Baseline Estimation Using DEM Prior Knowledge and Capability Analysis for Gaofen-3 Repeat-Pass SAR Interferometry

Comparison and Validation of Different DEM Data Derived from InSAR

GaoFen-3 (GF-3) is the first fully polarimetric C-band synthetic aperture radar (SAR) satellite in China. Interferometric observation is an important capability of GF-3. However, the long temporal baseline is a great challenge for repeat-pass interferometric synthetic aperture radar (InSAR) processing, especially over mountainous areas. Phase noise and complex topography make phase unwrapping difficult. This paper proposes a step-wise approach for high-resolution InSAR data processing focusing on facilitating phase unwrapping. First, the coarse GF-3 digital elevation model (DEM) is reconstructed by InSAR processing with multilooking of large looks, which is used to suppress phase noise. Second, the coarse GF-3 DEM is used to remove the terrain phase from the InSAR phase with multilooking of small looks, which can reduce phase gradient and improve the accuracy of phase unwrapping. After several iterations, the GF-3 DEM is finally inversed with multilooking of 2 looks, which is of high resolution and high accuracy. The performance of GF-3 C-band InSAR data on the extraction of DEM is examined over a deciduous forested area with the proposed method. The root-mean-square error of the extracted GF-3 DEM is 3.78 m in comparison with the LiDAR DEM.

Interferometric synthetic aperture radar (InSAR) processing, if lacking high quality ground control points (GCPs), may produce large errors in the final DEM. Some kind of alignment or registration can reduce these errors. This paper evaluates the accuracy of InSAR processed digital elevation models (DEM), against a high resolution DEM. InSAR DEMs were aligned and least-squares registered with USGS, 1/3 arc second NED. The accuracy evaluations after registration show InSAR DEMs alignment and registration can eliminate DEM errors caused by lack of accurate GCPs. In some cases, this process improves the accuracy of the InSAR DEM even more efficiently than including GCPs into InSAR processing.

In Antarctica, SAR interferometry has largely been used in coastal glacial areas, while in rare cases this method has been used on the Antarctic plateau. In this paper, the authors present a digital elevation and ice flow map based on SAR interferometry for an area encompassing Talos Dome (TD) and the Frontier Mountain (FM) meteorite site in North Victoria Land/Antarctica. A digital elevation model (DEM) was calculated using a double SAR interferometry method. The DEM of the region was calculated by extracting approximately 100 control points from the Reference Elevation Model of Antarctica (REMA). The two DEMs differ slightly in some areas, probably due to the penetration of the SAR-C band signal into the cold firn. The largest differences are found in the western area of TD, where the radar penetration is more pronounced and fits well with the layer structures calculated by the georadar and the snow accumulation observations. By differentiating a 70-day interferogram with the calculated DEM, a displacement interferogram was calculated that represents the ice dynamics. The resulting ice flow pattern clearly shows the catchment areas of the Priestley and Rennick Glaciers as well as the ice flow from the west towards Wilkes Basin. The ice velocity field was analysed in the area of FM. This area has become well known due to the search for meteorites. The velocity field in combination with the calculated DEM confirms the generally accepted theories about the accumulation of meteorites over the Antarctic Plateau.

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.

The development of satellite technology is rapidly increasing the evolution of remote sensing. Satellite images give extensive useful information about the land structure that is easily manageable in the process of generating true, high-speed information which allows the forecasting of future environmental and urban planning. Remote sensing comprises active and passive systems. Passive sensors detect natural radiation that is emitted or reflected by the object or surrounding area being observed. Active systems which produce their own electromagnetic energy and their main properties are their ability of collecting data in nearly all atmospheric conditions, day or night. These systems are frequently used to generate a digital elevation model (DEM) because they cover large areas. DEM supplies essential data for applications that are concerned with the Earth’s surface and DEMs derived from survey data are accurate but very expensive and time consuming to create. However, the use of satellite remote sensing to provide images to generate a DEM is considered to be an efficient method of obtaining data. Interferometric Synthetic Aperture Radar (InSAR) is a new geodetic technique for determining earth topography. InSAR measurements are highly dense and they only give information in Line of Sight of Radar. In the study, interferograms were produced from the InSAR images taken by ERS satellites in 1992 and 2007 and we developed the methods to generate a DEM using the InSAR technique and present the results relating to Kayseri Province in Turkey. The accuracy of the DEM derived from the InSAR technique is evaluated in comparison with a reference DEM generated from contours in a topographical map.

