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Special Issue "Synthetic Aperture Radar (SAR)"

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Remote Sensors".

Deadline for manuscript submissions: closed (31 May 2008)

Special Issue Editor

Guest Editor
Prof. Daniele Riccio (Website)

Department of Electrical Engineering and Information Technology, Faculty of Engineering, University of Napoli Federico II, Via Claudio 21, 80125 Napoli, Italy
Interests: remote sensing; electromagnetic scattering; synthetic aperture radar; radar; microwave imaging

Special Issue Information

Dear Colleagues,

A new generation of Spaceborne Synthetic Aperture Radar (SAR) sensors is being operational to map, monitor and analyze the Earth: new available configurations and operational modes increase the flexibility of SAR sensors that are now able to obtain microwave 2-D images and data as well as 3-D interferometric products within a wide range of space and time resolution and coverage. This unprecedented development in the SAR sensors requires definition of new techniques and algorithms for SAR data usage as well as assessment of existing methods for SAR products exploitation. Hence, main purpose of this Special issue is to provide a reference of the SAR sensors and their operating characteristics, as well as to advance the exploitation of their data for monitoring applications.

The Special Issue is open to all researchers. Papers are solicited on:
- existing and future SAR and ISAR sensors;
- SAR data processing and simulation for 2-D images, polarimetric, interferometric and differential interferometric products;
- SAR data processing and simulation for Stripmap, Spotlight, Hybrid Strip-Spot, ScanSAR, Bistatic, operational modes;
- SAR data usage and information retrieval for application to land, ocean, urban areas, forestry, volcanoes, ice monitoring;
- SAR data elaboration, parameters estimation, and feature extraction for retrieval of value added information;
- integration of SAR data with other remote sensing products;
- use of SAR data in conjunction with demographic, social and economics data;
- comparison of SAR products with measurement on field campaigns and in situ data.

Prof. Dr. Daniele Riccio
Guest Editor

Keywords

  • synthetic aperture radar
  • SAR
  • ISAR
  • remote sensing
  • imaging radar
  • earth observation
  • spaceborne SAR
  • airborne SAR
  • shuttle imaging radar
  • ERS
  • J-ERS
  • SRTM
  • radarsat
  • ASAR
  • ALOS
  • COSMO skymed
  • TerraSAR

Published Papers (33 papers)

