Single-pass Interferometric Synthetic Aperture Radar Research Articles

Satellite-Based Identification and Characterization of Extreme Ice Features: Hummocks and Ice Islands

The satellite-based techniques for the monitoring of extreme ice features (EIFs) in the Canadian Arctic were investigated and demonstrated using synthetic aperture radar (SAR) and electro-optical data sources. The main EIF types include large ice islands and ice-island fragments, multiyear hummock fields (MYHF) and other EIFs, such as fragments of MYHF and large, newly formed hummock fields. The main objectives for the paper included demonstration of various satellite capabilities over specific regions in the Canadian Arctic to assess their utility to detect and characterize EIFs. Stereo pairs of very-high-resolution (VHR) imagery provided detailed measurements of sea ice topography and were used as validation information for evaluation of the applied techniques. Single-pass interferometric SAR (InSAR) data were used to extract ice topography including hummocks and ice islands. Shape from shading and height from shadow techniques enable us to extract ice topography relying on a single image. A new method for identification of EIFs in sea ice based on the thermal infrared band of Landsat 8 was introduced. The performance of the methods for ice feature height estimation was evaluated by comparing with a stereo or InSAR digital elevation models (DEMs). Full polarimetric RADARSAT-2 data were demonstrated to be useful for identification of ice islands.

Improving Sea Surface Height Reconstruction by Simultaneous Ku- and Ka-Band Near-Nadir Single-Pass Interferometric SAR Altimeter

Wide swath near-nadir interferometric altimetry is a newly developed technology for sea surface height (SSH) measurement. However, the absence of actual measurement data makes this novel SSH mapping technique difficult to verify and apply for wide swath interferometric altimeters. To verify the designed performance of the scheduled wide swath single-pass interferometric altimeter in the "Guanlan Mission", an airborne campaign was carried out off the coast of Rizhao, China on November 16, 2020. An airborne dual-frequency interferometric radar altimeter system (ADIRAS) with a single-pass mode was utilized for SSH measurement as the first flight. Two pioneering and fundamental works have been conducted: an intensive altimetry error analysis according to the ADIRAS parameter settings along the incident direction, an effective SSH reconstruction approach based on a multichannel likelihood (ML) function, and detailed validation procedures through airborne campaigns illustrated in this study. The results indicated that the difference between the wave-induced sea surface elevation (WSSE) variances derived by the ML approach and GNSS buoy was 2 cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> , which was smaller than the results of the single band on Ku (11 cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ) and Ka (6 cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ). Moreover, the estimated Significant Waves Height (SWH) bias of joint bands was 10 cm, which was also superior to that of Ku (39 cm) and Ka (24 cm). Both simulated data and real airborne dual-frequency InSAR data were employed in this study for cross-validation of the proposed method. This approach represents an effective technique for SSH reconstruction of future spaceborne/airborne interferometric altimeters.

Forest Height Estimation Approach Combining P-Band and X-Band Interferometric SAR Data

Forest height is an essential parameter used to derive important information about forest ecosystems, such as forest above-ground biomass. In this article, a forest height estimation approach combining P-band and X-band interferometric synthetic aperture radar (InSAR) was introduced. The forest height was estimated using the difference in the penetration of long- and short-wavelength radars to the forest. That is, the P-band and X-band InSAR data were used to extract the digital terrain model (DTM) and digital surface model (DSM), respectively. For the DTM, an improved time-frequency (TF) analysis method was used to reduce the effect of forest scatterers on the extraction of a pure understory terrain phase based on P-band InSAR. For the DSM, a novel compensation algorithm based on a multi-layer model (MLM) was proposed to remove the penetration bias of the X-band. Compared to the existing method based on the infinitely deep uniform volumes (IDUV) model, the MLM-based method is more in line with the characteristics of forest structure and the scattering mechanism for X-band InSAR. The airborne P-band repeat-pass InSAR and spaceborne X-band (TanDEM-X) single-pass InSAR data were used to verify the proposed method over the study area in the Saihanba Forest Farm in Hebei, China. The results demonstrated that the improved TF method can achieve high-precision DTM extraction based on P-band InSAR data, and the root mean square error (RMSE) was 0.94 m. The proposed MLM-based compensation method of the DSM achieved a smaller error (RMSE: 1.67 m) compared to the IDUV-based method (RMSE: 3.01 m). Under the same DTM extracted by P-band InSAR, the estimation accuracy of forest height based on the MLM method was 86.58% (RMSE: 1.81 m), which was 8.49% higher than that of the IDUV-based method (RMSE: 2.98 m).

