Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar Research Articles

Oil Spill Detection in Quad-Polarimetric SAR Images Using an Advanced Convolutional Neural Network Based on SuperPixel Model

Oil spill detection plays an important role in marine environment protection. Quad-polarimetric Synthetic Aperture Radar (SAR) has been proved to have great potential for this task, and different SAR polarimetric features have the advantages to recognize oil spill areas from other look-alikes. In this paper we proposed an oil spill detection method based on convolutional neural network (CNN) and Simple Linear Iterative Clustering (SLIC) superpixel. Experiments were conducted on three Single Look Complex (SLC) quad-polarimetric SAR images obtained by Radarsat-2 and Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR). Several groups of polarized parameters, including H/A/Alpha decomposition, Single-Bounce Eigenvalue Relative Difference (SERD), correlation coefficients, conformity coefficients, Freeman 3-component decomposition, Yamaguchi 4-component decomposition were extracted as feature sets. Among all considered polarimetric features, Yamaguchi parameters achieved the highest performance with total Mean Intersection over Union (MIoU) of 90.5%. It is proved that the SLIC superpixel method significantly improved the oil spill classification accuracy on all the polarimetric feature sets. The classification accuracy of all kinds of targets types were improved, and the largest increase on mean MIoU of all features sets was on emulsions by 21.9%.

Influence of Wave Polarization on the Texture Characteristics of Objects in Radar Images

The influence of wave polarization on texture parameters of objects in radar images (RIs) is examined by calculations of the second-order statistics (the fractal dimension and the Haralick textural features) on the basis of polarimetric data acquired with the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) system for two wavelengths of the C- and L-ranges. The variance analysis of the samples of fractal dimension values for natural forested and water objects have revealed no influence of polarization on the values before the speckle filtering; however, after speckle filtering, statistically valid differences have been found in the mean values of some pairs of samples. For sample pairs of the copolarizations VV–HH and cross polarizations HV–VH, a random nature of the differences observed in the mean fractal dimension values has been shown. This conclusion is also true for the Haralick textural features of a water object—the contrast, inverse moment, and entropy. Statistically valid differences in the mean values of the Haralick textural features for urban and water objects have been revealed both before and after speckle filtering. For a forested object, variance analysis shows that the polarization-dependent differences in the mean values of the textural feature samples are statistically unreliable.

Sea Surface Wind Retrievals from SIR-C/X-SAR Data: A Revisit

The Geophysical Model Function (GMF) XMOD1 provides a linear algorithm for sea surface wind field retrievals for the Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar (SIR-C/X-SAR). However, the relationship between the normalized radar cross section (NRCS) and the sea surface wind speed, wind direction and incidence angles is non-linear. Therefore, in this paper, XMOD1 is revisited using the full dataset of X-SAR acquired over the ocean. We analyze the detailed relationship between the X-SAR NRCS, incidence angle and sea surface wind speed. Based on the C-band GMF CMOD_IFR2, an updated empirical retrieval model of the sea surface wind field called SIRX-MOD is derived. In situ buoy measurements and the scatterometer data of ERS-1/SCAT are used to validate the retrieved sea surface wind speeds from the X-SAR data with SIRX-MOD, which respectively yield biases of 0.13 m/s and 0.16 m/s and root mean square (RMS) errors of 1.83 m/s and 1.63 m/s.

Classification of sediments on exposed tidal flats in the German Bight using multi-frequency radar data

We present a new method for the extraction of roughness parameters of sand ripples on exposed tidal flats from multi-frequency synthetic aperture radar (SAR) data. The method is based on the Integral Equation Model (IEM) which predicts the normalized radar cross-section (NRCS) of randomly rough dielectric surfaces. The data used for this analysis were acquired in the German Bight of the North Sea by the Spaceborne Imaging Radar-C/X-Band SAR (SIR-C/X-SAR) in 1994. In-situ measurements of the root-mean-squared (rms) height and the correlation length of the sand ripples clearly demonstrate a relationship between these roughness parameters and the C-band NRCS determined from an ERS SAR image. Using the IEM we have calculated NRCS isolines for the three frequency bands deployed by SIR-C/X-SAR (L, C, and X band), as a function of the rms height and the correlation length of the sand ripples. For each SIR-C/X-SAR image pixel these two roughness parameters were determined from the intersections of the NRCS isolines at different radar bands, and they were used for a crude sediment classification for a small test area at the German North Sea coast. Comparing our results with available sediment maps, we conclude that the presented method is very promising for tidal flat classification by using data from presently existing airborne and future spaceborne multi-frequency SAR systems.

