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Hurricane Monitoring With Spaceborne Synthetic Aperture Radar

Hurricane Monitoring With Spaceborne Synthetic Aperture Radar

The spaceborne active remote sensing have the unique capability of observing sea surface through cloud, which has been playing an important role of monitor- ing response of sea surface under extreme weather situations. Scatterometers on board the European Remote Sensing (ERS), the Quick Scatterometer (QuikSCAT), and the Meteorological Operational (MetOp) satellites are particularly suitable for measurements of sea surface wind field, as both wind direction and wind speed can be derived without needing external information. Another active remote sensing instrument, spaceborne Synthetic Aperture Radar (SAR), e.g., the ERS-1/2 SAR, ENVISAT/ASAR, RADARSAT-1/2, TS-X/TD-X and Cosmo-Skymed, can not only provide sea surface backscatter intensity like scatterometer, but also image the sea sur- face in two-dimension with large spatial coverage and high spatial resolution, which provides abundant oceanic and atmospheric information of TCs, such as hurricane- generated long swell waves in small scales [ 3 , 4 ], hurricane/typhoon eye morphology [ 5 ] and roll vortices occurred in marine boundary layer [ 6 ] in meso-scale.
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Geosynchronous synthetic aperture radar: design and applications

Geosynchronous synthetic aperture radar: design and applications

Following the analysis of the technical complexities and challenges related to the active and passive configurations, Cranfield Space Research Centre looked into a system design of a bi-static passive SAR concept called GeoSAR. This concept has already been demonstrated in literature (Prati et al., 1998). It was also the subject of a group project for Cranfield University’s MSc course in Astronautics and Space Engineering for the academic year 2005/2006 (Hobbs, 2006). The group project carried out the design of a spacecraft for a geosynchronous radar capable of continuous monitoring of continental areas. The GeoSAR project shares with the present research only the baseline of the configuration therefore this chapter introduces the GeoSAR project and then moves into the analysis of system performance that has not been covered in the group project.
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Spaceborne L-Band Synthetic Aperture Radar Data for Geoscientific Analyses in Coastal Land Applications: A Review

Spaceborne L-Band Synthetic Aperture Radar Data for Geoscientific Analyses in Coastal Land Applications: A Review

During the literature review, we found that 35% (69) of all reviewed articles were used for analyzing wetlands. Wetlands represent one of the world’s most important ecosystems [115], providing valuable natural resources and ecosystem services such as flood control, water purification and food supply [116]. With an estimated carbon storage capacity of 12%, wetland ecosystems also play an important role in the global climate [117]. Located at the land–sea interface, coastal wetlands, such as mangrove forests or salt marshes, are among the most productive and carbon-rich ecosystems. Coastal wetlands are at risk from a variety of threats as they are highly exposed to climate change-induced impacts, such as sea level rise [118], increased storm surge frequency [119–121] and saline intrusion [122], which threaten wetlands. This can be observed especially in wide low- topography coastal plains, where the influence of the rising sea level on wetland vegetation communities is strictly controlled by tidal hydroperiods [123]. Human activities, such as draining wetlands for the conversion to agriculture [13] and aquaculture [12] (e.g., rice and shrimp farming in Southeast Asia) or building construction, causes destruction or degradation of wetlands around the globe [115]. The assessment of the extent of wetlands is of great importance for the quantification of environmental change in the coastal zone. Earth observation-derived spatio-temporal information on regional wetland extents and dynamics is baseline information for decision-makers and support coastal management. Davidson et al. [51] reviewed estimates of global and regional wetland area from global mapping and remote sensing and pointed to the improved availability of spaceborne sensing and canopy penetration capabilities with long wavelength L-band SAR instruments for the detection of wetlands and flooded vegetation, although mapping the variety of wetland types at the global scale using such SAR data has yet to be accomplished.
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Digital Beamforming for Spaceborne ReflectorBased Synthetic Aperture Radar, Part 1 Basic Imaging Modes

Digital Beamforming for Spaceborne ReflectorBased Synthetic Aperture Radar, Part 1 Basic Imaging Modes