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Open AccessArticle Using a LIDAR Vegetation Model to Predict UHF SAR Attenuation in Coniferous Forests
Sensors 2009, 9(3), 1559-1573; doi:10.3390/s90301559
Received: 16 December 2008 / Revised: 23 January 2009 / Accepted: 5 March 2009 / Published: 6 March 2009
Cited by 3 | PDF Full-text (279 KB) | HTML Full-text | XML Full-text
Abstract
Attenuation of radar signals by vegetation can be a problem for target detection and GPS reception, and is an important parameter in models describing vegetation backscatter. Here we first present a model describing the 3D distribution of stem and foliage structure based [...] Read more.
Attenuation of radar signals by vegetation can be a problem for target detection and GPS reception, and is an important parameter in models describing vegetation backscatter. Here we first present a model describing the 3D distribution of stem and foliage structure based on small footprint scanning LIDAR data. Secondly we present a model that uses ray-tracing methodology to record detailed interactions between simulated radar beams and vegetation components. These interactions are combined over the SAR aperture and used to predict two-way attenuation of the SAR signal. Accuracy of the model is demonstrated using UHF SAR observations of large trihedral corner reflectors in coniferous forest stands. Our study showed that the model explains between 66% and 81% of the variability in observed attenuation. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR))
Open AccessArticle A Fast Level Set Method for Synthetic Aperture Radar Ocean Image Segmentation
Sensors 2009, 9(2), 814-829; doi:10.3390/s90200814
Received: 14 December 2008 / Revised: 30 January 2009 / Accepted: 2 February 2009 / Published: 3 February 2009
Cited by 6 | PDF Full-text (1932 KB) | HTML Full-text | XML Full-text
Abstract
Segmentation of high noise imagery like Synthetic Aperture Radar (SAR) images is still one of the most challenging tasks in image processing. While level set, a novel approach based on the analysis of the motion of an interface, can be used to [...] Read more.
Segmentation of high noise imagery like Synthetic Aperture Radar (SAR) images is still one of the most challenging tasks in image processing. While level set, a novel approach based on the analysis of the motion of an interface, can be used to address this challenge, the cell-based iterations may make the process of image segmentation remarkably slow, especially for large-size images. For this reason fast level set algorithms such as narrow band and fast marching have been attempted. Built upon these, this paper presents an improved fast level set method for SAR ocean image segmentation. This competent method is dependent on both the intensity driven speed and curvature flow that result in a stable and smooth boundary. Notably, it is optimized to track moving interfaces for keeping up with the point-wise boundary propagation using a single list and a method of fast up-wind scheme iteration. The list facilitates efficient insertion and deletion of pixels on the propagation front. Meanwhile, the local up-wind scheme is used to update the motion of the curvature front instead of solving partial differential equations. Experiments have been carried out on extraction of surface slick features from ERS-2 SAR images to substantiate the efficacy of the proposed fast level set method. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR))
Open AccessArticle Observation of a Large Landslide on La Reunion Island Using Differential Sar Interferometry (JERS and Radarsat) and Correlation of Optical (Spot5 and Aerial) Images
Sensors 2009, 9(1), 616-630; doi:10.3390/s90100616
Received: 4 November 2008 / Revised: 12 January 2009 / Accepted: 13 January 2009 / Published: 21 January 2009
Cited by 15 | PDF Full-text (637 KB) | HTML Full-text | XML Full-text
Abstract
Slope instabilities are one of the most important geo-hazards in terms of socio-economic costs. The island of La Réunion (Indian Ocean) is affected by constant slope movements and huge landslides due to a combination of rough topography, wet tropical climate and its [...] Read more.
Slope instabilities are one of the most important geo-hazards in terms of socio-economic costs. The island of La Réunion (Indian Ocean) is affected by constant slope movements and huge landslides due to a combination of rough topography, wet tropical climate and its specific geological context. We show that remote sensing techniques (Differential SAR Interferometry and correlation of optical images) provide complementary means to characterize landslides on a regional scale. The vegetation cover generally hampers the analysis of C–band interferograms. We used JERS-1 images to show that the L-band can be used to overcome the loss of coherence observed in Radarsat C-band interferograms. Image correlation was applied to optical airborne and SPOT 5 sensors images. The two techniques were applied to a landslide near the town of Hellbourg in order to assess their performance for detecting and quantifying the ground motion associated to this landslide. They allowed the mapping of the unstable areas. Ground displacement of about 0.5 m yr-1 was measured. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR))
Open AccessArticle MAPSAR Image Simulation Based on L-band Polarimetric Data from the SAR-R99B Airborne Sensor (SIVAM System)
Sensors 2009, 9(1), 102-117; doi:10.3390/s90100102
Received: 17 September 2008 / Revised: 19 December 2008 / Accepted: 20 December 2008 / Published: 7 January 2009
Cited by 5 | PDF Full-text (3390 KB) | HTML Full-text | XML Full-text
Abstract
This paper describes the methodology applied to generate simulated multipolarized L-band SAR images of the MAPSAR (Multi-Application Purpose SAR) satellite from the airborne SAR R99B sensor (SIVAM System). MAPSAR is a feasibility study conducted by INPE (National Institute for Space Research) and [...] Read more.
This paper describes the methodology applied to generate simulated multipolarized L-band SAR images of the MAPSAR (Multi-Application Purpose SAR) satellite from the airborne SAR R99B sensor (SIVAM System). MAPSAR is a feasibility study conducted by INPE (National Institute for Space Research) and DLR (German Aerospace Center) targeting a satellite L-band SAR innovative mission for assessment, management and monitoring of natural resources. Examples of simulated products and their applications are briefly discussed. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR))
Open AccessArticle Inversion of Electromagnetic Models for Bare Soil Parameter Estimation from Multifrequency Polarimetric SAR Data
Sensors 2008, 8(12), 8181-8200; doi:10.3390/s8128181
Received: 23 September 2008 / Revised: 11 November 2008 / Accepted: 2 December 2008 / Published: 11 December 2008
Cited by 28 | PDF Full-text (297 KB) | HTML Full-text | XML Full-text
Abstract
The potentiality of polarimetric SAR data for the estimation of bare soil geophysical parameters (i.e., roughness and soil moisture) is investigated in this work. For this purpose, two forward models available in the literature, able to simulate the measurements of a multifrequency [...] Read more.
The potentiality of polarimetric SAR data for the estimation of bare soil geophysical parameters (i.e., roughness and soil moisture) is investigated in this work. For this purpose, two forward models available in the literature, able to simulate the measurements of a multifrequency radar polarimeter, have been implemented for use within an inversion scheme. A multiplicative noise has been considered in the multidimensional space of the elements of the polarimetric Covariance Matrix, by adopting a complex Wishart distribution to account for speckle effects. An additive error has been also introduced on the simulated measurements to account for calibration and model errors. Maximum a Posteriori Probability and Minimum Variance criteria have been considered to perform the inversion. As for the algorithms to implement the criteria, simple optimization/integration procedures have been used. A Neural Network approach has been adopted as well. A correlation between the roughness parameters has been also supposed in the simulation as a priori information, to evaluate its effect on the estimation accuracy. The methods have been tested on simulated data to compare their performances as function of number of looks, incidence angles and frequency bands, thus identifying the best radar configuration in terms of estimation accuracy. Polarimetric measurements acquired during MAC Europe and SIR-C campaigns, over selected bare soil fields, have been also used as validation data. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR))
Open AccessArticle A Modified Subpulse SAR Processing Procedure Based on the Range-Doppler Algorithm for Synthetic Wideband Waveforms