A new unsupervised classification algorithm for polarimetric sar images based on fuzzy set theory

In this letter, a new method is proposed for unsupervised classification of terrain types and man-made objects using POLarimetric Synthetic Aperture Radar (POLSAR) data. This technique is a combination of the usage of polarimetric information of SAR images and the unsupervised classification method based on fuzzy set theory. Image quantization and image enhancement are used to preprocess the POLSAR data. Then the polarimetric information and Fuzzy C-Means (FCM) clustering algorithm are used to classify the preprocessed images. The advantages of this algorithm are the automated classification, its high classification accuracy, fast convergence and high stability. The effectiveness of this algorithm is demonstrated by experiments using SIR-C/X-SAR (Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar) data.

Spaceborne imaging radar-C/X-band synthetic aperture radar (SIR-C/X-SAR): a look back on the tenth anniversary

The spaceborne imaging radar-C, X-band synthetic aperture radar (SIR-C/X-SAR) missions have resulted in important scientific discoveries and provided new insights into Earth system processes. Analyses of SIR-C/X-SAR engineering-mode data have also led to new measurement and mission concepts. The multifrequency, multipolarisation capability provided by SIR-C/X-SAR is unsurpassed from a spaceborne system, making the data set valuable for algorithm development and assessment of optimal imaging parameters more than a decade after the missions were flown.

A summary of experimental results to assess the contribution of SAR for mapping vegetation biomass and soil moisture

This paper is an overview of the most recent results obtained by Italian groups involved in the spaceborne imaging radar-C,X-band synthetic aperture radar (SIR-C/X-SAR) hydrological experiment, by using multi-frequency and multi-polarization synthetic aperture radar (SAR) data measured by JPL/AIRSAR, SIR-C, EMISAR, ERS-1, and JERS-1 sensors. The sensitivity of backscattering coefficients to some geophysical parameters that play a significant role in hydrological processes, such as vegetation biomass, soil moisture, and surface roughness, is discussed. Experimental results show that P band appears to be suitable for the monitoring of forest biomass, whereas L band is mainly sensitive to the biomass of wide-leaf crops and C band to narrow-leaf crops. Moreover, the L-band sensor gives the highest contribution in estimating soil moisture and surface roughness. The sensitivity of backscatter to soil moisture and surface roughness for individual agricultural fields is rather low, since both parameters affect the radar signal. However, by observing data collected at different dates and averaged over a relatively wide agricultural area, the correlation with soil moisture becomes considerable, since the effects of spatial roughness variations are smoothed. Retrievals of both soil moisture and surface roughness were performed using a semi-empirical model.

Review article Synthetic aperture radar (SAR) frequency and polarization requirements for applications in ecology, geology, hydrology, and oceanography: A tabular status quo after SIR-C/X-SAR

The Spaceborne Imaging Radar-C, X-Band Synthetic Aperture Radar (SIR-C/X-SAR) was the first multi-frequency and multi-polarization SAR system to be launched into space. SIR-C/X-SAR imaged over 300 sites around the Earth returning 143 terabits of data. There has been a tremendous advancement of knowledge in the field of radar remote sensing accomplished in the last two years, as well as verification of earlier findings since the two successful SIR-C/X-SAR missions. This review article presents the current status of optimal SAR parameters for various key issues within the disciplines of ecology, geology, hydrology, and oceanography. A polarimetric X- and L-band radar is suggested as a result of our review for future SAR sensors. The design of a single frequency, albeit polarimetric, SAR satellite, limits applications, as can be deduced from the tables.