Dual-pol capability (single transmit polarization and two orthogonal receive polarizations) requires a replication of the same functionality for each polarization channel. Imaging in fully polarimetric mode (quad-pol) in turn requires transmit- ting a second orthogonal polarization. In conventional SAR, the two transmit polarizations are operated in time multiplex; this requires changing the SAR operation parameters, such as increasing the PRF, which has an impact on the SAR performance. Further, the antenna polarization purity, i.e., the magnitude of the cross-polar component, becomes relevant. Reflector antennas with small focal-length-to-diameter ratios suffer from an intrinsic high cross-polar component; this can
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Spectral Estimation for Synthetic Aperture Radar Tomography

Spectral Estimation for Synthetic Aperture Radar Tomography

Synthetic Aperture Radar (SAR) Tomography, a new and advanced technique in the field of SAR processing, is aimed at determining the 3-D reflectivity function from measured multi-pass SAR data. It is essentially a spectrum estimation problem as for a specific resolution cell the complex valued SAR measurements of a SAR image stack are actually the irregularly sampled Fourier transform of the reflectivity function in the elevation direction. The successful launch of the German high resolution SAR mission TerraSAR-X provides a new possibility to investigate this topic with high quality spaceborne data. Within the framework of this master thesis, the spectrum estimation problem is formulated from a mathematical point of view. Different spectrum estimation strategies such as the Singular Value Decomposition (SVD) and Nonlinear Least Squares estimation (NLS) are evaluated and compared using both simulated data and TerraSAR-X data from the testsite Las Vegas with special consideration of the difficulties caused by sparse and irregularly spaced sampling. The problem of ill-conditioning when using the Singular Value Decomposition is investigated and regularization tools (such as singular value truncation and Wiener filtering) are utilized to overcome this problem. For the sake of validation, the spectrum estimation results with TerraSAR-X data are compared to the probable ground truth.
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A Tutorial on Synthetic Aperture Radar

A Tutorial on Synthetic Aperture Radar

coverage and weather conditions [1]–[9]. It is predestined to monitor dynamic processes on the Earth surface in a reliable, continuous and global way. SAR systems have a side-looking imaging geometry and are based on a pulsed radar installed on a platform with a forward movement. The radar system transmits electromagnetic pulses with high power and receives the echoes of the backscattered signal in a sequential way. Typical values for the pulse repetition frequency range from a few hundred to a few thousand Hertz for airborne and spaceborne systems, re- spectively. The swath width varies typically from a few kilometers to 20 km in the airborne case and from 30 to 500 km in the spaceborne case. The transmitted pulse interacts with the Earth surface and only a portion of it is backscattered to the receiving antenna which can be the same as the transmit antenna (for a monostatic ra- dar) or a different one (for a bi- or multi-static radar). The amplitude and phase of the backscattered signal depends on the physical (i.e., geometry, roughness) and electri- cal properties (i.e., permittivity) of the imaged object. Depending on the frequency band, considerable pen- etration can occur so that the imaged objects and media must be modeled as a volume (e.g., vegetation, ice and snow, dry soil). More penetration of the electromagnetic pulses in media will occur for radar systems using longer wavelengths which usually have an accentuated volume contribution in the backscattered signal. Commonly used frequency bands in SAR systems and the associated wave- length ranges are shown in Table 1.
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Multidimensional Radar Waveforms: A New Paradigm for the Design and Operation of Highly Performant Spaceborne Synthetic Aperture Radar Systems

Multidimensional Radar Waveforms: A New Paradigm for the Design and Operation of Highly Performant Spaceborne Synthetic Aperture Radar Systems

has the advantage to use always all Tx antenna elements which alleviates the peak power requirements of the T/R modules to achieve a predefined signal-to-noise ratio. A sequence of chirp signals is then transmitted while switch- ing between different azimuth beams from sub-pulse to sub-pulse. This specific illumination sequence results for each point on the ground in multiple and mutually delayed chirp signal returns. If we consider now a scatterer at a given range, one will at each instance of time only receive the scattered signal from one sub-pulse while the other sub-pulses lead to a superposition of the received signal with range ambiguous echoes from scatterers located at different ranges. These different ranges are in turn associ- ated with different look angles in elevation. It is hence possible to suppress the ambiguous returns from different ranges by digital beamforming on receive in elevation which enables a clear and unambiguous separation of the received echoes from the different azimuth beams. The echoes from multiple azimuth beams are finally combined coherently to recover the full Doppler spectrum for high azimuth resolution. This combination is equivalent to a signal reconstruction from a multi-channel bandpass de- composition, where the individual bandpass signals corre- spond to narrow band azimuth spectra with different Dop- pler centroids. Fig. 6 illustrates the improved azimuth am- biguity suppression from multidimensional waveform en- coding. A more detailed description and the corresponding processing algorithms can be found in [10].
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Demonstration of Digital Beamforming in Elevation for Spaceborne Synthetic Aperture Radar