Antarctic snow-covered sea ice topography derivation from TanDEM-X using polarimetric SAR interferometry

Abstract. Single-pass interferometric synthetic aperture radar (InSAR) enables the possibility for sea ice topographic retrieval despite the inherent dynamics of sea ice. InSAR digital elevation models (DEMs) are measuring the radar scattering center height. The height bias induced by the penetration of electromagnetic waves into snow and ice leads to inaccuracies of the InSAR DEM, especially for thick and deformed sea ice with snow cover. In this study, an elevation difference between the satellite-measured InSAR DEM and the airborne-measured optical DEM is observed from a coordinated campaign over the western Weddell Sea in Antarctica. The objective is to correct the penetration bias and generate a precise sea ice topographic map from the single-pass InSAR data. With the potential of retrieving sea ice geophysical information by the polarimetric-interferometry (Pol-InSAR) technique, a two-layer-plus-volume model is proposed to represent the sea ice vertical structure and its scattering mechanisms. Furthermore, a simplified version of the model is derived, to allow its inversion with limited a priori knowledge, which is then applied to a topographic retrieval scheme. The experiments are performed across four polarizations: HH, VV, Pauli 1 (HH + VV), and Pauli 2 (HH − VV). The model-retrieved performance is validated with the optically derived DEM of the sea ice topography, showing an excellent performance with root-mean-square error as low as 0.26 m in Pauli-1 (HH + VV) polarization.

A New Approach for Forest Height Inversion Using X-Band Single-Pass InSAR Coherence Data

In this article, a multilevel model (MLM) for forest height inversion is introduced and investigated using X-band single-pass interferometric synthetic aperture radar (InSAR) coherence data. Compared with the two-level model (TLM), as a generalized model, the MLM is more in line with the characteristics of forest structure and the scattering mechanism for X-band data. Based on the MLM model, three simplified MLM models were derived: TLMm, SINC, and MTND. An improved method of calculating coherence considering the assumptions of the MLM model is proposed. At two test sites, airborne (CASMSAR) and spaceborne (TanDEM-X) X-band single-pass InSAR data and LiDAR H100 data were used to verify the proposed new approach. The results showed that the MTND model can obtain more reliable and accurate inversion results compared to the SINC model and the TLMm. With airborne InSAR data, the MTND model’s highest accuracy was 82.56%, and the root mean square error (RMSE) was 2.4 m. With spaceborne InSAR data, the highest inversion accuracy of the MTND model was 73.55%, with an RMSE of 4.92 m. The inversion accuracy of forest height can be effectively improved by ensuring that the theoretical models and calculations of coherence obey the same assumptions.

Lava effusion rate evolution and erupted volume during the 2018 Kīlauea lower East Rift Zone eruption

The 2018 eruption on the lower East Rift Zone of Kīlauea Volcano produced one of the largest and most destructive lava flows in Hawai’i during the past 200 years. Over the course of more than 3 months, twenty-four fissures erupted, and the rate of lava effusion varied by two orders of magnitude, with significant implications for evolving flow behavior and hazards. Syn-eruptive data were collected to quantify these changes in lava effusion rate, including video of flow through channels and digital elevation models acquired using small unoccupied aircraft systems, airborne lidar, and airborne single-pass interferometric synthetic aperture radar. Topographic data through time allowed calculation of subaerial lava flow volume and time-averaged discharge rate over the course of the eruption, which we integrated with pre- and post-eruption bathymetric surveys. Repeat videos of the near-vent channel were analyzed with particle velocimetry to extract flow velocities, and these were combined with open channel flow theory to calculate a time series of instantaneous effusion rates. Results show a general increase in dense rock equivalent (DRE) effusion rate from ~7 to ~100 m3/s from early to late May for the whole flow field and ≥ 200 m3/s by mid-June after the eruption had focused at a primary vent. By the end of the eruption in August, 0.9–1.4 km3 DRE of lava had erupted, with 0.4 km3 deposited on land and at least 0.5 km3 offshore. The trends in effusion rate through time reflect magmatic processes in the connected summit and rift zone system that controlled eruption rate, with resulting implications for lava flow dynamics and hazards.