Microwave snowpack studies made in the Austrian Alps during the SIR-C/X-SAR experiment

Surface-based microwave studies made in the Austrian Alps during the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/XSAR) experiment in April 1994 are described, and are compared with the SAR data. The SAR test region included glaciers and unglaciated surfaces which were snow covered. Clear differences between these two surface types were observed with the SIR-C/X-SAR. In addition, the angular dependencies of the backscattering were useful in order to distinguish between the accumulation and the ablation areas of the glaciers, and the snow-covered areas showed characteristic differences depending on the presence or absence of layers containing wet snow. The surface-based studies were carried out at an alpine meadow in the valley Kaunertal at an altitude of 2160 m. The measurements included snow-physical observations supported by microwave dielectric probes, microwave radiometers at 21 and 35GHz and polarimetric scatterometers at 5.3 and 35 GHz. The dielectric measurements were used to retrieve the liquid-water profile of the snowpack. Three main layers were observed: a wet bottom layer as a remnant of a warm period in March, a thick crust (i.e., the refrozen part of the old pack), and a fresh and mostly dry snow layer on top. Except for the top layer, the temporal changes were small during the observation period from 8 to 12 April 1994. The radiometric measurements made at 21 and 35GHz showed pronounced temporal variations of the brightness temperature in the afternoons due to melt-and-refreeze cycles in the fresh snow. The liquid water in the top layer was monitored by a special radiometric method using a metal plate at the bottom of this layer. The radiometer and scatterometer measurements revealed the refrozen crust as the dominant scatterer, especially at 35 GHz. However, the wet bottom layer inhibited the detection of signals scattered at the snow-ground interface and therefore reduced the backscatter at 5.3 GHz. The comparison of the C-band SAR data with those of the C-band scatterometer shows higher returns in the SAR data for the considered test site. Explanations for the differences are discussed. Nevertheless, also the SAR backscatter data are clearly lower in the zones where wet snow was present than in areas either covered by dry snow or which were snow-free.

An evaluation of AIRSAR and SIR-C/X-SAR images for mapping northern forest attributes in Maine, USA

In previous work by the authors, multifrequency, polarimetric airborne synthetic aperture radar (AIRSAR) data were used to characterize forest categories and biomass density of a forest area in Maine, USA. This study area was included as a test site for ecological studies during the Spaceborne Imaging Radar C/X-band Synthetic Aperture Radar (SIR-C/X-SAR) missions in 1994. The SIR-C/X-SAR missions provided the first opportunity for Earth scientists to receive multifrequency and multipolarization SAR data from space from a single platform. During the Space Radar Laboratory missions in April and October 1994, images from AIRSAR and SIR-C/X-SAR were acquired for the same areas within a few days of each other. In this paper, the capabilities of AIRSAR and SIR-C/X-SAR images for characterizing a northern hardwood-boreal transitional forest were evaluated and compared. The use of multiple frequency, polarimetric information to produce forest-cover classification, biomass estimates, and forest spatial pattern analysis were investigated. The results from SIR-C/X-SAR compared with those from AIRSAR were generally similar despite different available frequencies (C-band, L-band, X-band vs. C-band, L-band, P-band) and resolution (25.0 m vs. 8.3 m). AIRSAR data better enabled the mapping of stands of hardwood and mixed forests than did SIR-C/X-SAR data. However, SIR-C/X-SAR produced better classification results for conifer forest stands. There was no great benefit from using higher resolution for classification except for forest stands in which there were mixtures of species (i.e., hardwood and softwood). A comparison of the image data also showed that both instruments could provide reasonable estimates of biomass density up to about 15 kg/m 2. At higher biomass levels, both AIRSAR and SIR-C showed the well-known biomass saturation effect. The average biomass densities determined from the AIRSAR and SIR-C images were reasonably close at 9.7 kg/m 2 and 9.0 kg/m 2, respectively. Finally, spatial character of the image data was examined by using perimeter and area relations and lacunarity analysis. The results were consistent between the two instruments and showed that the forest opening patterns were self-similar for openings greater than about 3 ha.