Sensors 2008, 8(12), 8224-8236; doi:10.3390/s8128224
Received: 14 October 2008 / Revised: 10 December 2008 / Accepted: 10 December 2008 / Published: 11 December 2008
Cited by 4 | PDF Full-text (563 KB) | HTML Full-text | XML Full-text
Abstract
Synthetic wideband waveforms (SWW) combine a stepped frequency CW waveform and a chirp signal waveform to achieve high range resolution without requiring a large bandwidth or the consequent very high sampling rate. If an efficient algorithm like the range-Doppler algorithm (RDA) is [...] Read more.
Synthetic wideband waveforms (SWW) combine a stepped frequency CW waveform and a chirp signal waveform to achieve high range resolution without requiring a large bandwidth or the consequent very high sampling rate. If an efficient algorithm like the range-Doppler algorithm (RDA) is used to acquire the SAR images for synthetic wideband signals, errors occur due to approximations, so the images may not show the best possible result. This paper proposes a modified subpulse SAR processing algorithm for synthetic wideband signals which is based on RDA. An experiment with an automobile-based SAR system showed that the proposed algorithm is quite accurate with a considerable improvement in resolution and quality of the obtained SAR image. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR))
Open AccessArticle Assessment of Polarimetric SAR Interferometry for Improving Ship Classification based on Simulated Data
Sensors 2008, 8(12), 7715-7735; doi:10.3390/s8127715
Received: 16 June 2008 / Revised: 17 November 2007 / Accepted: 27 November 2008 / Published: 2 December 2008
Cited by 5 | PDF Full-text (1556 KB) | HTML Full-text | XML Full-text
Abstract
This paper uses a complete and realistic SAR simulation processing chain, GRECOSAR, to study the potentialities of Polarimetric SAR Interferometry (POLInSAR) in the development of new classification methods for ships. Its high processing efficiency and scenario flexibility have allowed to develop exhaustive [...] Read more.
This paper uses a complete and realistic SAR simulation processing chain, GRECOSAR, to study the potentialities of Polarimetric SAR Interferometry (POLInSAR) in the development of new classification methods for ships. Its high processing efficiency and scenario flexibility have allowed to develop exhaustive scattering studies. The results have revealed, first, vessels’ geometries can be described by specific combinations of Permanent Polarimetric Scatterers (PePS) and, second, each type of vessel could be characterized by a particular spatial and polarimetric distribution of PePS. Such properties have been recently exploited to propose a new Vessel Classification Algorithm (VCA) working with POLInSAR data, which, according to several simulation tests, may provide promising performance in real scenarios. Along the paper, explanation of the main steps summarizing the whole research activity carried out with ships and GRECOSAR are provided as well as examples of the main results and VCA validation tests. Special attention will be devoted to the new improvements achieved, which are related to simulations processing a new and highly realistic sea surface model. The paper will show that, for POLInSAR data with fine resolution, VCA can help to classify ships with notable robustness under diverse and adverse observation conditions. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR))
Open AccessArticle Geological Interpretation of PSInSAR Data at Regional Scale
Sensors 2008, 8(11), 7469-7492; doi:10.3390/s8117469
Received: 16 July 2008 / Revised: 12 September 2008 / Accepted: 20 October 2008 / Published: 24 November 2008
Cited by 38 | PDF Full-text (3369 KB) | HTML Full-text | XML Full-text
Abstract
Results of a PSInSAR™ project carried out by the Regional Agency for Environmental Protection (ARPA) in Piemonte Region (Northern Italy) are presented and discussed. A methodology is proposed for the interpretation of the PSInSARTM data at the regional scale, easy to [...] Read more.
Results of a PSInSAR™ project carried out by the Regional Agency for Environmental Protection (ARPA) in Piemonte Region (Northern Italy) are presented and discussed. A methodology is proposed for the interpretation of the PSInSARTM data at the regional scale, easy to use by the public administrations and by civil protection authorities. Potential and limitations of the PSInSARTM technique for ground movement detection on a regional scale and monitoring are then estimated in relationship with different geological processes and various geological environments. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR))
Open AccessArticle From Maxwell’s Equations to Polarimetric SAR Images: A Simulation Approach
Sensors 2008, 8(11), 7380-7409; doi:10.3390/s8117380
Received: 2 June 2008 / Revised: 26 September 2008 / Accepted: 15 November 2008 / Published: 19 November 2008
Cited by 6 | PDF Full-text (1960 KB) | HTML Full-text | XML Full-text
Abstract
A new electromagnetic approach for the simulation of polarimetric SAR images is proposed. It starts from Maxwell’s equations, employs the spectral domain full-wave technique, the moment method, and the stationary phase method to compute the far electromagnetic fields scattered by multilayer structures. [...] Read more.
A new electromagnetic approach for the simulation of polarimetric SAR images is proposed. It starts from Maxwell’s equations, employs the spectral domain full-wave technique, the moment method, and the stationary phase method to compute the far electromagnetic fields scattered by multilayer structures. A multilayer structure is located at each selected position of a regular rectangular grid of coordinates, which defines the scene area under imaging. The grid is determined taking into account the elementary scatter size and SAR operational parameters, such as spatial resolution, pixel spacing, look angle and platform altitude. A two-dimensional separable “sinc” function to represent the SAR spread point function is also considered. Multifrequency sets of single-look polarimetric SAR images are generated, in L-, C- and X-bands and the images are evaluated using several measurements commonly employed in SAR data analysis. The evaluation shows that the proposed simulation process is working properly, since the obtained results are in accordance with those presented in the literature. Therefore, this new approach becomes suitable for carrying out theoretical and practical studies using polarimetric SAR images. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR))
Open AccessArticle Interferometric Phase Improvement Based on Polarimetric Data Fusion
Sensors 2008, 8(11), 7172-7190; doi:10.3390/s8117172
Received: 2 June 2008 / Revised: 7 September 2008 / Accepted: 7 November 2008 / Published: 13 November 2008
PDF Full-text (1855 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, a method is proposed to improve the interferometric phase quality, based on fusing data from different polarimetric channels. Since lower amplitude implies less reliable phase in general, the phase quality of polarimetric interferometric data can be improved by seeking [...] Read more.
In this paper, a method is proposed to improve the interferometric phase quality, based on fusing data from different polarimetric channels. Since lower amplitude implies less reliable phase in general, the phase quality of polarimetric interferometric data can be improved by seeking optimal fusion of data from different polarizations to maximize the resulting amplitude. In the proposed approach, for each pixel, two coherent polarimetric scattering vectors are synchronously projected onto a same optimum direction, maximizing the lower amplitude of the two projections. In the single-look case, the fused phase is equivalent to the weighted average of phases in all polarimetric channels. It provides a good physical explanation of the proposed approach. Without any filtering, the phase noise and the number of residue points are significantly reduced, and the interferometric phase quality is greatly improved. It is a useful tool to preprocess the phase ahead of phase unwrapping. The Cloude’s coherence optimization method is used for a comparison. Using the data collected by SIR-C/X-SAR, the authors demonstrate the effectiveness and the robustness of the proposed approach. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR))
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Open AccessArticle Rapid Urban Mapping Using SAR/Optical Imagery Synergy
Sensors 2008, 8(11), 7125-7143; doi:10.3390/s8117125
Received: 11 September 2008 / Revised: 7 November 2008 / Accepted: 10 November 2008 / Published: 12 November 2008
Cited by 15 | PDF Full-text (1083 KB) | HTML Full-text | XML Full-text
Abstract
