X-band Interferometric Synthetic Aperture Radar Research Articles

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).

TanDEM-X multiparametric data features in sea ice classification over the Baltic sea

ABSTRACT In this study, we assess the potential of X-band Interferometric Synthetic Aperture Radar imagery for automated classification of sea ice over the Baltic Sea. A bistatic SAR scene acquired by the TanDEM-X mission over the Bothnian Bay in March of 2012 was used in the analysis. Backscatter intensity, interferometric coherence magnitude, and interferometric phase have been used as informative features in several classification experiments. Various combinations of classification features were evaluated using Maximum likelihood (ML), Random Forests (RF) and Support Vector Machine (SVM) classifiers to achieve the best possible discrimination between open water and several sea ice types (undeformed ice, ridged ice, moderately deformed ice, brash ice, thick level ice, and new ice). Adding interferometric phase and coherence-magnitude to backscatter-intensity resulted in improved overall classification performance compared to using only backscatter-intensity. The RF algorithm appeared to be slightly superior to SVM and ML due to higher overall accuracies, however, at the expense of somewhat longer processing time. The best overall accuracy (OA) for three methodologies were achieved using combination of all tested features were 71.56, 72.93, and 72.91% for ML, RF and SVM classifiers, respectively. Compared to OAs of 62.28, 66.51, and 63.05% using only backscatter intensity, this indicates strong benefit of SAR interferometry in discriminating different types of sea ice. In contrast to several earlier studies, we were particularly able to successfully discriminate open water and new ice classes.

Morphometric attributes-based soil erosion susceptibility mapping in Dnyanganga watershed of India using individual and ensemble models

Identification of the sensitive regions to soil erosion can be the foremost step in controlling the vigorous pace of soil degradation in agricultural lands. This study employs individual and ensemble models including compound factor (CF), analytical hierarchy process (AHP), and technique for order preference by similarity to ideal solution-analytical hierarchy process (TOPSIS-AHP) for identifying the regions susceptible to soil erosion in Dnyanganga watershed of India using morphometric attributes (MAs). Thirteen MAs were computed using the newly released TanDEM-X data, which is a bi-static X-band interferometric Synthetic Aperture Radar (SAR) acquisition. Weights for each of the MAs were calculated using AHP, which was employed in both AHP and TOPSIS-AHP models. The outcome of the AHP model displays that watershed slope (Sw), stream frequency (Fu), ruggedness number (Rn), and relative relief (Rr) greatly influences soil erosion in the study area. The priority ranking outcome of individual and ensemble models are compared using the Spearman correlation coefficient test (SCCT) and Kendall tau correlation coefficient test (KTCCT) to select the best model for soil erosion susceptibility mapping. The result of the non-parametric tests reveals that TOPSIS-AHP ensemble model is better in ranking alternatives than the individual models. According to TOPSIS-AHP ensemble model, the sub-watershed DNY16 is highly susceptibility to erosion, whereas DNY1 is least susceptible. Based on the ensemble model, 14.54%, 41.02%, and 44.43% of the area in Dnyanganga watershed fall under high, medium and low soil erosion susceptible classes, respectively. The results from this study will aid decision makers in better conservation planning of soil and water resources.

Assessment of Mitigation Strategies for Tropospheric Phase Contributions to InSAR Time-Series Datasets over Two Nicaraguan Volcanoes

Interferometric Synthetic Aperture Radar (InSAR) studies of ground displacement are often plagued by tropospheric artifacts, which are phase delays resulting from spatiotemporal variations in the refractivity of air within the troposphere. In this study, we focus on COSMO-SkyMed (X-band) InSAR products obtained over two different types of volcanoes in Nicaragua: the Telica stratovolcano and the Masaya caldera. We examine the applicability of an empirical linear correction method and three Global Weather Models (GWMs) with different spatial and temporal resolutions for removing the tropospheric phase component. We linearly invert the tropospheric-corrected interferograms using the Small BAseline Subset (SBAS) time-series technique to produce time-series of ground displacement. Statistical assessments were performed on the corrected interferograms to examine the significance of the applied corrections on the individual interferograms and time-series results. We find that the applicability of the correction methods is highly case-dependent and that in general, the temporal resolution of GWMs influences their ability to capture turbulent tropospheric phase delays. At the two target volcanoes, our study shows that none of the GWMs are able to accurately capture the tropospheric phase delays. Our study provides a guide for researchers using InSAR data in tropical regions who wish to use tropospheric model corrections to carefully assess the applicability of the different types of tropospheric correction methods.