Demonstration of Digital Beamforming in Elevation for Spaceborne Synthetic Aperture Radar

summing them up leads to a narrow beam in the desired direction. For a system using a reflector antenna, mul- tiple beams in elevation require multiple feeds placed at different positions along the elevation direction. Each el- ement generates a narrow beam that looks in a specific direction depending on its position. The angular seg- ments in elevation covered by the beam of each element does not fully overlap with those of the other elements. Those two possible options of digital beamforming will be demonstrated using modified acquisition schemes for the TerraSAR-X satellite.

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Smart Multi-Aperture Radar Techniques for Spaceborne Remote Sensing

Smart Multi-Aperture Radar Techniques for Spaceborne Remote Sensing

If spaceborne synthetic aperture radar (SAR) sensors were categorized according to their operational flexibility, four generations could be identified. The first sensors were on/off sensors with a single fixed mode of operation (fixed beam, in- cidence angle, bandwidth, etc.) Later, sensors were developed which could be operated in multiple modes, such as StripMap, ScanSAR or SpotLight; however the macro-based command- ing was basically restricted to selecting a specific mode without the flexibility to alter/access individual instrument set- tings. Current SAR sensors –third generation– offer a greater flexibility in commanding nearly each individual parameter of the instrument (see T ERRA SAR-X [1] for example). This can be understood as providing the basic building blocks to construct any operation mode in combination with any possible instrument setting. However, even current sensors do not offer a satisfactory solution to the “fundamental limitation of SAR sensors” which can be described in short as the incapability to simultaneously provide high resolution and wide coverage [2], instead they offer the flexibility to choose a compromise between high resolution or wide coverage.
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Predictive Quantization for Staggered Synthetic Aperture Radar Systems

Predictive Quantization for Staggered Synthetic Aperture Radar Systems

A big challenge for future spaceborne remote sensing missions is now turning to the estimation and long-term monitoring of dynamic processes in the Earth’s environmental system, such as deformation events, forest and biomass change, and ocean surface cur- rents. The German Aerospace Center (DLR) is investigating an innovative single-pass interferometric and fully polarimetric L-band radar mission, named Tandem-L, which ex- ploits innovative high-resolution wide swath SAR modes, together with the use of large bandwidths, high pulse repetition frequencies, and multiple acquisition channels, result- ing in an achievable swath width of about 350 km on ground. Such an increase in term of coverage has as a main drawback the generation of a huge amount of onboard data, which is of around 8 Terabytes per day. One of the proposed solutions to reduce the resulting onboard data reduction suggests to perform a complex onboard processing (i.e. an onboard interpolation, low-pass filtering and decimation) and allows a data reduction up to 50% [23][21]. On the other hand, the onboard computational memory required for the data reduction processing is at the limit of the hardware components, leading to high energy consumption. Moreover, the practical realization of the technique is very complex, including many specific coefficients which must be correctly selected during acquisition. The research of alternative solutions is therefore of great interest in order to have differ- ent options to choose for the mission development, which motivates the present master thesis. In this work, a data reduction strategy based on Linear Predictive Coding (LPC) is investigated in the context of Tandem-L. The method has been designed to reduce the complexity as much as possible while achieving a certain data reduction. A mathemati- cal formulation for the novel technique is an interesting goal for understanding in which situation the present method can be more or less efficient. The resulting performance has been verified through Monte Carlo simulations in order to evaluate the solution under different aspects (i.e. final performance versus resulting system complexity). Moreover, other complications introduced by the Tandem-L system such as the presence of missing samples (so-called gaps) during the acquisition, have been investigated and successfully solved through novel coding strategies.
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Operational Synthetic Aperture Radar Based Sea Ice Classification