This paper highlights the potential of combining Synthetic Aperture Radar (SAR) and optical data for operational rapid urban mapping. An algorithm consisting of a completely unsupervised procedure for processing pairs of co-registered SAR/optical images is proposed. In a first stage, a texture [...] Read more.
This paper highlights the potential of combining Synthetic Aperture Radar (SAR) and optical data for operational rapid urban mapping. An algorithm consisting of a completely unsupervised procedure for processing pairs of co-registered SAR/optical images is proposed. In a first stage, a texture analysis is conducted independently on the two images using eight different chain-based Gaussian models. In a second stage, the resulting texture images are partitioned by an unsupervised fuzzy K-means approach. Finally, a fuzzy decision rule is used to aggregate the results provided by the classification of texture images obtained from the pair of SAR and optical images. The method was tested and validated on images of Bucharest (Romania) and Cayenne (French Guiana). These two study areas are of different terrain relief, urban settlement structure and land cover complexity. The data set included Radarsat-1/ENVISAT and SPOT-4/5 images. The developed SAR/optical information fusion scheme improved the capabilities of urban areas extraction when compared with the separate use of SAR and optical sensors. It also proved to be suitable for monitoring urbanization development. The encouraging results thus confirm the potential of combining information from SAR and optical sensors for timely urban area analysis, as required in cases of disaster management and planning in urban sprawl areas. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR))
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Open AccessArticle Mesoscale Near-Surface Wind Speed Variability Mapping with Synthetic Aperture Radar
Sensors 2008, 8(11), 7012-7034; doi:10.3390/s8117012
Received: 8 October 2008 / Revised: 31 October 2008 / Accepted: 3 November 2008 / Published: 5 November 2008
Cited by 7 | PDF Full-text (1497 KB) | HTML Full-text | XML Full-text
Abstract
Operationally-significant wind speed variability is often observed within synthetic aperture radar-derived wind speed (SDWS) images of the sea surface. This paper is meant as a first step towards automated distinguishing of meteorological phenomena responsible for such variability. In doing so, the research [...] Read more.
Operationally-significant wind speed variability is often observed within synthetic aperture radar-derived wind speed (SDWS) images of the sea surface. This paper is meant as a first step towards automated distinguishing of meteorological phenomena responsible for such variability. In doing so, the research presented in this paper tests feature extraction and pixel aggregation techniques focused on mesoscale variability of SDWS. A sample of twenty eight SDWS images possessing varying degrees of near-surface wind speed variability were selected to serve as case studies. Gaussian high- and low-pass, local entropy, and local standard deviation filters performed well for the feature extraction portion of the research while principle component analysis of the filtered data performed well for the pixel aggregation. The findings suggest recommendations for future research. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR))
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Open AccessArticle Dielectric Constant Modelling with Soil–Air Composition and Its Effect on Sar Radar Signal Backscattered over Soil Surface
Sensors 2008, 8(11), 6810-6824; doi:10.3390/s8116810
Received: 16 July 2008 / Revised: 27 August 2008 / Accepted: 29 October 2008 / Published: 1 November 2008
Cited by 3 | PDF Full-text (196 KB) | HTML Full-text | XML Full-text
Abstract
The objective of this paper is to present the contribution of a new dielectric constant characterisation for the modelling of radar backscattering behaviour. Our analysis is based on a large number of radar measurements acquired during different experimental campaigns (Orgeval’94, Pays de [...] Read more.
The objective of this paper is to present the contribution of a new dielectric constant characterisation for the modelling of radar backscattering behaviour. Our analysis is based on a large number of radar measurements acquired during different experimental campaigns (Orgeval’94, Pays de Caux’98, 99). We propose a dielectric constant model, based on the combination of contributions from both soil and air fractions. This modelling clearly reveals the joint influence of the air and soil phases, in backscattering measurements over rough surfaces with large clods. A relationship is established between the soil fraction and soil roughness, using the Integral Equation Model (IEM), fitted to real radar data. Finally, the influence of the air fraction on the linear relationship between moisture and the backscattered radar signal is discussed. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR))
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Open AccessArticle Two-dimensional Co-Seismic Surface Displacements Field of the Chi-Chi Earthquake Inferred from SAR Image Matching
Sensors 2008, 8(10), 6484-6495; doi:10.3390/s8106484
Received: 10 June 2008 / Revised: 14 August 2008 / Accepted: 20 October 2008 / Published: 21 October 2008
Cited by 20 | PDF Full-text (1741 KB) | HTML Full-text | XML Full-text
Abstract
The Mw=7.6 Chi-Chi earthquake in Taiwan occurred in 1999 over the Chelungpu fault and caused a great surface rupture and severe damage. Differential Synthetic Aperture Radar Interferometry (DInSAR) has been applied previously to study the co-seismic ground displacements. There have [...] Read more.
The Mw=7.6 Chi-Chi earthquake in Taiwan occurred in 1999 over the Chelungpu fault and caused a great surface rupture and severe damage. Differential Synthetic Aperture Radar Interferometry (DInSAR) has been applied previously to study the co-seismic ground displacements. There have however been significant limitations in the studies. First, only one-dimensional displacements along the Line-of-Sight (LOS) direction have been measured. The large horizontal displacements along the Chelungpu fault are largely missing from the measurements as the fault is nearly perpendicular to the LOS direction. Second, due to severe signal decorrelation on the hangling wall of the fault, the displacements in that area are un-measurable by differential InSAR method. We estimate the co-seismic displacements in both the azimuth and range directions with the method of SAR amplitude image matching. GPS observations at the 10 GPS stations are used to correct for the orbital ramp in the amplitude matching and to create the two-dimensional (2D) co-seismic surface displacements field using the descending ERS-2 SAR image pair. The results show that the co-seismic displacements range from about -2.0 m to 0.7 m in the azimuth direction (with the positive direction pointing to the flight direction), with the footwall side of the fault moving mainly southwards and the hanging wall side northwards. The displacements in the LOS direction range from about -0.5 m to 1.0 m, with the largest displacement occuring in the northeastern part of the hanging wall (the positive direction points to the satellite from ground). Comparing the results from amplitude matching with those from DInSAR, we can see that while only a very small fraction of the LOS displacement has been recovered by the DInSAR mehtod, the azimuth displacements cannot be well detected with the DInSAR measurements as they are almost perpendicular to the LOS. Therefore, the amplitude matching method is obviously more advantageous than the DInSAR in studying the Chi-Chi earthquake. Another advantage of the method is that the displacement in the hanging wall of the fault that is un-measurable with DInSAR due to severe signal decorrelation can almost completely retrieved in this research. This makes the whole co-seismic displacements field clearly visible and the location of the rupture identifiable. Using displacements measured at 15 independent GPS stations for validation, we found that the RMS values of the differences between the two types of results were 6.9 cm and 5.7 cm respectively in the azimuth and the range directions. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR))
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Open AccessArticle An Evaluation of Radarsat-1 and ASTER Data for Mapping Veredas (Palm Swamps)
Sensors 2008, 8(9), 6055-6076; doi:10.3390/s8096055
Received: 6 August 2008 / Revised: 10 September 2008 / Accepted: 22 September 2008 / Published: 26 September 2008
Cited by 6 | PDF Full-text (913 KB) | HTML Full-text | XML Full-text
Abstract
