Interferometric Synthetic Aperture Radar Digital Elevation Models 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.

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.

Integration of an InSAR and ANN for Sinkhole Susceptibility Mapping: A Case Study from Kirikkale-Delice (Turkey)

Suitable route determination for linear engineering structures is a fundamental problem in engineering geology. Rapid evaluation of alternative routes is essential, and novel approaches are indispensable. This study aims to integrate various InSAR (Interferometric Synthetic Aperture Radar) techniques for sinkhole susceptibility mapping in the Kirikkale-Delice Region of Turkey, in which sinkhole formations have been observed in evaporitic units and a high-speed train railway route has been planned. Nine months (2019–2020) of ground deformations were determined using data from the European Space Agency’s (ESA) Sentinel-1A/1B satellites. A sinkhole inventory was prepared manually using satellite optical imagery and employed in an ANN (Artificial Neural Network) model with topographic conditioning factors derived from InSAR digital elevation models (DEMs) and morphological lineaments. The results indicate that high deformation areas on the vertical displacement map and sinkhole-prone areas on the sinkhole susceptibility map (SSM) almost coincide. InSAR techniques are useful for long-term deformation monitoring and can be successfully associated in sinkhole susceptibility mapping using an ANN. Continuous monitoring is recommended for existing sinkholes and highly susceptible areas, and SSMs should be updated with new results. Up-to-date SSMs are crucial for the route selection, planning, and construction of important transportation elements, as well as settlement site selection, in such regions.

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.

Glacier mass and area changes on the Kenai Peninsula, Alaska, 1986–2016

AbstractGlacier mass loss in Alaska has implications for global sea level rise, fresh water input into the Gulf of Alaska and terrestrial fresh water resources. We map all glaciers (&gt;4000 km2) on the Kenai Peninsula, south central Alaska, for the years 1986, 1995, 2005 and 2016, using satellite images. Changes in surface elevation and volume are determined by differencing a digital elevation model (DEM) derived from Advanced Spaceborne Thermal Emission and Reflection Radiometer stereo images in 2005 from the Interferometric Synthetic Aperture Radar DEM of 2014. The glacier area shrunk by 543 ± 123 km2(12 ± 3%) between 1986 and 2016. The region-wide mass-balance rate between 2005 and 2014 was −0.94 ± 0.12 m w.e. a−1(−3.84 ± 0.50 Gt a−1), which is almost twice as negative than found for earlier periods in previous studies indicating an acceleration in glacier mass loss in this region. Area-averaged mass changes were most negative for lake-terminating glaciers (−1.37 ± 0.13 m w.e. a−1), followed by land-terminating glaciers (−1.02 ± 0.13 m w.e. a−1) and tidewater glaciers (−0.45 ± 0.14 m w.e. a−1). Unambiguous attribution of the observed acceleration in mass loss over the last decades is hampered by the scarcity of observational data, especially at high elevation, and by large interannual variability.

Bare Earth DEM Generation for Large Floodplains Using Image Classification in High-Resolution Single-Pass InSAR

The increasing frequency and severity of flood events demand improved accuracy of hydrodynamic models to better mitigate the societal and economic consequences of these disasters. Ideally, these models derive elevation data from high-accuracy LiDAR, which often captures the subtle variations in elevation and microtopography—elements that are critical to high-resolution hydrodynamic modeling. Due largely to the cost of acquisitions, these data, however, are not widely available at high spatial resolutions for large-scale areas, i.e. floodplains and coastal regions, especially outside of the U.S. and Western Europe, where flood-prone communities already lack the infrastructure and resources to manage these disasters. High-resolution interferometric synthetic aperture radar (InSAR) systems may offer a viable and cost-effective alternative to LiDAR, with comparable spatial resolutions and vertical accuracies. Like any swath mapping sensor, systematic errors in calibration knowledge increase as the lever-arm increases when viewing further off vertical. InSAR-derived digital elevation models (DEMs) are often corrected using LiDAR or ground control points, although this limits the application of InSAR to those areas where these data exist. In this paper, we present a novel approach for using near-range InSAR data to correct inherent systematic bias that propagates across adjacent, overlapping swaths for the same airborne acquisition. This eliminates the need for LiDAR in generating InSAR DEMs, while maintaining a vertical error of approximately 0.26 m relative to LiDAR, at a spatial resolution of 30 m. Data was acquired using the NASA/JPL airborne, single-pass, Ka-band GLISTIN-A (Glacier and Ice Surface Topography Interferometer) InSAR over the Red River Basin (RRB), ND. The accuracy of the final DEM is evaluated using National Geodetic Survey (NGS) GPS and a high-resolution LiDAR DEM.