On the Capabilities of the Italian Airborne FMCW AXIS InSAR System

Airborne Synthetic Aperture Radar (SAR) systems are gaining increasing interest within the remote sensing community due to their operational flexibility and observation capabilities. Among these systems, those exploiting the Frequency-Modulated Continuous-Wave (FMCW) technology are compact, lightweight, and comparatively low cost. For these reasons, they are becoming very attractive, since they can be easily mounted onboard ever-smaller and highly flexible aerial platforms, like helicopters or unmanned aerial vehicles (UAVs). In this work, we present the imaging and topographic capabilities of a novel Italian airborne SAR system developed in the frame of cooperation between a public research institute (IREA-CNR) and a private company (Elettra Microwave S.r.l.). The system, which is named AXIS (standing for Airborne X-band Interferometric SAR), is based on FMCW technology and is equipped with a single-pass interferometric layout. In the work we first provide a description of the AXIS system. Then, we describe the acquisition campaign carried out in April 2018, just after the system completion. Finally, we perform an analysis of the radar data acquired during the campaign, by presenting a quantitative assessment of the quality of the SLC (Single Look Complex) SAR images and the interferometric products achievable through the system. The overall analysis aims at providing first reference values for future research and operational activities that will be conducted with this sensor.

Coseismic Slip Distribution of the 2019 Mw 7.5 New Ireland Earthquake from the Integration of Multiple Remote Sensing Techniques

The 2019 Mw 7.5 New Ireland earthquake occurred at an equatorial area where the dense vegetation prevents remote sensing techniques such as C- or X-band interferometric synthetic aperture radar (SAR) from acquiring coherent phase measurements. Therefore, in this paper, multiple remote sensing techniques including the L-band interferometric SAR, the range and azimuth offset tracking of SAR intensities, and the offset tracking of optical images were employed to map its co-seismic deformation field and to determine the slip distribution. The surface rupture was clearly and consistently captured by all offset observations, with the ground fault trace striking at an angel of 315° and extending over 10 km. An iterative weighting strategy based on the residual root mean square of inversions using individual datasets was developed to determine the relative weight of each dataset, allowing for the joint inversion of the fault geometry, the refinement of the dip angle, and the determination of the best fitting slip distribution. The resultant model indicates a nearly left-lateral strike-slip motion on the Weitin fault that ruptured to the surface with a maximum slip of 6.10 m, occurring at a depth of ~10 km, and a geodetic moment release of 1.03 × 1020 Nm, corresponding to a magnitude of Mw 7.31. The distribution of aftershocks shows about 70% of aftershocks were located in the area with increased Coulomb failure stress and few aftershocks in the subduction zone to the south of the Weitin fault were triggered by this event.

Canopy penetration depth estimation with TanDEM-X and its compensation in temperate forests

The potential of X-band interferometric synthetic aperture radar (InSAR) heights (e.g. from the TanDEM-X mission) for vegetation canopy height estimation has long been recognized. However, the penetration of the X-band into the canopy results in a height bias and substantially affects this estimation. The aim of the study was to apply a physical model to compensate the penetration depth (i.e. height bias) in canopy height estimation and evaluate its performance. We applied a penetration depth model on different TanDEM-X data in three German forests. This model is based on the volume coherence and imaging geometry of the InSAR acquisitions. We extracted the volume coherence from the TanDEM-X data and retrieved the height bias based on the penetration depth compared to actual surface heights. The modeled height bias was used to compensate the height bias in InSAR heights. The corrected TanDEM-X heights were evaluated with LiDAR data. In general, the penetration depth compensation in the InSAR heights improved the performance compared to the original InSAR heights resulting in elevations with a lower root mean squared error and the mean error decreased to less than 1 m with the LiDAR heights used as reference. This suggested that the height bias was accurately modeled for temperate forests, which can be of high relevance when InSAR heights are used for canopy height estimation or used in multi-temporal analysis such as forest growth, degradation and deforestation monitoring.