Since 2007, the revolutionary X-band synthetic aperture radar (SAR) satellites Cosmo-SkyMed (CSK) and TerraSAR-X (TSX) have been collecting high-resolution images that are convenient for digital surface model (DSM) acquisition by the interferometric SAR (InSAR) technique. In this study, the potential of DSMs derived from CSK and TSX high-resolution spotlight (HS) images is thoroughly analysed regarding the basic accuracy metrics absolute vertical accuracy (AVA) and relative vertical accuracy (RVA). Utilising convenient InSAR pairs, 2 m gridded DSMs are generated in Istanbul and validated with model-based comparisons using an actual airborne laser scanning (ALS) DSM. Results show that CSK and TSX DSMs are compatible in open, built-up and forest land forms. The AVAs are between 8 m and 10 m based on standard deviation of height discrepancies against the ALS model. The RVAs, calculated by the coherence of neighbouring pixels for each DSM, are superior to AVAs for both CSK and TSX.

Trong những nam gần đây, kỹ thuật SAR giao thoa (Synthetic Aperture Radar Interferometry - InSAR) đa được xem như một trong những kỹ thuật hiệu quả hỗ trợ cho việc xây dựng va cập nhật dữ liệu của GIS. Dữ liệu độ cao số trong GIS thường lưu trữ theo cac dạng mo hinh độ cao số (DEM) va được sử dụng kha phổ biến để thể hiện địa hinh. Bai bao nhằm giới thiệu khả nang ứng dụng kỹ thuật InSAR trong xây dựng DEM va minh họa kết qủa thực nghiệm đạt được tại lưu vực song Kon – Ha Thanh thuộc tỉnh Binh Định. Độ chinh xac của mo hinh độ cao số (DEM) tạo bởi kỹ thuật InSAR được so sanh với cac phương phap tạo DEM khac (DEM nhận được từ cặp ảnh lập thể SPOT hay ASTER). In recent years, the Synthetic Aperture Radar Interferometry (InSAR) technique has been considered as an efficienty method in creating or updating GIS data. Digital Elevation Data referred to as Digital Elevation Models (DEMs) are digital representations of the sharpe of the earth’s surface. DEMs derived from survey data are accurate but they are very expensive and time-consuming. This paper introduces the ability of application of InSAR technique to generate a DEM and shows the result of experiment in Kon – Ha Thanh river in Binh Dinh province. The accuracy of DEM derived from InSAR technique is evaluated in comparison with other methods (DEM is derived from the stereoscopic images of SPOT or ASTER).

Abstract. In recent years, Synthetic Aperture Radar (SAR) data have been widely used for scientific applications and several SAR missions were realized. The active sensor principle and the signal wavelength in the order of centimeters provide all-day and all-weather capabilities, respectively. The modern German TerraSAR-X (TSX) satellite provides high spatial resolution down to one meter. Based on such data SAR Interferometry may yield high quality digital surface models (DSMs), which includes points located on 3d objects such as vegetation, forest, and elevated man-made structures. By removing these points, digital elevation model (DEM) representing the bare ground of Earth is obtained. The primary objective of this paper is the validation of DEMs obtained from TSX SAR data covering Barcelona area, Spain, in the framework of a scientific project conducted by ISPRS Working Group VII/2 "SAR Interferometry" that aims the evaluation of DEM derived from data of modern SAR satellite sensors. Towards this purpose, a DSM was generated with 10 m grid spacing using TSX StripMap mode SAR data and converted to a DEM by filtering. The accuracy results have been presented referring the comparison with a more accurate (10 cm–1 m) digital terrain model (DTM) derived from large scale photogrammetry. The results showed that the TSX DEM is quite coherent with the topography and the accuracy is in between ±8–10 m. As another application, the persistent scatterer interferometry (PSI) was conducted using TSX data and the outcomes were compared with a 3d city model available in Google Earth, which is known to be very precise because it is based on LIDAR data. The results showed that PSI outcomes are quite coherent with reference data and the RMSZ of differences is around 2.5 m.

A ground‐based synthetic aperture radar (GB SAR) interferometer was employed to detect small terrain movements which occurred over long periods of time on a landslide hazard zone in the Citrin Valley in northern Italy. Three measurement campaigns were carried out from September 2003 to September 2004. The radar instrumentation was carefully re‐installed at each campaign on the same observation point in order to avoid geometric decorrelation. Because of the global loss of coherence due to the long temporal separation between the observations, the retrieved displacements are limited to a number of very coherent points throughout the surveyed scenario. Radar data are locally compared with data provided by a global positioning system (GPS) network installed on the area interested by the landslide. Digital elevation model, photographic images, interferometric and GPS data are integrated within GIS environment providing a very effective geophysical knowledge tool.