Overview of the Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar (SIR-C/X-SAR) missions

The Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar (SIR-C/X-SAR), the most advanced imaging radar system to have flown in Earth orbit, was carried in the cargo bay of the Space Shuttle Endeavour in April and October 1994. SIR-C/X-SAR simultaneously recorded data at three wavelengths (L-, C-, and X-bands; 23.5 cm, 5.8 cm, and 3.1 cm, respectively). In addition, the full polarimetric scattering matrix was obtained at L- and C-band over a variety of terrain and vegetation types. Scientists are using multifrequency, polarimetric SIR-C/X-SAR data in studies of geology, hydrology, ecology, oceanography, and radar remote sensing techniques. The October SIR-C/X-SAR flight also included acquisition of experimental repeat-pass interferometry data which have been used to generate digital elevation models and to detect surface motions in volcanic, tectonic, and glacial terrains. Results from SIR-C/X-SAR clearly show the increased value of using multiparameter and interferometric capabilities to characterize Earth's surface and vegetation cover and to generate geophysical products compared with optical sensors or single-channel radars alone.

Use of multifrequency, multipolarization shuttle imaging radar for volcano mapping in the Kunlun Mountains of Western China

A group of volcanoes northeast of Aksayqin Lake, in the western Kunlun Mountains, China, have been identified on multifrequency, multipolarization spaceborne imaging radar-C/X-band synthetic aperture radar (SIR-C/X-SAR) images. Field observations made on the volcanic morphology and terrain features are described in this paper. Analysis of single-band, single-polarization radar backscatter coefficients (σ°) shows that LHV best discriminates the two types of lava flows (pahoehoe and aa lavas), alluvium, and bedrock. The factors affecting the radar backscatter coefficient also are analyzed. Finally, this paper presents KAr isotopic ages of volcanic samples collected in the field and discusses the volcanism in the area.

Overview of results of Spaceborne Imaging Radar-C, X-Band Synthetic Aperture Radar (SIR-C/X-SAR)

The Spaceborne Imaging Radar-C, X-Band Synthetic Aperture Radar (SIR-C/X-SAR) was launched on the Space Shuttle Endeavour for two ten day missions in the spring and fall of 1994. Radar data from these missions are being used to better understand the dynamic global environment. During each mission, radar images of over 300 sites around the Earth were obtained, returning over a terabit of data. SIR-C/X-SAR science investigations were focused on quantifying radar's ability to estimate surface properties of importance to understanding global change; and focused studies in geology, ecology, hydrology and oceanography, as well as radar calibration and electromagnetic theory studies. In addition, the second flight featured an interferometry experiment, where digital elevation maps were obtained by interfering data from the first and second shuttle flight, and from successive days on the second flight. SIR-C/X-SAR data have been used to validate algorithms which produce maps of vegetation type and biomass; snow, soil and vegetation moisture; and the distribution of wetlands, developed with earlier aircraft data.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

The SIR-C/X-SAR Synthetic Aperture Radar system

The Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) was a joint United States/German/Italian space agency imaging radar system successfully flown aboard the shuttle Endeavor in April 1994 and again in September/October 1994. The multifaceted SIR-C/X-SAR represents a major technological step forward in radar remote sensing and is the first spaceborne multifrequency, polarimetric SAR. The United States developed SIR-C operated at L- and C-band, each with quad polarization. The SIR-C antenna was an active phased array, with the capability for electronic beam steering and multiple swath width illumination. The German/Italian X-SAR operated at X-band with a single polarization using a slotted waveguide antenna, mechanically steerable in elevation. SIR-C and X-SAR were designed to operate synchronously, collecting data over common sites synchronously. A total of 143 hours (93 terabits) of SAR data were recorded on tape.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

SIR-C/X-SAR: A multifaceted radar

The multifaceted Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar (SIR-C/X-SAR) was successfully flown twice in 1994 aboard the Shuttle Endeavour as part of an international imaging radar mission. The United States SIR-C operated at L- and C-band, each with multiple polarization, utilizing an active phased array antenna. The German/Italian X-SAR operated at X-band with a single polarization. SIR-C and X-SAR operated synchronously to collect data over common sites. Data were collected for repeat-track interferometric processing at all three frequencies. A total of 143 hours (93 terabits) of SAR data were digitally recorded on tape over the two flights for subsequent processing in the U.S., Germany, and Italy. This advanced multifrequency/multipolarization system has produced a rich radar data set for Earth scientific investigation and demonstration of spaceborne radar remote sensing capabilities.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>