L-Band Temporal Coherence Assessment and Modeling Using Amplitude and Snow Depth over Interior Alaska

Interferometric synthetic aperture radar (InSAR) provides the capability to detect surface deformation. Numerous processing approaches have been developed to improve InSAR results and overcome its limitations. Regardless of the processing methodology, however, temporal decorrelation is a major obstacle for all InSAR applications, especially over vegetated areas and dynamic environments, such as Interior Alaska. Temporal coherence is usually modeled as a univariate exponential function of temporal baseline. It has been, however, documented that temporal variations in surface backscattering due to the change in surface parameters, i.e., dielectric constant, roughness, and the geometry of scatterers, can result in gradual, seasonal, or sudden decorrelations and loss of InSAR coherence. The coherence models introduced so far have largely neglected the effect of the temporal change in backscattering on InSAR coherence. Here, we introduce a new temporal decorrelation model that considers changes in surface backscattering by utilizing the relative change in SAR intensity between two images as a proxy for the change in surface scattering parameters. The model also takes into account the decorrelation due to the change in snow depth between two images. Using the L-band Advanced Land Observation Satellite (ALOS-2) Phased Array type L-band Synthetic Aperture Radar (PALSAR-2) data, the model has been assessed over forested and shrub landscapes in Delta Junction, Interior Alaska. The model decreases the RMS error of temporal coherence estimation from 0.18 to 0.09 on average. The improvements made by the model have been statistically proved to be significant at the 99% confidence level. Additionally, the model shows that the coherence of forested areas are more prone to changes in backscattering than shrub landscape. The model is based on L-band data and may not be expanded to C-band or X-band InSAR observations.

Analysis of X‐band PolInSAR coherence characteristics in forested areas

The X-band coherence statistical characteristics related to the height of ambiguity, polarisation and resolution in two typical forested areas are investigated, using X-band multi-baseline polarimetric synthetic aperture radar interferometry (PolInSAR) data acquired by an automobile-based interferometric synthetic aperture radar (InSAR) system. The influences of the polarisation and resolution on coherence are carefully analysed. The results show that the volume decorrelation in forested areas is independent of the polarisation and the coherence decreases with the reduction of the resolution. In addition, an empirical coherence model in relation to the height of ambiguity, resolution, forest height and range slope is proposed, according to the coherence statistical characteristics of the experimental data. The model can be used to calculate the mean coherence of forested areas under a specific system baseline and therefore it can play an important role in X-band InSAR baseline configuration for forest mapping.

An unsupervised two-stage clustering approach for forest structure classification based on X-band InSAR data — A case study in complex temperate forest stands

Forest structure at stand level plays a key role for sustainable forest management, since the biodiversity, productivity, growth and stability of the forest can be positively influenced by managing its structural diversity. In contrast to field-based measurements, remote sensing techniques offer a cost-efficient opportunity to collect area-wide information about forest stand structure with high spatial and temporal resolution. Especially Interferometric Synthetic Aperture Radar (InSAR), which facilitates worldwide acquisition of 3d information independent from weather conditions and illumination, is convenient to capture forest stand structure. This study purposes an unsupervised two-stage clustering approach for forest structure classification based on height information derived from interferometric X-band SAR data which was performed in complex temperate forest stands of Traunstein forest (South Germany). In particular, a four dimensional input data set composed of first-order height statistics was non-linearly projected on a two-dimensional Self-Organizing Map, spatially ordered according to similarity (based on the Euclidean distance) in the first stage and classified using the k-means algorithm in the second stage. The study demonstrated that X-band InSAR data exhibits considerable capabilities for forest structure classification. Moreover, the unsupervised classification approach achieved meaningful and reasonable results by means of comparison to aerial imagery and LiDAR data.

