating and benchmarking InSAR-derived deformation products more generally, covering native-resolution evaluation, validation-network representativeness, accuracy-precision separation, scale-dependent uncertainty, and principled threshold construction, so that inter-product disagreement is neither conflated with measurement failure nor permitted to drive policy-relevant conclusions without rigorous independent validation.