Veredas (palm swamps) are wetland complexes associated with the Brazilian savanna (cerrado) that often represent the only available source of water for the ecosystem during the dry months. Their extent and condition are mainly unknown and their cartography is an [...] Read more.
Veredas (palm swamps) are wetland complexes associated with the Brazilian savanna (cerrado) that often represent the only available source of water for the ecosystem during the dry months. Their extent and condition are mainly unknown and their cartography is an essential issue for their protection. This research article evaluates some of the fine resolution satellite data both in the radar (Radarsat-1) and optical domain (ASTER) for the delineation and characterization of veredas. Two separate approaches are evaluated. First, given the known potential of Radarsat-1 images for wetland inventories, the automatic delineation of veredas is tested using only Radarsat-1 data and a Markov random fields region-based segmentation. In this case, to increase performance, processing is limited to a buffer zone around the river network. Then, characterization of their type is attempted using traditional classification methods of ASTER optical data combined with Radarsat-1 data. The automatic classification of Radarsat data yielded results with an overall accuracy between 62 and 69%, that proved reliable enough for delineating wide and very humid veredas. Scenes from the wet season and with a smaller angle of incidence systematically yielded better results. For the classification of the main vegetation types, better results (overall success of 78.8%) were obtained by using only the visible and near infrared (VNIR) bands of the ASTER image. Radarsat data did not bring any improvement to these classification results. In fact, when using solely the Radarsat data from two different angle of incidence and two different dates, the classification results were low (50.8%) but remained powerful for delineating the permanently moist riparian forest portion of the veredas with an accuracy better than 75% in most cases. These results are considered good given the width of some types often less than 50 m wide compared with the resolution of the images (12.5 - 15 m). Comparing the classification results with the Radarsat-generated delineation allows an understanding of the relation between synthetic aperture radar (SAR) backscattering and vegetation types of the veredas. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR))
Open AccessArticle Tomographic Imaging of a Forested Area By Airborne Multi-Baseline P-Band SAR
Sensors 2008, 8(9), 5884-5896; doi:10.3390/s8095884
Received: 30 May 2008 / Revised: 29 August 2008 / Accepted: 18 September 2008 / Published: 24 September 2008
Cited by 16 | PDF Full-text (9604 KB) | HTML Full-text | XML Full-text
Abstract
In recent years, various attempts have been undertaken to obtain information about the structure of forested areas from multi-baseline synthetic aperture radar data. Tomographic processing of such data has been demonstrated for airborne L-band data but the quality of the focused tomographic [...] Read more.
In recent years, various attempts have been undertaken to obtain information about the structure of forested areas from multi-baseline synthetic aperture radar data. Tomographic processing of such data has been demonstrated for airborne L-band data but the quality of the focused tomographic images is limited by several factors. In particular, the common Fourierbased focusing methods are susceptible to irregular and sparse sampling, two problems, that are unavoidable in case of multi-pass, multi-baseline SAR data acquired by an airborne system. In this paper, a tomographic focusing method based on the time-domain back-projection algorithm is proposed, which maintains the geometric relationship between the original sensor positions and the imaged target and is therefore able to cope with irregular sampling without introducing any approximations with respect to the geometry. The tomographic focusing quality is assessed by analysing the impulse response of simulated point targets and an in-scene corner reflector. And, in particular, several tomographic slices of a volume representing a forested area are given. The respective P-band tomographic data set consisting of eleven flight tracks has been acquired by the airborne E-SAR sensor of the German Aerospace Center (DLR). Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR))
Open AccessArticle SAR Observation and Modeling of Gap Winds in the Prince William Sound of Alaska
Sensors 2008, 8(8), 4894-4914; doi:10.3390/s8084894
Received: 12 July 2008 / Revised: 19 August 2008 / Accepted: 20 August 2008 / Published: 22 August 2008
Cited by 9 | PDF Full-text (6595 KB) | HTML Full-text | XML Full-text
Abstract
Alaska’s Prince William Sound (PWS) is a unique locale tending to have strong gap winds, especially in the winter season. To characterize and understand these strong surface winds, which have great impacts on the local marine and aviation activities, the surface wind [...] Read more.
Alaska’s Prince William Sound (PWS) is a unique locale tending to have strong gap winds, especially in the winter season. To characterize and understand these strong surface winds, which have great impacts on the local marine and aviation activities, the surface wind retrieval from the Synthetic Aperture Radar data (SAR-wind) is combined with a numerical mesoscale model. Helped with the SAR-wind observations, the mesoscale model is used to study cases of strong winds and relatively weak winds to depict the nature of these winds, including the area of extent and possible causes of the wind regimes. The gap winds from the Wells Passage and the Valdez Arm are the most dominant gap winds in PWS. Though the Valdez Arm is north-south trending and Wells Passage is east-west oriented, gap winds often develop simultaneously in these two places when a low pressure system is present in the Northern Gulf of Alaska. These two gap winds often converge at the center of PWS and extend further out of the Sound through the Hinchinbrook Entrance. The pressure gradients imposed over these areas are the main driving forces for these gap winds. Additionally, the drainage from the upper stream glaciers and the blocking effect of the banks of the Valdez Arm probably play an important role in enhancing the gap wind. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR))
Open AccessArticle Ship Detection in SAR Image Based on the Alpha-stable Distribution
Sensors 2008, 8(8), 4948-4960; doi:10.3390/s8084948
Received: 19 June 2008 / Revised: 18 July 2008 / Accepted: 19 July 2008 / Published: 22 August 2008
Cited by 30 | PDF Full-text (1534 KB) | HTML Full-text | XML Full-text
Abstract
This paper describes an improved Constant False Alarm Rate (CFAR) ship detection algorithm in spaceborne synthetic aperture radar (SAR) image based on Alphastable distribution model. Typically, the CFAR algorithm uses the Gaussian distribution model to describe statistical characteristics of a SAR image [...] Read more.
This paper describes an improved Constant False Alarm Rate (CFAR) ship detection algorithm in spaceborne synthetic aperture radar (SAR) image based on Alphastable distribution model. Typically, the CFAR algorithm uses the Gaussian distribution model to describe statistical characteristics of a SAR image background clutter. However, the Gaussian distribution is only valid for multilook SAR images when several radar looks are averaged. As sea clutter in SAR images shows spiky or heavy-tailed characteristics, the Gaussian distribution often fails to describe background sea clutter. In this study, we replace the Gaussian distribution with the Alpha-stable distribution, which is widely used in impulsive or spiky signal processing, to describe the background sea clutter in SAR images. In our proposed algorithm, an initial step for detecting possible ship targets is employed. Then, similar to the typical two-parameter CFAR algorithm, a local process is applied to the pixel identified as possible target. A RADARSAT-1 image is used to validate this Alpha-stable distribution based algorithm. Meanwhile, known ship location data during the time of RADARSAT-1 SAR image acquisition is used to validate ship detection results. Validation results show improvements of the new CFAR algorithm based on the Alpha-stable distribution over the CFAR algorithm based on the Gaussian distribution. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR))
Open AccessArticle Detecting Land Subsidence in Shanghai by PS-Networking SAR Interferometry
Sensors 2008, 8(8), 4725-4741; doi:10.3390/s8084725
Received: 14 July 2008 / Revised: 5 August 2008 / Accepted: 13 August 2008 / Published: 19 August 2008
Cited by 19 | PDF Full-text (4460 KB) | HTML Full-text | XML Full-text
Abstract