A NEW HIGH-RESOLUTION ELEVATION MODEL OF GREENLAND DERIVED FROM TANDEM-X

Abstract. In this paper we present for the first time the new digital elevation model (DEM) for Greenland produced by the TanDEM-X (TerraSAR add-on for digital elevation measurement) mission. The new, full coverage DEM of Greenland has a resolution of 0.4 arc seconds corresponding to 12 m. It is composed of more than 7.000 interferometric synthetic aperture radar (InSAR) DEM scenes. X-Band SAR penetrates the snow and ice pack by several meters depending on the structures within the snow, the acquisition parameters, and the dielectricity constant of the medium. Hence, the resulting SAR measurements do not represent the surface but the elevation of the mean phase center of the backscattered signal. Special adaptations on the nominal TanDEM-X DEM generation are conducted to maintain these characteristics and not to raise or even deform the DEM to surface reference data. For the block adjustment, only on the outer coastal regions ICESat (Ice, Cloud, and land Elevation Satellite) elevations as ground control points (GCPs) are used where mostly rock and surface scattering predominates. Comparisons with ICESat data and snow facies are performed. In the inner ice and snow pack, the final X-Band InSAR DEM of Greenland lies up to 10 m below the ICESat measurements. At the outer coastal regions it corresponds well with the GCPs. The resulting DEM is outstanding due to its resolution, accuracy and full coverage. It provides a high resolution dataset as basis for research on climate change in the arctic.

A NEW HIGH-RESOLUTION ELEVATION MODEL OF GREENLAND DERIVED FROM TANDEM-X

In this paper we present for the first time the new digital elevation model (DEM) for Greenland produced by the TanDEM-X (TerraSAR add-on for digital elevation measurement) mission. The new, full coverage DEM of Greenland has a resolution of 0.4 arc seconds corresponding to 12 m. It is composed of more than 7.000 interferometric synthetic aperture radar (InSAR) DEM scenes. X-Band SAR penetrates the snow and ice pack by several meters depending on the structures within the snow, the acquisition parameters, and the dielectricity constant of the medium. Hence, the resulting SAR measurements do not represent the surface but the elevation of the mean phase center of the backscattered signal. Special adaptations on the nominal TanDEM-X DEM generation are conducted to maintain these characteristics and not to raise or even deform the DEM to surface reference data. For the block adjustment, only on the outer coastal regions ICESat (Ice, Cloud, and land Elevation Satellite) elevations as ground control points (GCPs) are used where mostly rock and surface scattering predominates. Comparisons with ICESat data and snow facies are performed. In the inner ice and snow pack, the final X-Band InSAR DEM of Greenland lies up to 10 m below the ICESat measurements. At the outer coastal regions it corresponds well with the GCPs. The resulting DEM is outstanding due to its resolution, accuracy and full coverage. It provides a high resolution dataset as basis for research on climate change in the arctic.

The InSAeS4 Airborne X-Band Interferometric SAR System: A First Assessment on Its Imaging and Topographic Mapping Capabilities

We present in this work a first assessment of the imaging and topographic mapping capabilities of the InSAeS4 system, which is a single-pass interferometric airborne X-Band Synthetic Aperture Radar (SAR). In particular, we first provide a brief description of the InSAeS4 sensor. Then, we discuss the results of our analysis on the SAR and interferometric SAR products relevant to the first flight-test campaign. More specifically, we have exploited as reference the GPS measurements relevant to nine Corner Reflectors (CRs) deployed over the illuminated area during the campaign and a laser scanner Digital Elevation Model (DEM). From the analysis carried out on the CRs we achieved a mean geometric resolution, for the SAR products, of about 0.14 m in azimuth and 0.49 m in range, a positioning misalignment with standard deviation of 0.07 m in range and 0.08 m in azimuth, and a height error with standard deviation of 0.51 m. From the comparison with the laser scanner DEM we estimated a height error with standard deviation of 1.57 m.

Tropical-Forest Biomass Estimation at X-Band From the Spaceborne TanDEM-X Interferometer