A Framework for Correcting Ionospheric Artifacts and Atmospheric Effects to Generate High Accuracy InSAR DEM

Repeat-pass interferometric synthetic aperture radar is a well-established technology for generating digital elevation models (DEMs). However, the interferogram usually has ionospheric and atmospheric effects, which reduces the DEM accuracy. In this paper, by introducing dual-polarization interferograms, a new approach is proposed to mitigate the ionospheric and atmospheric errors of the interferometric synthetic aperture radar (InSAR) data. The proposed method consists of two parts. First, the range split-spectrum method is applied to compensate for the ionospheric artifacts. Then, a multiresolution correlation analysis between dual-polarization InSAR interferograms is employed to remove the identical atmospheric phases, since the atmospheric delay is independent of SAR polarizations. The corrected interferogram can be used for DEM extraction. Validation experiments, using the ALOS-1 PALSAR interferometric pairs covering the study areas in Hawaii and Lebanon of the U.S.A., show that the proposed method can effectively reduce the ionospheric artifacts and atmospheric effects, and improve the accuracy of the InSAR-derived DEMs by 64.9% and 31.7% for the study sites in Hawaii and Lebanon of the U.S.A., respectively, compared with traditional correction methods. In addition, the assessment of the resulting DEMs also includes comparisons with the high-precision Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) altimetry data. The results show that the selection of reference data will not affect the validation results.

High-Resolution Elevation Model of Lop Nur Playa Derived from TanDEM-X

In this paper, a digital elevation model (DEM) was produced for Lop Nur playa produced with the data from TanDEM-X mission. The spatial resolution is 10 m. It covers an area of 38,000 km2for orthometric height from 785 m to 900 m above sea level, which is composed of 42 interferometric synthetic aperture radar (InSAR) scenes. A least-square adjustment approach was used to reduce the systematic errors in each DEM scene. The DEM produced was validated with data from other sensors including Ice, Cloud, and land Elevation Satellite (ICESat) Geoscience Laser Altimeter System (GLAS) and aerial Structure-from-Motion (SfM) DEM. The results show that global elevation root mean square error to GLAS is 0.57 m, and the relative height error to SfM DEM in complicated terrain is 3 m. The excellent height reliability of TanDEM InSAR DEM in Lop region was proved in this paper. A reliable high-resolution basic topographic dataset for researches of Lop Nur was provided.

Using Dual-Polarization Interferograms to Correct Atmospheric Effects for InSAR Topographic Mapping

Atmospheric effect represents one of the major error sources for interferometric synthetic aperture radar (InSAR), particularly for the repeat-pass InSAR data. In order to further improve the practicability of InSAR technology, it is essential to study how to estimate and eliminate the undesired impact of atmospheric effects. In this paper, we propose the multi-resolution weighted correlation analysis (MRWCA) method between the dual-polarization InSAR data to estimate and correct atmospheric effects for InSAR topographic mapping. The study is based on the a priori knowledge that atmospheric effects is independent of the polarization. To find the identical atmospheric phase (ATP) signals of interferograms in different polarizations, we need to remove the other same or similar phase components. Using two different topographic data, differential interferometry was firstly performed so that the obtained differential interferograms (D-Infs) have different topographic error phases. A polynomial fitting method is then used to remove the orbit error phases. Thus, the ATP signals are the only identical components in the final obtained D-Infs. By using a forward wavelet transform, we break down the obtained D-Infs into building blocks based on their frequency properties. We then applied weighted correlation analysis to estimate the wavelet coefficients attributed to the atmospheric effects. Thus, the ATP signals can be obtained by the refined wavelet coefficients during inverse wavelet transform (IWT). Lastly, we tested the proposed method by the L-band Advanced Land Observing Satellite (ALOS)-1 PALSAR dual-polarization SAR data pairs covering the San Francisco (USA) and Moron (Mongolia) regions. By using Ice, Cloud, and land Elevation Satellite (ICESat) data as the reference data, we evaluated the vertical accuracy of the InSAR digital elevation models (DEMs) with and without atmospheric effects correction, which shows that, for the San Francisco test site, the corrected interferogram could provide a DEM with a root-mean-square error (RMSE) of 7.79 m, which is an improvement of 40.5% with respect to the DEM without atmospheric effects correction. For the Moron test site, the corrected interferogram could provide a DEM with an RMSE of 10.74 m, which is an improvement of 30.2% with respect to the DEM without atmospheric effects correction.