Operational Synthetic Aperture Radar Based Sea Ice Classification

Over decades, synthetic aperture radar (SAR) has become an invaluable tool for operational and scientific monitoring of ice infested maritime regions. In contrast to optical imaging, SAR is not affected by cloud coverage or lack of daylight. While air-borne and ship-borne SAR cannot always be used during adverse weather conditions, space-borne SAR image acquisition is not impeded by weather incidents and can cover almost any region on the globe with short revisit times. Satellites such as ALOS-1 and ALOS-2 in L-band, RADARSAT-1 and 2, ENVISAT and Sentinal-1 in C-band and TerraSAR-X (TS-X) in X-band have proven the usefulness of SAR sensors for investigating sea ice in Arctic and Antarctic regions. The size of SAR images extends up to a few hundred kilometers in width and length and provides much higher resolution information compared to other conventional sensors (e.g. passive microwave) and are ideal for the long term-monitoring conducted by meteorological services around the world. The operational sea ice classification processing chain is able to process all commercially available SAR images in different frequency band [1, 2]. Our algorithmic approach for an automated sea ice classification consists of two steps. In the first step, we perform a polarimetric feature extraction procedure. The resulting feature vectors are then ingested into a trained neural network classifier to arrive at a pixel-wise supervised classification. During the symposium we will show examples of above mentioned products which are not only helpful for campaign planning but also might provide useful information to scientists across different scientific domains.
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Bathymetry derived from Sentinel-1 Synthetic Aperture Radar

Bathymetry derived from Sentinel-1 Synthetic Aperture Radar

With the advance of satellite remote sensing technology, the continental topography can be accurately measured by Synthetic Aperture Radar (SAR) satellites, as recently done globally by the TanDEM-X mission [4]. However, about 70% of the Earth are covered by water, where the sea floor topography cannot be measured by a single spaceborne Earth Observation technology today. Con- ventional means of measuring the bathymetry use ship- mounted echo sounders; shallow water with low turbid- ity can also be covered with plane-mounted techniques like LIDAR. The high costs connected to these ways of measurement are one of major the reasons for the current lack of bathymetric data worldwide. Free datasets like GEBCO (General Bathymetric Charts of the Oceans) [2] are available, but in many areas based only on interpo- lation or deprecated measurement data. Even projects like EMODnet bathymetry [1], where many individual bathymetric sources are combined for European waters, still have coverage gaps.
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Sparse Reconstruction Automaton for Synthetic Aperture Radar Tomography

Sparse Reconstruction Automaton for Synthetic Aperture Radar Tomography

Modern spaceborne synthetic aperture radar (SAR) sensors, e.g., TerraSAR-X (TSX), TanDEM-X (TDX) and COSMO- SkyMed, acquire images with up to meter- or even decimeter- level resolution. Due to their side-looking nature, echoes from objects at the same distance are mapped onto one azimuth- range pixel, which is also known as the layover effect. On this account, interpretation of SAR images w.r.t. urban areas, where buildings are often superimposed on ground or lower infrastructures, is not straightforward. In order to separate different potential scatterers within one resolution cell and to reconstruct true three-dimensional images, tomographic SAR (TomoSAR) comes to play.
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Ocean wave measurements using complex synthetic aperture radar data

Ocean wave measurements using complex synthetic aperture radar data

The first theoretical aspect discussed was a modification of the existing SAR cross spectra integral transform proposed by Engen and Johnson [1995], introducing a nonlinear formulation of the RAR modulation in order to avoid negative radar cross sections occurring in the existing linear model. The presented analysis is the first systematic investigation of this phenomenon. It was shown that for the ERS and ENVISAT configuration the effect is tolerable with less than 10% of meaningless cross sections. However, for future spaceborne systems with higher range resolution of up to 2 m, like TerraSAR, or for airborne SAR the effect becomes significant. For the TerraSAR configuration more than 20% of the predicted cross sections are outside the feasible range, if the linear model is used. To solve the problem, an exponential model for the SAR image intensity was proposed, which predicts positive cross sections under all configurations. The model is consistent with the former linear model in so far as both mean and variance of the RAR image are maintained. Based on the new RAR model, an integral transform was derived, which maps an ocean wave spectrum into the corresponding SAR look cross spectrum. Comparisons with the transform introduced in Engen and Johnson [1995] showed that the exponential RAR model leads to changes in the fine structure of the simulated cross spectrum, while overall shape and energy levels are maintained.
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Synthetic Aperture Radar Tomography - Compressed Sensing Models and Algorithms