Polarimetric Behavior for the Derivation of Sea Ice Topographic Height From TanDEM-X Interferometric SAR Data

Single-pass interferometric synthetic aperture radar (InSAR) is an effective technique for sea ice topographic retrieval despite the inherent dynamics of sea ice. However, the penetration of microwaves into snow-covered thick ice and the achievable height sensitivity for tens-of-centimeters thin ice are two major issues, which limit the accuracy of InSAR-derived sea ice topography. Polarimetry provides scattering information concerning the sea ice properties and has the potential, in combination with interferometry, to achieve an accurate reconstruction of a sea ice digital elevation model (DEM). This article studies the relation between polarimetric signatures and sea ice topography, and explores the possibility to compensate the penetration bias by merging copolar coherence into InSAR processing. The newly generated topographic map has a root-mean-square error under 0.3 m. For thin ice below 1 m, a positive relation between copolar phase φ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">coPol</sub> and surface height is observed, suggesting that φ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">coPol</sub> can effectively characterize thin sea ice topography. For thick ice with ridges, the maximum polarimetric phase difference Δφ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">maxPol</sub> reveals a particular shape of the coherence region, which can be interpreted as oriented volume scattering. It suggests that the model-based approach using polarimetric SAR interferometry assuming an oriented volume scattering model is promising in measuring the scattering centers in thick and deformed sea ice. The study of polarimetric behavior for the InSAR DEM is, therefore, a step forward toward accurate modeling of sea ice topography from polarimetric single-pass InSAR data.

Phase Difference Measurement of Under-Sampled Sinusoidal Signals for InSAR System Phase Error Calibration.

Phase difference measurement of sinusoidal signals can be used for phase error calibration of the spaceborne single-pass interferometric synthetic aperture radar (InSAR) system. However, there are currently very few papers devoted to the discussion of phase difference measurement of high-frequency internal calibration signals of the InSAR system, especially the discussion of sampling frequency selection and the corresponding measuring method when the high-frequency signals are sampled under the under-sampling condition. To solve this problem, a phase difference measurement method for high-frequency sinusoidal signals is proposed, and the corresponding sampling frequency selection criteria under the under-sampling condition is determined. First, according to the selection criteria, the appropriate under-sampling frequency was chosen to sample the two sinusoidal signals with the same frequency. Then, the sampled signals were filtered by limited recursive average filtering (LRAF) and coherently accumulated in the cycle of the baseband signal. Third, the filtered and accumulated signals were used to calculate the phase difference of the two sinusoidal signals using the discrete Fourier transform (DFT), digital correlation (DC), and Hilbert transform (HT)-based methods. Lastly, the measurement accuracy of the three methods were compared respectively by different simulation experiments. Theoretical analysis and experiments verified the effectiveness of the proposed method for the phase error calibration of the InSAR system.

Robust, Model-Based External Calibration of Multi-Channel Airborne SAR Sensors Using Range Compressed Raw Data

The paper describes a method for the accurate calibration of multi-channel SAR instruments, such as those required to support SAR polarimetry, single-pass interferometry and digital beam-forming (DBF), on the basis of dedicated SAR acquisitions containing reference targets with known properties. Unlike conventional approaches, the method is based entirely on the analysis of range-compressed raw data. It leverages the pulse-by-pulse analysis of amplitude, phase and delay variations observed within the range histories of reference targets to fully characterize and correct propagation direction dependent calibration issues such as those related to antenna pointing or antenna phase center positions. The fact that the approach does not require SAR image focusing in azimuth is especially relevant in the context of DBF, where individual channels need to be calibrated but are, by themselves, under-sampled. The calibration techniques presented are illustrated and validated using multi-channel polarimetric and single-pass interferometric SAR data acquired by DLR’s airborne F-SAR and DBFSAR instruments.

