Polarimetric synthetic aperture radar (SAR) interferometry has shown great potential to estimate the height of crops and forests by inverting simple scattering models of the canopy and the underlying soil. The random-volume-over-ground (RVoG) model assumes that the scatterers within the canopy (e.g., stalks and leaves) are not aligned along a preferred direction. If these scatterers are characterized by a correlation of orientations, then the scene is better described by the oriented-volume-over-ground (OVoG) model. This paper investigates the plausibility of the “random volume” and “oriented volume” assumptions, as well as the robustness of single- and dual-baseline inversion schemes in relation to agricultural crop height estimation. To this end, we implemented different single- and dual-baseline techniques for the inversion of the RVoG and OVoG models, and we evaluated their height retrieval performances with the help of simulated observations and experimental F-SAR measurements in L-, C-, and X-Bands. The inversion results revealed a positive relationship between the bias of the estimated height and the differential extinction when the RVoG inversion scheme is applied. By contrast, no such dependence was observed for the OVoG inversion, whose height estimates are on average consistent with the actual values (i.e., median bias below 10% in magnitude). Despite the observed superiority of dual-baseline approaches, the study also pointed out the feasibility of crop height estimation using single-baseline RVoG inversion schemes, provided the appropriate a priori constraints (e.g., on the extinction coefficient) and crop-specific configuration parameters (e.g., C-Band for maize, and C- and X-Bands for wheat).

Landslides can have complex, spatially strongly inhomogeneous surface displacement fields with discontinuities from multiple active lobes that are deforming while failing on nested slip surfaces at different depths. For synthetic aperture radar interferometry (InSAR), particularly at lower resolutions, these characteristics can cause significant aliasing of the wrapped phase. In combination with steep terrain and seasonal snow cover, causing layover and temporal decorrelation, respectively, traditional phase unwrapping can become unfeasible, even after topographic phase contributions have been removed with an external high-resolution digital surface model (DSM). We present a novel method: warp demodulation that reduces the complexity of the phase unwrapping problem for noisy and/or aliased, low-resolution interferograms of discontinuous landslide displacement. The key input to our warp demodulation method is a single (or several) reference interferogram(s) from a high-resolution sensor mode such as TerraSAR-X Staring Spotlight with short temporal baseline and good coherence to allow localization of phase discontinuities and accurate unwrapping. The task of constructing suitable phase surfaces to approximate individual to-be-demodulated interferograms from the reference interferogram is made difficult by strong and spatially inhomogeneous temporal, seasonal, and interannual variations of the landslide with individual lobes accelerating or decelerating at different rates. This prevents using simple global scaling of the reference. Instead, our method uses an irregular grid of small patches straddling strong spatial gradients and phase discontinuities in the reference to find optimum local scaling factors that minimize the residual phase gradients across the discontinuities after demodulation. Next, for each to-be-demodulated interferogram, from these measurements we interpolate a spatially smooth global scaling function, which is then used to scale the (discontinuous) reference. Demodulation with the scaled reference leads to a residual phase that is also spatially smooth, allowing it to be unwrapped robustly after low-pass filtering. A key assumption of warp demodulation is that the locations of the phase discontinuities can be mapped in the reference and that they are stationary in time at the scale of the image resolution. We carry out extensive tests with simulated data to establish the accuracy, robustness, and limitations of the new method with respect to relevant parameters, such as decorrelation noise and aliasing along phase discontinuities. A realistic parameterization of the method is demonstrated for the example of the Fels Glacier Slide in Alaska using a recent late-summer high-resolution staring spotlight interferometric image pair from TerraSAR-X to demodulate. We show warp demodulation results for also recent but early-summer, partially incoherent interferograms of the same sensor, as well as for older and coarser aliased interferograms from RADARSAT-2, ALOS-1, and ERS.