Existing studies have shown that satellite synthetic aperture radar (SAR) interferometry has two apparent drawbacks, i.e., temporal decorrelation and atmospheric contamination, in the application of deformation mapping. It is however possible to improve deformation analysis by tracking some natural or man-made objects [...] Read more.
Existing studies have shown that satellite synthetic aperture radar (SAR) interferometry has two apparent drawbacks, i.e., temporal decorrelation and atmospheric contamination, in the application of deformation mapping. It is however possible to improve deformation analysis by tracking some natural or man-made objects with steady radar reflectivity, i.e., permanent scatterers (PS), in the frame of time series of SAR images acquired over the same area. For detecting land subsidence in Shanghai, China, this paper presents an attempt to explore an approach of PS-neighborhood networking SAR interferometry. With use of 26 ERS-1/2 SAR images acquired 1992 through 2002 over Shanghai, the analysis of subsiding process in time and space is performed on the basis of a strong network which is formed by connecting neighboring PSs according to a distance threshold. The linear and nonlinear subsidence, atmospheric effects as well as topographic errors can be separated effectively in this way. The subsidence velocity field in 10 years over Shanghai is also derived. It was found that the annual subsidence rates in the study area range from -2.1 to -0.6 cm/yr, and the averaged subsidence rate reaches -1.1 cm/yr. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR))
Open AccessArticle A Methodology to Validate the InSAR Derived Displacement Field of the September 7th, 1999 Athens Earthquake Using Terrestrial Surveying. Improvement of the Assessed Deformation Field by Interferometric Stacking
Sensors 2008, 8(7), 4119-4134; doi:10.3390/s8074119
Received: 20 March 2008 / Revised: 19 June 2008 / Accepted: 20 June 2008 / Published: 10 June 2008
Cited by 2 | PDF Full-text (1248 KB) | HTML Full-text | XML Full-text
Abstract
The primary objective of this paper is the evaluation of the InSAR derived displacement field caused by the 07/09/1999 Athens earthquake, using as reference an external data source provided by terrestrial surveying along the Mornos river open aqueduct. To accomplish this, a [...] Read more.
The primary objective of this paper is the evaluation of the InSAR derived displacement field caused by the 07/09/1999 Athens earthquake, using as reference an external data source provided by terrestrial surveying along the Mornos river open aqueduct. To accomplish this, a processing chain to render comparable the leveling measurements and the interferometric derived measurements has been developed. The distinct steps proposed include a solution for reducing the orbital and atmospheric interferometric fringes and an innovative method to compute the actual InSAR estimated vertical ground subsidence, for direct comparison with the leveling data. Results indicate that the modeled deformation derived from a series of stacked interferograms, falls entirely within the confidence interval assessed for the terrestrial surveying data. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR))
Open AccessArticle An Assessment of the Altimetric Information Derived from Spaceborne SAR (RADARSAT-1, SRTM3) and Optical (ASTER) Data for Cartographic Application in the Amazon Region
Sensors 2008, 8(6), 3819-3829; doi:10.3390/s8063819
Received: 15 April 2008 / Revised: 27 May 2008 / Accepted: 28 May 2008 / Published: 6 June 2008
Cited by 16 | PDF Full-text (3081 KB) | HTML Full-text | XML Full-text
Abstract
Difficulties in acquiring a complete aerial photography coverage on a regular basis in the Brazilian Amazon due to adverse environmental conditions affect the quality of the national topographic database. As a consequence, topographic information is still poor, and when available needs to [...] Read more.
Difficulties in acquiring a complete aerial photography coverage on a regular basis in the Brazilian Amazon due to adverse environmental conditions affect the quality of the national topographic database. As a consequence, topographic information is still poor, and when available needs to be up-dated or re-mapped. In this research, altimetric information derived from RADARSAT-1 (Fine and Standard modes), SRTM3 (3 arcseconds) and ASTER (band 3N-3B) was evaluated for topographic mapping in two sites located in the region: Serra dos Carajás (mountainous relief) and Tapajós National Forest (flat terrain). The quality of the information produced from Digital Elevation Models (DEMs) was evaluated regarding field altimetric measurements. Precise topographic field information acquired from Differential Global Positioning System (DGPS) was used as Ground Control Points (GCPs) for the modeling of the stereoscopic DEMs (RADARSAT- 1, ASTER) and as Independent Check Points (ICPs) for the calculation of accuracies of the products. The accuracies were estimated by comparison of the DEMs values and real elevation values given by ICPs. The analysis was performed following two approaches: (1) the use of Root Mean Square Error (RMSE) for the overall classification of the DEMs considering the Brazilian Map Accuracy Standards (PEC) limits and, (2) calculations of trend analysis and accuracy based on a methodology that takes into account computed discrepancies and standard deviations. The investigation has shown that for flat relief, the altimetric accuracy of SRTM3 and Fine RADARSAT-1 DEMs fulfilled the PEC requirements for 1:100,000 A Class Map. However, for mountainous terrain, only the altimetry of SRTM3 and ASTER fulfilled these requirements. In addition, the performance of ASTER was slightly superior to SRTM3. However it is important to consider the difficulties in the acquisition of good stereo-pairs with optical data in the Amazon and the additional cost (GCPs) to produce ASTER DEMs. Despite showing systematic errors, the findings justify the usage of SRTM3 as a primary elevation source for semi-detailed topographic mapping in the region. It is suggested a combination of altimetry derived for SRTM3 and planimetry extracted from high-resolution SAR (ALOS/PALSAR, TerraSARX, RADARSAT-2) or if available optical data for semi-detailed topographic mapping programs in the Brazilian Amazon, where terrain information is seldom available or presents low quality. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR))
Open AccessArticle A Two Dimensional Overlapped Subaperture Polar Format Algorithm Based on Stepped-chirp Signal
Sensors 2008, 8(5), 3438-3446; doi:10.3390/s8053438
Received: 3 April 2008 / Accepted: 19 May 2008 / Published: 26 May 2008
Cited by 4 | PDF Full-text (105 KB) | HTML Full-text | XML Full-text
Abstract
In this work, a 2-D subaperture polar format algorithm (PFA) based on steppedchirp signal is proposed. Instead of traditional pulse synthesis preprocessing, the presented method integrates the pulse synthesis process into the range subaperture processing. Meanwhile, due to the multi-resolution property of [...] Read more.
In this work, a 2-D subaperture polar format algorithm (PFA) based on steppedchirp signal is proposed. Instead of traditional pulse synthesis preprocessing, the presented method integrates the pulse synthesis process into the range subaperture processing. Meanwhile, due to the multi-resolution property of subaperture processing, this algorithm is able to compensate the space-variant phase error caused by the radar motion during the period of a pulse cluster. Point target simulation has validated the presented algorithm. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR))
Open AccessArticle SAR System for UAV Operation with Motion Error Compensation beyond the Resolution Cell
Sensors 2008, 8(5), 3384-3405; doi:10.3390/s8053384
Received: 12 March 2008 / Accepted: 14 May 2008 / Published: 23 May 2008
Cited by 23 | PDF Full-text (713 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents an experimental Synthetic Aperture Radar (SAR) system that is under development in the Universidad Politécnica de Madrid. The system uses Linear Frequency Modulated Continuous Wave (LFM-CW) radar with a two antenna configuration for transmission and reception. The radar operates [...] Read more.