A New Single-Pass SAR Interferometry Technique with a Single-Antenna for Terrain Height Measurements

One of the prospective research topics in radar remote sensing technology is the methodology for designing an optimal radar system for high-precision two-dimensional and three-dimensional image acquisition of the Earth’s surface with minimal hardware requirements. In this study, we propose a single-pass interferometric synthetic aperture radar (SAR) imaging technique with only a single antenna for the estimation of the terrain height. This technique enabled us to obtain terrain height information in one flight of the carrier, on which only one receiving antenna was mounted. This single-antenna single-pass interferometry required a squint angle look geometry and additional image synthesis processing. The limiting accuracy of the terrain height measurement was approximately 1.5 times lower than that of the conventional two-pass mode and required a longer baseline than two-pass interferometry to have an equivalent accuracy performance. This imaging method could overcome the temporal decorrelation problem of two-pass interferometry due to a short time gap in the radar echo acquisitions during two sub-aperture intervals. We compared the accuracy performance of the terrain height measurements of our method with the conventional two-pass interferometry. This comparison was carried out at various spectral bandwidths, degrees of surface roughness, and baseline lengths. We validated our idea with numerical simulations of a digital elevation map, and showed real extracted data of the terrain heights in the Astrakhan and Volga regions of the Russian Federation, obtained from airborne SAR with our single-antenna single-pass interferometry technique.

High-Rise Building 3D Reconstruction with the Wrapped Interferometric Phase.

The great development of high-resolution SAR system gives more opportunities to observe building structures in detail, especially the advanced interferometric SAR (InSAR), which techniques attract more attention on exploiting useful information on urban infrastructures. Considering that the high-rise buildings in urban areas are quite common in big cities, it is of great importance to retrieve the three-dimension (3D) information of the urban high-rise buildings in urban remote sensing applications. In this paper, the 3D reconstruction of high-rise buildings using the wrapped InSAR phase image was studied, referring to the geometric modulation in very high resolution (VHR) SAR images, such as serious layover cause by high-rise buildings. Under the assumption of a rectangular shape, the high-rise buildings were detected and building façades were extracted based on the local frequency analysis of the layover fringe patterns. Then 3D information of buildings were finally extracted according to the detected façade geometry. Except for testing on a small urban area from the TanDEM-X data, the experiment carried on the single-pass InSAR wrapped phase in the wide urban scene, which was collected by the Chinese airborne N-SAR system, also demonstrated the possibility and applicability of the approach.

High-Resolution Forest Mapping from TanDEM-X Interferometric Data Exploiting Nonlocal Filtering

In this paper, we discuss the potential and limitations of high-resolution single-pass interferometric synthetic aperture radar (InSAR) data for forest mapping. In particular, we present forest/non-forest classification mosaics of the State of Pennsylvania, USA, generated using TanDEM-X data at ground resolutions down to 6 m. The investigated data set was acquired between 2011 in bistatic stripmap single polarization (HH) mode. Among the different factors affecting the quality of InSAR data, the so-called volume correlation factor quantifies the coherence loss due to volume scattering, which typically occurs in the presence of vegetation, and is a very sensitive indicator for the discrimination of forested from non-forested areas. For this reason, it has been chosen as input observable for performing the classification. In this framework, both standard boxcar and nonlocal filtering methods have been considered for the estimation of the volume correlation factor. The resulting forest/non-forest mosaics have been validated using an accurate vegetation map of the region derived from Lidar-Optic data as external independent reference. Thanks to their outstanding performance in terms of noise reduction, together with spatial features preservation, nonlocal filters show a level of agreement of about 80.5% and we observed a systematic improvement in terms of accuracy with respect to the boxcar filtering at the same resolution of about 4.5 percent points. This approach is therefore of primary importance to achieve a reliable classification at such fine resolution. Finally, the high-resolution forest/non-forest classification product of the State of Pennsylvania presented in this paper demonstrates once again the outstanding capabilities of the TanDEM-X system for a wide spectrum of commercial services and scientific applications in the field of the biosphere.