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.

A Wavelet Decomposition and Polynomial Fitting-Based Method for the Estimation of Time-Varying Residual Motion Error in Airborne Interferometric SAR

Compensating the residual motion error (RME) is very important in airborne interferometric synthetic aperture radar (InSAR). In this paper, the wavelet decomposition and polynomial fitting-based (WDPF) method is proposed for detecting and correcting the RME. Wavelet decomposition with root-mean-square error (RMSE) change ratio-based decomposition scale identification is used to detect the RME from the differential interferogram. Polynomial fitting in combination with robust estimation-based least squares is used to absorb the incidence-angle-dependent and topography-dependent components of the RME. A simulated experiment was conducted to test the proposed WDPF method. High-precision RME (with an RMSE of 0.0375 rad) was obtained, which can meet the requirements of InSAR. Real-data L- and P-band InSAR experiments were also performed to test the WDPF method. The results confirmed that the WDPF method can effectively correct the RME for the interferogram. The RMSE of the estimated digital elevation model (DEM) was reduced from 8.03 to 3.46 m and 8.18 to 3.10 m for the L- and P-band interferograms, respectively. Finally, the effects of the external DEM error and polarization on the RME calibration were investigated. The results indicated that the global InSAR DEM products can fulfill the requirement of differential interferogram generation for the WDPF method, and the multipolarization interferograms can help to reduce the effect of the topographic error phase on RME estimation.

Comparison and Validation of Digital Elevation Models Derived from InSAR for a Flat Inland Delta in the High Latitudes of Northern Canada

Inaccuracies in topographic data can be a significant source of error and uncertainty for hydrologic, atmospheric-land exchange and climate change modeling. This study was conducted to examine how different data sources and techniques used to generate digital elevation models (DEM) influence DEM accuracy. Using the interferometric synthetic aperture radar (InSAR) technique, the system acquisition parameters and the topographic characteristics are important factors in determining DEM quality. ICESat elevation footprints and highly accurate ground control points (based on GPS measurements) are used as independent references to validate the accuracy of DEMs. The TanDEM-X DEM shows the highest accuracy among all studied DEM products, with the root mean square error (RMSE) of 2.9 m, followed by 3.3 m for Canadian digital elevation data, 5.2 m for ASTER-GDEM, and 5.5 m for ALOS-PALSAR DEM. The RMSEs of the RADARSAT-2 based InSAR DEM and global GTOPO30 are considerably higher than the other DEMs, 24 m and 36 m, respectively. The interferograms of RADARSAT-2 and ALOS-PALSAR data acquired in early winter resulted in higher DEM accuracy compared with the summer image pairs, even with their lower InSAR coherence. This is attributed to the higher importance of perpendicular baseline and height of ambiguity and potentially the significant influence of atmospheric phase delay in DEM generation. We also compared the accuracy of DEMs of different land cover types and their representation of the land-water surface. The results show that vegetated areas of coniferous and broadleaf trees (i.e., white and black spruce, trembling aspen, balsam poplar) seem to be the main sources of error in all DEMs. The river slopes derived from the TanDEM-X, ASTER, and ALOS-PALSAR DEMs show patterns consistent with the river bed slope from our river bathymetry survey. Further studies are necessary to evaluate the performance of those different DEMs in earth surface modeling as well as to improve the quality of high error DEMs such as RADARSAT-2 data in this study. The Slave River Delta in the Northwest Territories of Canada was used as a test case.