Interferometric synthetic aperture radar (InSAR) is a useful technology to observe the earth topography. However, a synthetic aperture radar (SAR) interferogram usually includes a lot of rotational points, that is, singular points (SPs). SPs seriously affect the quality of generated digital elevation model (DEM). One of the dominant origins of the SPs is the local distortion in the co-registration of the master and slave images, which are the source of the interferogram. Previously, we proposed a local and fine co-registration method of the master and the slave using the number of SPs as the evaluation criterion (SPEC method). In this paper, we propose an improved version of the SPEC method which uses the shape-from-shading technique additionally for a better adjustment. In comparison to the conventional SPEC method, results indicate that the proposed technique improves the signal-to-noise ratio of the created DEM from InSAR images.

Synthetic aperture radar (SAR) enables imaging of topographic surfaces day and night in different atmospheric conditions. SAR imaging systems record both intensity and phase information of the backscattered signals. Acquired intensity information is often exposed to speckle noise, and gathered phase information is usually corrupted by thermal and other types of noise. Thus, these types of noises have negative effects on interpretation of SAR images. Digital elevation model (DEM) can be generated by interferometric SAR using two SAR images, of the same area, with slightly different look angles. The generated DEM is affected by the corruption of both intensity and phase information. In this paper, a proposed framework of convolutional neural network (CNN) and modified Wiener filter (MWF) is suggested in DEM generation process. The main purpose of the proposed framework is minimizing not only speckle noise of input SAR images but also phase noise of the interferogram. Thus, an enhanced DEM can be generated. Extensive experiments are carried out and different DEMs are generated from original SAR and from both despeckled SAR images and filtered interferogram. Results and comparative analyses show significant improvements in both quality and vertical accuracy of the DEM generated by the proposed hybrid (CNN-MWF) framework.

Abstract. In synthetic aperture radar (SAR) technology, urban mapping and modelling have become possible with revolutionary missions TerraSAR-X (TSX) and Cosmo-SkyMed (CSK) since 2007. These satellites offer 1m spatial resolution in high-resolution spotlight imaging mode and capable for high quality digital surface model (DSM) acquisition for urban areas utilizing interferometric SAR (InSAR) technology. With the advantage of independent generation from seasonal weather conditions, TSX and CSK DSMs are much in demand by scientific users. The performance of SAR DSMs is influenced by the distortions such as layover, foreshortening, shadow and double-bounce depend up on imaging geometry. In this study, the potential of DSMs derived from convenient 1m high-resolution spotlight (HS) InSAR pairs of CSK and TSX is validated by model-to-model absolute and relative accuracy estimations in an urban area. For the verification, an airborne laser scanning (ALS) DSM of the study area was used as the reference model. Results demonstrated that TSX and CSK urban DSMs are compatible in open, built-up and forest land forms with the absolute accuracy of 8–10 m. The relative accuracies based on the coherence of neighbouring pixels are superior to absolute accuracies both for CSK and TSX.

Unconstructed environments perception is a challenge problem for Unmanned Ground Vehicle (UGV) and is not well solved by traditional sensors, such as: optical camera, lidar and millimeter wave radar. This paper presents a novel forward looking InSAR (Interferometric Synthetic Aperture Radar) sensor for UGVs and focuses on reconstruction the Digital Terrain Model (DTM) of unconstructed environments. DTMs are vital to boost obstacle detection and path planning performances. The forward-looking InSAR system and its signal processing flow are briefly described. Then practical issues of applying the sensor in field environment are addressed. The impacts of height error and pitch angle error of the InSAR antenna are analyzed and solved by the split spectrum algorithm. Field experiment on a rough meadow has shown advanced perception capability of the forward-looking InSAR in complex environments.

Abstract. Interferometric Synthetic Aperture Radar (InSAR) technology is an important method to generate digital surface model (DSM). The past studies on space-borne derived DSM most focused on the elevation correction, due to the relative low resolution of DSM product. As a large number of high-resolution satellite data emerge, the horizontal discrepancies are needed to be considered. This paper proposes a DSM block adjustment method with horizontal constraints, aimed at eliminating the horizontal errors that exist between multiple DSM scenes with overlaps, achieving high precision and consistency in both the horizontal and vertical dimensions. Using ICESat-2 ATL08 point clouds as absolute elevation control and a reference DSM for horizontal control, the adjustment equations are constructed based on the constraint of tie points and controls. The experiment selects 7 image pairs of China TH2-01 SAR satellite, corresponding ICESat-2 ATL08 point and AW3D30 as reference DEM. The block adjustment results show that the proposed method improves the absolute vertical accuracy from 3.78 m to 2.56 m and reduces the average horizontal standard deviation between the InSAR derived DSMs and the reference AW3D30 from 15.31 m to 9.08 m.