Staring Spotlight TerraSAR-X SAR Interferometry for Identification and Monitoring of Small-Scale Landslide Deformation

We discuss enhanced processing methods for high resolution Synthetic Aperture Radar (SAR) interferometry (InSAR) to monitor small landslides with difficult spatial characteristics, such as very steep and rugged terrain, strong spatially heterogeneous surface motion, and coherence-compromising factors, including vegetation and seasonal snow cover. The enhanced methods mitigate phase bias induced by atmospheric effects, as well as topographic phase errors in coherent regions of layover, and due to inaccurate blending of high resolution discontinuous with lower resolution background Digital Surface Models (DSM). We demonstrate the proposed methods using TerraSAR-X (TSX) Staring Spotlight InSAR data for three test sites reflecting diverse challenging landslide-prone mountain terrains in British Columbia, Canada. Comparisons with corresponding standard processing methods show significant improvements with resulting displacement residuals that reveal additional movement hotspots and unprecedented spatial detail for active landslides/rockfalls at the investigated sites

A Multibaseline Pol-InSAR Inversion Scheme for Crop Parameter Estimation at Different Frequencies

A novel oriented volume over ground (OVoG) inversion scheme is developed and tested on a data set of simulated agricultural scenarios and real SAR acquisitions. The algorithm makes use of multibaseline measurements to estimate the whole set of the OVoG structural parameters (e.g., crop height, differential extinction between eigenpolarizations, and ground-to-volume ratios) and is significantly robust against non-volumetric decorrelation contributions. The theoretical assessment points out that, in the dual-baseline case, the vegetation height hV can be estimated with a relative root-mean-square deviation (%RMSD) of 7.8% if the selected baselines fulfill the condition 1.2 <; κzhV <; 2.8 rad (κz is the vertical wavenumber). Furthermore, the variance of the estimates is inversely related to the number of baselines Nb. Compared with the dual-baseline case, the RMSD of the differential extinction is reduced by 45% (from 1.1 to 0.6 dB/m) when Nb = 5 baselines are employed, whereas its mean bias is independent of Nb. The proposed scheme has been assessed using a set of repeat-pass F-SAR acquisitions at L-, C-, and X-band of an agricultural area in Germany. Using two baselines, the height of maize and rape fields is estimated with an average 10% %RMSD if the inversion is carried out over L-band acquisitions. On the other hand, when X-band data are employed, one can obtain reliable estimates of wheat and barley height, with a %RMSD better than 24%. The study also indicates the existence of differential wave propagation effects through maize (Δσ = σVV - σHH between 0.7 and 1 dB/m) and rape (Δσ = -0.8 dB/m) canopies at L-band

A New InSAR Phase Demodulation Technique Developed for a Typical Example of a Complex, Multi-Lobed Landslide Displacement Field, Fels Glacier Slide, Alaska

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

Comparing performances of RVoG and OVoG crop height inversion schemes from multi-frequency SAR data

In this work, we assess the plausibility of the Random Volume over Ground (RVoG) assumption in relation to crop height estimation. For this reason, two dual-baseline Random-VoG and Oriented-VoG inversion schemes have been developed and applied to a dataset of fully-polarimetric F-SAR measurements over an agricultural area in Germany. Preliminary results for the wheat case study indicate a positive relation between the bias of the estimated height and the differential extinction when the Random-VoG inversion scheme is used. © VDE VERLAG GMBH · Berlin · Offenbach

On the Potential of Polarimetric SAR Interferometry to Characterize the Biomass, Moisture and Structure of Agricultural Crops at L-, C- and X-Bands

Polarimetric SAR Interferometry (Pol-InSAR) has shown great promise for estimating the height of agricultural crops through the inversion of a scattering model of the plant canopy and the soil. The inversion also provides estimates of model parameters describing the microwave attenuation within the canopy and the relative scattering contributions from canopy and soil surface. Here, we investigate how vegetation characteristics including biomass, water content (VWC) and canopy structure are related to these parameters and provide a first assessment of the potential of estimating such characteristics using Pol-InSAR time series in L-, C- and X-Bands. The overall attenuation for maize is positively related to total VWC in L- and C-Bands. Furthermore, larger attenuation in VV than HH points toward the existence of anisotropic propagation effects due to vertical orientation of the stalks. Conversely, for wheat in C- and X-Bands there is no consistent relation between attenuation loss and VWC. Rather, structural changes occurring within the plant growth cycle appear to have an appreciable polarization-dependent effect on the observed attenuation changes. In addition, the estimated normalized volume backscattering power NVP (a measure of the relative scattering contribution from the canopy compared to the underlying soil) is associated with wet biomass. However, the contrasting sign of this relation (negative for maize in L- and C-Bands; positive for wheat in C- and X-Bands) indicates again the role of crop structural properties in the Pol-InSAR measurements. For instance, the NVP for maize in L- and C-Bands appears to decrease with increasing biomass due to the increasingly important double bounce ground-stalk scattering contribution as plants become taller and thicker. Overall, these results indicate the sensitivity of the Pol-InSAR parameters to canopy structure and biomass; this sensitivity is however dependent, amongst others, on crop type and radar frequency. When choosing an appropriate baseline/frequency configuration, the Pol-InSAR attenuation loss and NVP may complement the information of the estimated crop height, especially if the latter shows very little variation over the plant growth cycle (e.g. as for wheat)