This letter reports the sensitivity of X-band interferometric synthetic aperture radar (InSAR) data from the first dual-spacecraft radar interferometer, TanDEM-X, to variations in tropical-forest aboveground biomass (AGB). It also reports the first tropical-forest AGB estimates from TanDEM-X data. Tropical forests account for about 50% of the world's forested biomass and play critical roles in the control of atmospheric carbon dioxide by emission through deforestation and uptake through forest growth. The TanDEM-X InSAR data used in this analysis were taken over the Tapajos National Forest, Para, Brazil, where field measurements from 30 stands were acquired. The magnitude of the InSAR normalized complex correlation, which is called coherence, decreases by about 25% as AGB increases from 2 to 430 Mg-ha -1 , suggesting more vertically distributed return-power profiles with increasing biomass. Comparison of InSAR coherences to those of small-spot (15 cm) lidar suggests that lidar penetrates deeper into the canopies than InSAR. Modeling InSAR profiles from InSAR coherence and lidar profiles yields an estimate of 0.29 dB/m for the X-band extinction coefficient relative to that of lidar. Forest AGB estimated from InSAR observations on 0.25-ha plots shows RMS scatters about the field-estimated AGB between 52 and 62 Mg-ha -1 , which is between 29% and 35% of the average AGB of 179 Mg-ha -1 , depending on the data analysis mode. The sensitivity and biomass-estimation performance suggest the potential of TanDEM-X observations to contribute to global tropical-forest biomass monitoring.

DEM generation and error analysis using the first Chinese airborne dual-antenna interferometric SAR data

Terrain survey with traditional photogrammetry is often difficult in western China, such as Qingzang tableland at an average height of 5000 m above sea level and the southwest China area with cloudy weather. To resolve western terrain mapping, the first Chinese single-pass airborne Interferometric Synthetic Aperture Radar (InSAR) system was successfully developed by the Institute of Electronics, Chinese Academy of Sciences (IECAS) in 2004. The main objective of this article is to examine and evaluate the performance of the airborne SAR system through interferometric processing and error analysis. First, the article describes how high-precision digital elevation models (DEMs) are derived from the airborne dual-antenna (single-pass) InSAR data. In order to improve the precision, the antenna eccentricity correction and parameter calibration with the least square method (LSM) are proposed. Based on the airborne dual-antenna InSAR bore-sight model, this article summarizes the primary factors that influence the accuracy of DEMs in data processing, and analyses the errors induced by these factors. Then, the global positioning system (GPS)/inertial measurement unit (IMU) data, acquired and stored by the position and orientation system (POS), is used for analysing the quantitative relationships among the platform height, baseline length, baseline angle, look angle and DEM error. The experimental data used are airborne dual-antenna X-band InSAR data, and the measured ground control points (GCPs) are used to validate the accuracy of the DEM. The evaluation results in terms of the standard deviation (SD) and the average mean error (AME) are derived by comparing the reconstructed InSAR DEM with the reference GCPs. The AMEs of the X-direction, the Y-direction and the height are up to 2.078, 9.149 and 1.763 m, respectively. The SDs of the X-direction, the Y-direction and the height are up to ±1.379, ±0.764 and ±1.086 m, respectively. These results agree with the previously calculated quantitative errors. The error value of the Y-direction seems too large, a possible result of system errors. In general, the airborne dual-antenna InSAR system initially meets the requirements of 1:50 000 terrain mapping in western China.

Current measurements by SAR along-track interferometry from a Space Shuttle

We present one of the first studies on ocean current retrievals from interferometric synthetic aperture radar (InSAR) data acquired during the Shuttle Radar Topography Mission (SRTM) in February 2000. The InSAR system of SRTM was designed for high-resolution topographic mapping of the Earth's land surfaces, using two SAR antennas on a Space Shuttle with a cross-track separation of 60 m. An additional along-track antenna separation of 7 m resulted in an effective time lag of about 0.5 ms between the two images, which could theoretically be exploited for target velocity retrievals. However, the feasibility of ocean current measurements with SRTM has been questionable, since the time lag was much shorter than the theoretical optimum (about 3 ms at X-band) and the signal-to-noise ratio over water was quite low. Nevertheless, some X-band InSAR images of coastal areas exhibit clear signatures of tidal flow patterns. As an example, we discuss an image of the Dutch Wadden Sea. We convert the InSAR data into a line-of-sight current field, which is then compared with results of the numerical circulation model KUSTWAD. For tidal phases close to the conditions at the time of the SRTM overpass; we obtain correlation coefficients of up to 0.6 and rms differences on the order of 0.2 m/s. Furthermore we find that SRTM resolves current variations down to spatial scales on the order of 1 km. This is consistent with predictions of a numerical InSAR imaging model. Remaining differences between SRTM- and KUSTWAD-derived currents can be attributed mainly to residual motion errors in the SRTM data as well as to a limited representation of the conditions at the time of the SRTM overpass in the available KUSTWAD results.