This paper presents an experimental Synthetic Aperture Radar (SAR) system that is under development in the Universidad Politécnica de Madrid. The system uses Linear Frequency Modulated Continuous Wave (LFM-CW) radar with a two antenna configuration for transmission and reception. The radar operates in the millimeter-wave band with a maximum transmitted bandwidth of 2 GHz. The proposed system is being developed for Unmanned Aerial Vehicle (UAV) operation. Motion errors in UAV operation can be critical. Therefore, this paper proposes a method for focusing SAR images with movement errors larger than the resolution cell. Typically, this problem is solved using two processing steps: first, coarse motion compensation based on the information provided by an Inertial Measuring Unit (IMU); and second, fine motion compensation for the residual errors within the resolution cell based on the received raw data. The proposed technique tries to focus the image without using data of an IMU. The method is based on a combination of the well known Phase Gradient Autofocus (PGA) for SAR imagery and typical algorithms for translational motion compensation on Inverse SAR (ISAR). This paper shows the first real experiments for obtaining high resolution SAR images using a car as a mobile platform for our radar. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR))
Open AccessArticle The Landcover Impact on the Aspect/Slope Accuracy Dependence of the SRTM-1 Elevation Data for the Humboldt Range
Sensors 2008, 8(5), 3134-3149; doi:10.3390/s8053134
Received: 18 February 2008 / Accepted: 8 May 2008 / Published: 15 May 2008
Cited by 4 | PDF Full-text (5039 KB) | HTML Full-text | XML Full-text
Abstract
The U.S. National Landcover Dataset (NLCD) and the U.S National Elevation Dataset (NED) (bare earth elevations) were used in an attempt to assess to what extent the directional and slope dependency of the Shuttle Radar Topography Mission (SRTM) finished digital elevation model [...] Read more.
The U.S. National Landcover Dataset (NLCD) and the U.S National Elevation Dataset (NED) (bare earth elevations) were used in an attempt to assess to what extent the directional and slope dependency of the Shuttle Radar Topography Mission (SRTM) finished digital elevation model is affected by landcover. Four landcover classes: forest, shrubs, grass and snow cover, were included in the study area (Humboldt Range in NW portion of Nevada, USA). Statistics, rose diagrams, and frequency distributions of the elevation differences (NED-SRTM) per landcover class per geographic direction were used. The decomposition of elevation differences on the basis of aspect and slope terrain classes identifies a) over-estimation of elevation by the SRTM instrument along E, NE and N directions (negative elevation difference that decreases linearly with slope) while b) underestimation is evident towards W, SW and S directions (positive elevation difference increasing with slope). The aspect/slope/landcover elevation differences modelling overcome the systematic errors evident in the SRTM dataset and revealed vegetation height information and the snow penetration capability of the SRTM instrument. The linear regression lines per landcover class might provide means of correcting the systematic error (aspect/slope dependency) evident in SRTM dataset. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR))
Open AccessArticle A Novel Modified Omega-K Algorithm for Synthetic Aperture Imaging Lidar through the Atmosphere
Sensors 2008, 8(5), 3056-3066; doi:10.3390/s8053056
Received: 20 December 2007 / Accepted: 14 April 2008 / Published: 6 May 2008
Cited by 3 | PDF Full-text (107 KB) | HTML Full-text | XML Full-text
Abstract
The spatial resolution of a conventional imaging lidar system is constrained by the diffraction limit of the telescope’s aperture. The combination of the lidar and synthetic aperture (SA) processing techniques may overcome the diffraction limit and pave the way for a higher [...] Read more.
The spatial resolution of a conventional imaging lidar system is constrained by the diffraction limit of the telescope’s aperture. The combination of the lidar and synthetic aperture (SA) processing techniques may overcome the diffraction limit and pave the way for a higher resolution air borne or space borne remote sensor. Regarding the lidar transmitting frequency modulation continuous-wave (FMCW) signal, the motion during the transmission of a sweep and the reception of the corresponding echo were expected to be one of the major problems. The given modified Omega-K algorithm takes the continuous motion into account, which can compensate for the Doppler shift induced by the continuous motion efficiently and azimuth ambiguity for the low pulse recurrence frequency limited by the tunable laser. And then, simulation of Phase Screen (PS) distorted by atmospheric turbulence following the von Karman spectrum by using Fourier Transform is implemented in order to simulate turbulence. Finally, the computer simulation shows the validity of the modified algorithm and if in the turbulence the synthetic aperture length does not exceed the similar coherence length of the atmosphere for SAIL, we can ignore the effect of the turbulence. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR))
Open AccessArticle Multiscale Unsupervised Segmentation of SAR Imagery Using the Genetic Algorithm
Sensors 2008, 8(3), 1704-1711; doi:10.3390/s8031704
Received: 17 January 2008 / Accepted: 25 February 2008 / Published: 12 March 2008
Cited by 6 | PDF Full-text (171 KB) | HTML Full-text | XML Full-text
Abstract
A valid unsupervised and multiscale segmentation of synthetic aperture radar(SAR) imagery is proposed by a combination GA-EM of the Expectation Maximization(EM) algorith with the genetic algorithm (GA). The mixture multiscale autoregressive(MMAR) model is introduced to characterize and exploit the scale-to-scale statisticalvariations and [...] Read more.
A valid unsupervised and multiscale segmentation of synthetic aperture radar(SAR) imagery is proposed by a combination GA-EM of the Expectation Maximization(EM) algorith with the genetic algorithm (GA). The mixture multiscale autoregressive(MMAR) model is introduced to characterize and exploit the scale-to-scale statisticalvariations and statistical variations in the same scale in SAR imagery due to radar speckle,and a segmentation method is given by combining the GA algorithm with the EMalgorithm. This algorithm is capable of selecting the number of components of the modelusing the minimum description length (MDL) criterion. Our approach benefits from theproperties of the Genetic and the EM algorithm by combination of both into a singleprocedure. The population-based stochastic search of the genetic algorithm (GA) exploresthe search space more thoroughly than the EM method. Therefore, our algorithm enablesescaping from local optimal solutions since the algorithm becomes less sensitive to itsinitialization. Some experiment results are given based on our proposed approach, andcompared to that of the EM algorithms. The experiments on the SAR images show that theGA-EM outperforms the EM method. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR))
Open AccessArticle Temporal Stability of Soil Moisture and Radar Backscatter Observed by the Advanced Synthetic Aperture Radar (ASAR)
Sensors 2008, 8(2), 1174-1197; doi:10.3390/s80201174
Received: 11 January 2008 / Accepted: 19 February 2008 / Published: 21 February 2008
Cited by 12 | PDF Full-text (1333 KB) | HTML Full-text | XML Full-text
Abstract
The high spatio-temporal variability of soil moisture is the result of atmosphericforcing and redistribution processes related to terrain, soil, and vegetation characteristics.Despite this high variability, many field studies have shown that in the temporal domainsoil moisture measured at specific locations is correlated [...] Read more.
The high spatio-temporal variability of soil moisture is the result of atmosphericforcing and redistribution processes related to terrain, soil, and vegetation characteristics.Despite this high variability, many field studies have shown that in the temporal domainsoil moisture measured at specific locations is correlated to the mean soil moisture contentover an area. Since the measurements taken by Synthetic Aperture Radar (SAR)instruments are very sensitive to soil moisture it is hypothesized that the temporally stablesoil moisture patterns are reflected in the radar backscatter measurements. To verify this hypothesis 73 Wide Swath (WS) images have been acquired by the ENVISAT AdvancedSynthetic Aperture Radar (ASAR) over the REMEDHUS soil moisture network located inthe Duero basin, Spain. It is found that a time-invariant linear relationship is well suited forrelating local scale (pixel) and regional scale (50 km) backscatter. The observed linearmodel coefficients can be estimated by considering the scattering properties of the terrainand vegetation and the soil moisture scaling properties. For both linear model coefficients,the relative error between observed and modelled values is less than 5 % and thecoefficient of determination (R2) is 86 %. The results are of relevance for interpreting anddownscaling coarse resolution soil moisture data retrieved from active (METOP ASCAT)and passive (SMOS, AMSR-E) instruments. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR))