Synthetic Aperture Radar Tomography - Compressed Sensing Models and Algorithms

A synthetic aperture radar (SAR) is an active microwave instrument capable of imag- ing the surface of the earth at specific wavelengths and polarizations in day/night and all-weather conditions. In its basic configuration, a small airborne/spaceborne antenna traveling along a straight-line trajectory is pointed perpendicular to the flight track in a side-looking fashion. This results in the synthesis of a virtual along-track antenna aperture that enables the formation of a high-resolution 2-D image of the illuminated area. Moreover, when multiple parallel trajectories—with cross-track and/or elevation displacements—are considered, the resulting sensing geometry enables the synthesis of two virtual antenna apertures that allow for 3-D backscatter profiling. This imaging modality is known as SAR tomography and is commonly approached by first obtain- ing multiple 2-D coregistered SAR images—such that each image corresponds with a parallel pass—followed by 1-D standard spectral estimation techniques. A typical ap- plication is the 3-D imaging of vegetated areas which, due to the high-penetration ca- pabilities of radiation at long wavelengths, has proven to be of great value for the esti- mation of forest structure and, in turn, for the quantification of above ground biomass. In addition, with the anticipated advent of long-wavelength spaceborne radars, tomo- graphic SAR techniques will become of considerable interest, as tomographic data sets will be available on a large scale. However, ideal sampling conditions are known to require a large number of dense regular acquisitions, which are not only limited and expensive but can also lead to temporal decorrelation.
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Interferometric Synthetic Aperture Radar (SAR) Missions Employing Formation Flying

Interferometric Synthetic Aperture Radar (SAR) Missions Employing Formation Flying

interferograms with different baseline lengths to resolve phase ambiguities. By this, it becomes possible to derive DEMs with HRTI-4–like accuracy on a local or even re- gional scale. Further opportunities arise from a compar- ison of multiple large baseline TanDEM-X interferograms acquired during different passes of the satellite formation. This provides a very sensitive measure for vertical scene and structure changes with a height sensitivity of a few decimeters. Potential applications are a detection of the grounding line that separates the shelf from the inland ice in polar regions, monitoring of vegetation growth, map- ping of atmospheric water vapor with high spatial reso- lution, measurement of snow accumulation, or the detection of anthropogenic changes of the environment, e.g., due to deforestation. Note that most of these com- binations rely on a comparison of two or more single-pass (large baseline) cross-track interferograms and do hence not necessarily require coherence between the different passes, i.e., the highly accurate measurement of the height change is not affected by temporal decorrelation. Further information can be gained from an evaluation of coherence changes (e.g., from varying volume decorrela- tion) between different passes, potentially augmented by polarimetric information. This could, for instance, reveal even slight changes in the soil and vegetation structure reflecting vegetation growth and loss, freezing and thawing, fire destruction, human activities, and so on. TanDEM-X hence enables the entry into a new era of interferometric (and tomographic) processing techniques as did ERS-1/2 for the development of classical repeat-pass SAR interferometry.
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Physics-based clutter model for geosynchronous synthetic aperture radar

Physics-based clutter model for geosynchronous synthetic aperture radar

(GEO) satellite radar is quite different with incidence angles of 20 ◦ - 70 ◦ . For spaceborne radar we expect less shadowing of clutter patches and more scatter from within the canopy. Billingsley’s work does however include models of the re- lationship between windspeed and clutter scattering. This is useful for GEO SAR because for some systems the proposed relative orbit speed is relatively low, which combined with the long slant range can lead to very large azimuth spread of clutter backscatter.