Improving the quality of interferometric synthetic aperture radar digital elevation models through a segmentation-based coregistration approach

With the rapid development of remote sensing, multiple techniques are now capable of producing digital elevation models (DEMs), such as photogrammetry, Light Detection and Ranging (LiDAR), and interferometric synthetic aperture radar (InSAR). Satellite-derived InSAR DEMs are particularly attractive due to their advantages of large spatial extents, cost-effectiveness, and less dependence on the weather. However, several complex factors may limit the quality of derived DEMs, e.g., the inherited errors may be nonlinear and spatially variable over an entire InSAR pair scene. We propose a segmentation-based coregistration approach for generating accurate InSAR DEMs over large areas. Two matching algorithms, including least squares matching and iterative closest point, are integrated in this approach. Three Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar (ALOS PALSAR) InSAR DEMs are evaluated, and their root mean square errors (RMSEs) improved from 17.87 to 9.98 m, 51.94 to 15.80 m, and 27.12 to 12.26 m. Compared to applying a single global matching strategy, the segmentation-based strategy further improved the RMSEs of the three DEMs by 3.27, 13.01, and 9.70 m, respectively. The results clearly demonstrate that the segmentation-based coregistration approach is capable of improving the geodetic quality of InSAR DEMs.

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.

Improving InSAR elevation models in Antarctica using laser altimetry, accounting for ice motion, orbital errors and atmospheric delays

Ice dynamics is closely related to climate change. However, a lack of digital elevation models (DEMs) of sufficient horizontal resolution and vertical precision has been a major issue in dynamic studies for years. Existing Antarctic DEMs are derived from satellite radar and laser altimetry as well as limited terrestrial data; these sparse datasets result in poor spatial resolution (hundreds of metres to 1km). In this paper, we propose a method for generating high-accuracy and high-resolution DEMs using interferometric synthetic aperture radar (InSAR) and Ice, Cloud and land Elevation Satellite (ICESat) laser altimetry by reducing the influence of ice motion, satellite orbital errors and topographically correlated atmospheric delays. A case study in the Grove Mountains area shows that the InSAR DEM has a root-mean-square (RMS) error of 5.9m, which is better than the Radarsat Antarctic Mapping Project (RAMP) (21.1m) and Bamber (8.5m) DEMs. The new DEM is used to calculate ice velocity over the Grove Mountains area where GPS measurements have been collected for comparison. Compared to the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) InSAR-Based Antarctica Ice Velocity Map, ice velocity estimates from long-baseline interferogram and the new DEM have a smaller RMS error; this suggests that with the new DEM, baseline length is no longer a limiting factor for the accuracy of InSAR-based ice velocity mapping.

InSAR Image Regularization and DEM Error Correction With Fractal Surface Scattering Model

This paper presents a method for removing spikes in digital elevation models (DEMs) caused by residues in interferometric synthetic aperture radar (InSAR) phase image. We consider that the scattering mechanism is properly modeled by the small perturbation method for fractal surfaces and present a model that relates the phase and magnitude in InSAR image. This data model provides the regularization term of the method, without directly enforcing smooth phase or magnitude. Noise models are given by additive Gaussian for the phase and multiplicative non-unit-mean gamma for the magnitude. Experiments with simulated and real L-band data show that the proposed method considerably improves DEM accuracy and simultaneously suppresses speckle and phase noise.