Review

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Open AccessReview Applications of SAR Interferometry in Earth and Environmental Science Research
Sensors 2009, 9(3), 1876-1912; doi:10.3390/s90301876
Received: 23 September 2008 / Revised: 10 December 2009 / Accepted: 12 March 2009 / Published: 13 March 2009
Cited by 24 | PDF Full-text (305 KB) | HTML Full-text | XML Full-text
Abstract
This paper provides a review of the progress in regard to the InSAR remote sensing technique and its applications in earth and environmental sciences, especially in the past decade. Basic principles, factors, limits, InSAR sensors, available software packages for the generation of [...] Read more.
This paper provides a review of the progress in regard to the InSAR remote sensing technique and its applications in earth and environmental sciences, especially in the past decade. Basic principles, factors, limits, InSAR sensors, available software packages for the generation of InSAR interferograms were summarized to support future applications. Emphasis was placed on the applications of InSAR in seismology, volcanology, land subsidence/uplift, landslide, glaciology, hydrology, and forestry sciences. It ends with a discussion of future research directions. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR))
Open AccessReview Improvement of the Accuracy of InSAR Image Co-Registration Based On Tie Points – A Review
Sensors 2009, 9(2), 1259-1281; doi:10.3390/s90201259
Received: 12 January 2009 / Revised: 11 February 2009 / Accepted: 17 February 2009 / Published: 24 February 2009
Cited by 6 | PDF Full-text (2970 KB) | HTML Full-text | XML Full-text
Abstract
Interferometric Synthetic Aperture Radar (InSAR) is a new measurement technology, making use of the phase information contained in the Synthetic Aperture Radar (SAR) images. InSAR has been recognized as a potential tool for the generation of digital elevation models (DEMs) and the [...] Read more.
Interferometric Synthetic Aperture Radar (InSAR) is a new measurement technology, making use of the phase information contained in the Synthetic Aperture Radar (SAR) images. InSAR has been recognized as a potential tool for the generation of digital elevation models (DEMs) and the measurement of ground surface deformations. However, many critical factors affect the quality of InSAR data and limit its applications. One of the factors is InSAR data processing, which consists of image co-registration, interferogram generation, phase unwrapping and geocoding. The co-registration of InSAR images is the first step and dramatically influences the accuracy of InSAR products. In this paper, the principle and processing procedures of InSAR techniques are reviewed. One of important factors, tie points, to be considered in the improvement of the accuracy of InSAR image co-registration are emphatically reviewed, such as interval of tie points, extraction of feature points, window size for tie point matching and the measurement for the quality of an interferogram. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR))
Open AccessReview Oil Spill Detection by SAR Images: Dark Formation Detection, Feature Extraction and Classification Algorithms
Sensors 2008, 8(10), 6642-6659; doi:10.3390/s8106642
Received: 10 June 2008 / Revised: 24 August 2008 / Accepted: 21 October 2008 / Published: 23 October 2008
Cited by 64 | PDF Full-text (278 KB) | HTML Full-text | XML Full-text
Abstract
This paper provides a comprehensive review of the use of Synthetic Aperture Radar images (SAR) for detection of illegal discharges from ships. It summarizes the current state of the art, covering operational and research aspects of the application. Oil spills are seriously [...] Read more.
This paper provides a comprehensive review of the use of Synthetic Aperture Radar images (SAR) for detection of illegal discharges from ships. It summarizes the current state of the art, covering operational and research aspects of the application. Oil spills are seriously affecting the marine ecosystem and cause political and scientific concern since they seriously effect fragile marine and coastal ecosystem. The amount of pollutant discharges and associated effects on the marine environment are important parameters in evaluating sea water quality. Satellite images can improve the possibilities for the detection of oil spills as they cover large areas and offer an economical and easier way of continuous coast areas patrolling. SAR images have been widely used for oil spill detection. The present paper gives an overview of the methodologies used to detect oil spills on the radar images. In particular we concentrate on the use of the manual and automatic approaches to distinguish oil spills from other natural phenomena. We discuss the most common techniques to detect dark formations on the SAR images, the features which are extracted from the detected dark formations and the most used classifiers. Finally we conclude with discussion of suggestions for further research. The references throughout the review can serve as starting point for more intensive studies on the subject. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR))
Figures

Open AccessReview Atmospheric Effects on InSAR Measurements and Their Mitigation
Sensors 2008, 8(9), 5426-5448; doi:10.3390/s8095426
Received: 28 July 2008 / Revised: 29 August 2008 / Accepted: 29 August 2008 / Published: 3 September 2008
Cited by 60 | PDF Full-text (1695 KB) | HTML Full-text | XML Full-text
Abstract
Interferometric Synthetic Aperture Radar (InSAR) is a powerful technology for observing the Earth surface, especially for mapping the Earth's topography and deformations. InSAR measurements are however often significantly affected by the atmosphere as the radar signals propagate through the atmosphere whose state [...] Read more.
Interferometric Synthetic Aperture Radar (InSAR) is a powerful technology for observing the Earth surface, especially for mapping the Earth's topography and deformations. InSAR measurements are however often significantly affected by the atmosphere as the radar signals propagate through the atmosphere whose state varies both in space and in time. Great efforts have been made in recent years to better understand the properties of the atmospheric effects and to develop methods for mitigating the effects. This paper provides a systematic review of the work carried out in this area. The basic principles of atmospheric effects on repeat-pass InSAR are first introduced. The studies on the properties of the atmospheric effects, including the magnitudes of the effects determined in the various parts of the world, the spectra of the atmospheric effects, the isotropic properties and the statistical distributions of the effects, are then discussed. The various methods developed for mitigating the atmospheric effects are then reviewed, including the methods that are based on PSInSAR processing, the methods that are based on interferogram modeling, and those that are based on external data such as GPS observations, ground meteorological data, and satellite data including those from the MODIS and MERIS. Two examples that use MODIS and MERIS data respectively to calibrate atmospheric effects on InSAR are also given. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR))
Open AccessReview On the Soil Roughness Parameterization Problem in Soil Moisture Retrieval of Bare Surfaces from Synthetic Aperture Radar
Sensors 2008, 8(7), 4213-4248; doi:10.3390/s8074213
Received: 22 May 2008 / Revised: 30 May 2008 / Accepted: 25 June 2008 / Published: 15 July 2008
Cited by 124 | PDF Full-text (254 KB) | HTML Full-text | XML Full-text
Abstract
Synthetic Aperture Radar has shown its large potential for retrieving soil moisture maps at regional scales. However, since the backscattered signal is determined by several surface characteristics, the retrieval of soil moisture is an ill-posed problem when using single configuration imagery. Unless [...] Read more.
Synthetic Aperture Radar has shown its large potential for retrieving soil moisture maps at regional scales. However, since the backscattered signal is determined by several surface characteristics, the retrieval of soil moisture is an ill-posed problem when using single configuration imagery. Unless accurate surface roughness parameter values are available, retrieving soil moisture from radar backscatter usually provides inaccurate estimates. The characterization of soil roughness is not fully understood, and a large range of roughness parameter values can be obtained for the same surface when different measurement methodologies are used. In this paper, a literature review is made that summarizes the problems encountered when parameterizing soil roughness as well as the reported impact of the errors made on the retrieved soil moisture. A number of suggestions were made for resolving issues in roughness parameterization and studying the impact of these roughness problems on the soil moisture retrieval accuracy and scale. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR))
Open AccessReview Interferometric Synthetic Aperture Microscopy: Computed Imaging for Scanned Coherent Microscopy
Sensors 2008, 8(6), 3903-3931; doi:10.3390/s8063903
Received: 5 June 2008 / Revised: 9 June 2008 / Accepted: 9 June 2008 / Published: 11 June 2008
Cited by 22 | PDF Full-text (7538 KB) | HTML Full-text | XML Full-text
Abstract
Three-dimensional image formation in microscopy is greatly enhanced by the use of computed imaging techniques. In particular, Interferometric Synthetic Aperture Microscopy (ISAM) allows the removal of out-of-focus blur in broadband, coherent microscopy. Earlier methods, such as optical coherence tomography (OCT), utilize interferometric [...] Read more.
Three-dimensional image formation in microscopy is greatly enhanced by the use of computed imaging techniques. In particular, Interferometric Synthetic Aperture Microscopy (ISAM) allows the removal of out-of-focus blur in broadband, coherent microscopy. Earlier methods, such as optical coherence tomography (OCT), utilize interferometric ranging, but do not apply computed imaging methods and therefore must scan the focal depth to acquire extended volumetric images. ISAM removes the need to scan the focus by allowing volumetric image reconstruction from data collected at a single focal depth. ISAM signal processing techniques are similar to the Fourier migration methods of seismology and the Fourier reconstruction methods of Synthetic Aperture Radar (SAR). In this article ISAM is described and the close ties between ISAM and SAR are explored. ISAM and a simple strip-map SAR system are placed in a common mathematical framework and compared to OCT and radar respectively. This article is intended to serve as a review of ISAM, and will be especially useful to readers with a background in SAR. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar (SAR))

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