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Spaceborne MIMO Synthetic Aperture Radar for Multimodal Operation

Spaceborne MIMO Synthetic Aperture Radar for Multimodal Operation

the receive array height. In this system operation, a severe nonuniform sampling will not occur due to the narrow PRF range. In the case that a wide range of PRF is considered, the degree of nonuniform sampling will be significant and reach the maximum at the highest PRF. In the designed system, it is assumed that all receive channels have the identical noise figure of 3.75 dB and a system loss of 3 dB. The required peak and average power of this system are higher than those of the TerraSAR-X system (2-kW peak) in order to achieve the desired SNR over the 100-km swath width. As a rule, the sampling frequency of 275 MHz includes a 10% guard band, and then, the pulse length of 150 μs leads to 41 250 subcar- riers with the 6.67-kHz subcarrier spacing. In this example, we assume that the ICI due to instantaneous Doppler shift is compensated by the method introduced in [35]. Regarding the undersampling for HRWS SAR imaging in the MIMO SAR, the reconstruction algorithm [13] recovers the original Doppler spectrum prior to the Doppler compensation. This approach has been used for frequency-modulated continuous-wave (FMCW) SAR with DBF in [45] and also for the very high resolution SAR data processing [46]. Therefore, the ICI issue is not included in the performance estimation in Section VI-A. To improve the computation speed of DFT/inverse DFT, one can select a number of subcarriers that are equal to a power of two. This MIMO SAR antenna is composed of six panels in azimuth and 42 receive subarrays in elevation in each panel. The receive subarray consists of three X-band radiators in elevation and azimuth, respectively. Fig. 12 depicts the MIMO SAR antenna configuration and geometric parameters in this example design.
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Synthetic aperture radar remote sensing for landfill monitoring

Synthetic aperture radar remote sensing for landfill monitoring

4.8 Ascending and Descending Scenes Coregistration The research explores SAR data acquired from both ascending and descending orbits. In some instances, these scenes, or products derived from them, are merged together into a single image. As briefly explained in Section 2.1.2, foreshortening, layover and shadow effects in the radar slant direction can have a drastic impact on an image especially in the presence of steep topography. Due to the different points of view of the ascending and descending scenes, these distortion effects are produced in different directions and consequently the combination of such data sets must be carried out with particular attention. This matter has not been significantly investigated in the literature. The fusion of multi-angle ERS-1 and 2 tandem data has been applied in previous research (Sansosti et al., 1999; Coltelli et al., 1998 and Carrasco et al., 1997) to improve the accuracy of digital elevation models and to detect ground displacements in three dimensions as opposed to a single-orbit-direction tandem pair which can instead only detect displacements in the SAR slant direction. More specifically, Werner et al. (2002) discuss issues related to SAR geocoding and multi-sensor image registration. They use the satellite orbit and local terrain information to reduce coregistration errors. They also select recognisable image features as ground control points as an additional aid. Their analysis highlights the problem of selecting certain persistent scatterers which might not have the same position in the ascending and descending images due to their height (e.g. high buildings). The utilisation of SAR images with different acquisition geometries has also been applied by Dell’Acqua et al. (2003). They manually coregister three simulated SAR images with 3 m ground resolution and generated each with a different viewing geometry. Dell’Acqua et al. (2003) try to extract an accurate map of the road system of the city of Pavia in northern Italy and do not use the images for a direct multi-band classification because the same buildings have a difference appearance in the two images.
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Orbital Effects in Spaceborne Synthetic Aperture Radar Interferometry

Orbital Effects in Spaceborne Synthetic Aperture Radar Interferometry

Whereas the predictions for a correction with the translation approach have already been validated for a PS-InSAR time series (B¨ ahr et al., 2012), the reference frame effect itself has not been explicitly observed yet. Nevertheless, its existence is evident without explicit verification, and a correction is advisable whenever large-scale deformation phenomena are measured with high accuracy requirements. Based on the comparison in figure 7.8, a dedicated Euler rotation of orbital state vectors can be considered sufficiently accurate in most cases. Also a homogeneous translation derived from one representative ITRF velocity performs well but may involve minor phase artefacts. It should be preferred nevertheless in regions where the approximation quality of plate kinematic models is bad. The general transformation approach may be worth considering whenever InSAR measurements are used to densify an existing (GNSS) velocity field. If the benefit of the complex transformation outweighs the involved effort in this case still needs to be investigated.
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