Research Pathways of Forest Above-Ground Biomass Estimation Based on SAR Backscatter and Interferometric SAR Observations

Estimation of forest biomass with synthetic aperture radar (SAR) and interferometric SAR (InSAR) observables has been surveyed in 186 peer-reviewed papers to identify major research pathways in terms of data used and retrieval models. Research evaluated primarily (i) L-band observations of SAR backscatter; and, (ii) single-image or multi-polarized retrieval schemes. The use of multi-temporal or multi-frequency data improved the biomass estimates when compared to single-image retrieval. Low frequency SAR backscatter contributed the most to the biomass estimates. Single-pass InSAR height was reported to be a more reliable predictor of biomass, overcoming the loss of sensitivity of SAR backscatter and coherence in high biomass forest. A variety of empirical and semi-empirical regression models relating biomass to the SAR observables were proposed. Semi-empirical models were mostly used for large-scale mapping because of the simple formulation and the robustness of the model parameters estimates to forest structure and environmental conditions. Non-parametric models were appraised for their capability to ingest multiple observations and perform accurate retrievals having a large number of training samples available. Some studies argued that estimating compartment biomass (in stems, branches, foliage) with different types of SAR observations would lead to an improved estimate of total biomass. Although promising, scientific evidence for such an assumption is still weak. The increased availability of free and open SAR observations from currently orbiting and forthcoming spaceborne SAR missions will foster studies on forest biomass retrieval. Approaches attempting to maximize the information content on biomass of individual data streams shall be pursued.

Optimum Baseline of a Single-Pass In-SAR System to Generate the Best DEM in Tidal Flats

Continuous monitoring of topographic heights and changes in tidal flats is challenging, as it is generally difficult to observe topographic changes from on-site measurements or remote sensing techniques with high resolution and high accuracy. In this regard, an interferometric synthetic aperture radar (In-SAR) can be an effective tool to generate precise digital elevation models (DEMs) and detect large-scale topographic changes. Nevertheless, utilizing the In-SAR to detect topographic changes in tidal flats is not practical because the average slope of tidal flats is usually less than 5°, and the overall spatial and temporal variations of height are not significant. Therefore, the accuracy of In-SAR DEMs must be high to detect meaningful topographic changes. In order to minimize the error of In-SAR DEMs, height of ambiguity and random phase deviation of interferograms should be taken into account. These two factors are related to incidence angle and baseline. We simulated topographic error levels in tidal flats for a single-pass In-SAR system such as TanDEM-X. Phase error of interferograms was derived using the relationship between In-SAR coherence and the probability density function of phase deviation. Signal-to-noise ratio and geometric decorrelation were formulated by the function of baseline, incidence angle, and surface slope. The simulation results show that the height error of the DEM was minimized to lower than 15 cm when the baseline was 1500 m with an incidence angle of 29° in the TanDEM-X system. Finally, the validation of simulation results was carried out by comparing them with TanDEM-X DEM accuracies in tidal flats.

Sea ice local surface topography from single-pass satellite InSAR measurements: a feasibility study

Abstract. Quantitative parameters characterizing the sea ice surface topography are needed in geophysical investigations such as studies on atmosphere–ice interactions or sea ice mechanics. Recently, the use of space-borne single-pass interferometric synthetic aperture radar (InSAR) for retrieving the ice surface topography has attracted notice among geophysicists. In this paper the potential of InSAR measurements is examined for several satellite configurations and radar frequencies, considering statistics of heights and widths of ice ridges as well as possible magnitudes of ice drift. It is shown that, theoretically, surface height variations can be retrieved with relative errors ≤ 0.5 m. In practice, however, the sea ice drift and open water leads may contribute significantly to the measured interferometric phase. Another essential factor is the dependence of the achievable interferometric baseline on the satellite orbit configurations. Possibilities to assess the influence of different factors on the measurement accuracy are demonstrated: signal-to-noise ratio, presence of a snow layer, and the penetration depth into the ice. Practical examples of sea surface height retrievals from bistatic SAR images collected during the TanDEM-X Science Phase are presented.

Mapping Snow Depth From Ka-Band Interferometry: Proof of Concept and Comparison With Scanning Lidar Retrievals

This letter presents the first demonstration of millimeter-wave single-pass interferometric synthetic aperture radar (InSAR) for snow-depth mapping. Maps are presented over the Tuolumne River Basin region of the Sierra Nevada, CA, USA, and compared with those collected by a scanning lidar onboard the NASA Airborne Snow Observatory for the same region on the same snow day. For this observation, the snow surface was wet and melting and as such penetration of the electromagnetic wave into the snow volume can be effectively neglected. Despite the rugged terrain, heavy tree-cover, and very low snow-volume, depth maps had a standard deviation <1 m with the largest differences occurring on slopes exceeding 40°. While additional evaluation is needed with demonstration of the InSAR capability over a greater range of conditions and terrain, these results are promising. InSAR for snow-depth mapping holds significant advantages for a spaceborne mission if proven viable as it can operate through cloud cover, day or night, and measure snowpack when wet or melting.