Fusion of high-resolution DEMs derived from COSMO-SkyMed and TerraSAR-X InSAR datasets

Voids caused by shadow, layover, and decorrelation usually occur in digital elevation models (DEMs) of mountainous areas that are derived from interferometric synthetic aperture radar (InSAR) datasets. The presence of voids degrades the quality and usability of the DEMs. Thus, void removal is considered as an integral part of the DEM production using InSAR data. The fusion of multiple DEMs has been widely recognized as a promising way for the void removal. Because the vertical accuracy of multiple DEMs can be different, the selection of optimum weights becomes a key problem in the fusion and is studied in this article. As a showcase, two high-resolution InSAR DEMs near Mt. Qilian in northwest China are created and then merged. The two pairs of InSAR data were acquired by TerraSAR-X from an ascending orbit and COSMO-SkyMed from a descending orbit. A maximum likelihood fusion scheme with the weights optimally determined by the height of ambiguity and the variance of phase noise is adopted to syncretize the two DEMs in our study. The fused DEM has a fine spatial resolution of 10 m and depicts the landform of the study area well. The percentage of void cells in the fused DEM is only 0.13 %, while 6.9 and 5.7 % of the cells in the COSMO-SkyMed DEM and the TerraSAR-X DEM are originally voids. Using the ICESat/GLAS elevation data and the Chinese national DEM of scale 1:50,000 as references, we evaluate vertical accuracy levels of the fused DEM as well as the original InSAR DEMs. The results show that substantial improvements could be achieved by DEM fusion after atmospheric phase screen removal. The quality of fused DEM can even meet the high-resolution terrain information (HRTI) standard.

High precision DEM generation using airborne dual-antenna InSAR data：A case study of large hilly areas

The airborne interferometric synthetic aperture Radar( InSAR) is a new technique for generating digital elevation model( DEM) with high accuracy. To generate high precision DEMs in large areas,this paper introduces accurate parameter calibration and bundle adjustment to the pre existing data processing flow of airborne InSAR DEMs generation,and presents a novel method and procedure for massive high precision DEMs generation by using airborne dual- antenna InSAR data of hilly areas, which includes parameter calibration, interferometric processing,bundle adjustment,phase- to- height conversion,geo coding and mosaicking. The airborne InSAR for the topography mapping processing system has been exploited based on the VC + +. Some experimental research is presented based on airborne dual- antenna X- band InSAR data of 4 stripes. The authors processed and generated a high precision DEM covering an area of over 500 km2. Several corner reflectors were placed in this area as reference GCPs for the assessment of the accuracy of the generated DEM. The evaluation results in terms of the mean square error( MSE) were derived by comparing the generated InSAR DEM with the reference GCPs. The MSE of the point and the height are ± 1. 188 m and ± 0. 508 m,respectively. It is concluded that the generated DEM using the proposed method meets the requirements of 1∶ 10 000 terrain mapping. The airborne InSAR system could provide a new technique for topographic mapping in large complex areas.

Geodetic Mass Balance of Glaciers in the Central Brooks Range, Alaska, U.S.A., from 1970 to 2001

Alaska’s arctic glaciers have retreated and thinned during recent decades, and glaciers in the central Brooks Range are no exception. Digital elevation models (DEMs) reconstructed from topographic maps (from 1970 and 1973) were differenced from a 2001 interferometric synthetic aperture radar DEM to calculate the volume and mass changes of 107 glaciers covering 42 km2 (1970/1973) in the central Brooks Range, Alaska, U.S.A. For each glacier the 1970/1973 DEM was 3-D co-registered (horizontal and vertical) to maximize agreement between the non-glacierized terrains of both DEMs. Over the period 1970–2001, total ice volume loss was 0.69 ± 0.06 km3 corresponding to a mean (area-weighted) specific mass balance rate of -0.54 ± 0.05 m w.e. a-1 (± uncertainty). The arithmetic mean of all glaciers’ specific mass balance rates was -0.47 ± 0.27 m w.e. a-1 (± 1 std. dev.). A value of -0.52 ± 0.36 m w.e. a-1 (± 1 std. dev.) was found when 3-D coregistration is performed over the entire domain instead of individually for each glacier, indicating the importance of proper co-registration. Glacier area, perimeter, boundary compactness, mean elevation, and mean slope were correlated with specific balance rates, suggesting that large, low-elevation, elongated and shallow sloped glaciers had more negative balance rates than small, high-elevation, circular, and steep glaciers. A subsample of 36 glaciers showed a mean area reduction of 26 ± 16% (±1 std. dev.) over ∼35 years.