Biomass and InSAR height relationship in a dense tropical forest

In the present study we applied X-band interferometric SAR (InSAR) data from the TanDEM-X mission, and investigated the relationship between InSAR height above ground and above-ground biomass (AGB) in a forest with very high biomass. We carried out this study in the East Usambara Mountains in Tanzania, with AGB ranging up to >1000t/ha. Field inventory provided AGB data for 153 plots of 900m2 in size. An airborne laser scanning (ALS) provided a DTM as well as AGB predictions for larger 8100m2 cells over the entire study area. Three TanDEM-X acquisitions provided single-pass InSAR data, from which we generated a Digital Surface Models (DSM) and InSAR height by subtracting the ALS DTM. The results showed that proportionality may represent the relationship where AGB increased with 18.4t/ha per m increase in InSAR height. The accuracy was low with RMSE=203t/ha (44%), which was partly attributable to small field plots and partly to a limited sensitivity of InSAR height to variations in basal area and stand density. An identical proportionality model, with less residual noise, was achieved by replacing the small field plots with the 8100m2 cells having AGB predictions from ALS data.

Исследование точности однопроходного переднебокового РСА интерферометра при измерении рельефа поверхности Земли

Исследование точности однопроходного переднебокового РСА интерферометра при измерении рельефа поверхности Земли

Three‐dimensional deceptive scene generation against single‐pass InSAR based on coherent transponders

Single-pass interferometric synthetic aperture radar (InSAR) has strong anti-jamming capacity, and can eliminate the arbitrary jamming generated by single stationary transponder via dual-channel cancellation. In this study, a novel three-dimensional (3D) deceptive scene generation method against single-pass InSAR based on two coherent transponders is proposed. The deceptive signal of the proposed method at arbitrary location is composed by two complex components generated by the transponders. The complex scattering coefficient template modulated in each transponder is determined according to the relation between the deceptive interferometric phase template and the modulated complex scattering coefficient ratio of the two transponders. The 3D deceptive scene against single-pass InSAR is realised by generating jamming signal in each transponder via the fast deceptive jamming techniques against SAR. Simulation results of false point targets and 3D deceptive scene demonstrate the validity of the proposed method.

Estimation of Forest Biomass From Two-Level Model Inversion of Single-Pass InSAR Data

A model for aboveground biomass estimation from single-pass interferometric synthetic aperture radar (InSAR) data is presented. Forest height and canopy density estimates Δh and η <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> , respectively, obtained from two-level model (TLM) inversion, are used as biomass predictors. Eighteen bistatic VV-polarized TanDEM-X (TDM) acquisitions are used, made over two Swedish test sites in the summers of 2011, 2012, and 2013 (nominal incidence angle: 41°; height-of-ambiguity: 32-63 m) . Remningstorp features a hemiboreal forest in southern Sweden, with flat topography and where 32 circular plots have been sampled between 2010 and 2011 (area: 0.5 ha; biomass: 42-242 t/ha; height: 14-32 m) . Krycklan features a boreal forest in northern Sweden, 720-km north-northeast from Remningstorp, with significant topography and where 31 stands have been sampled in 2008 (area: 2.4-26.3 ha; biomass: 23-183 t/ha; height: 7-21 m) . A high-resolution digital terrain model has been used as ground reference during InSAR processing. For the aforementioned plots and stands and if the same acquisition is used for model training and validation, the new model explains 65%-89% of the observed variance, with root-mean-square error (RMSE) of 12%-19% (median: 15%) . By fixing two of the three model parameters, accurate biomass estimation can also be done when different acquisitions or different test sites are used for model training and validation, with RMSE of 12%-56% (median: 17%) . Compared with a simple scaling model computing biomass from the phase center elevation above ground, the proposed model shows significantly better performance in Remningstorp, as it accounts for the large canopy density variations caused by active management. In Krycklan, the two models show similar performance.