Suppression of speckle in synthetic aperture radar images using wavelet

A filter for suppressing speckle in synthetic aperture radar (SAR) images utilizing wavelet is proposed. The filter suppresses speckle by reducing the amplitude of the detail images in wavelet subspaces, while preserving edges by releasing the amplitude reduction around edges; information on edges, contained in the detail images, is utilized for edge detection. Simulations and application to SAR images have shown that the performance of the filter is satisfactory in both smoothing and edge preservation, and in generating visually-natural images as well.     

逆合成孔径雷达在驼峰测速系统中的应用

目前使用的驼峰测速雷达一般安装在轨旁,应用多普勒原理对溜放车组的速度进行测量,一部雷达只能测量一个股道的溜放车组速度.现基于逆合成孔径雷达测速原理,提出将雷达侧向安装在溜放线路一侧的上方,并建立了雷达回波数学模型,采用了一种基于自聚焦的溜放车组速度估计算法.仿真结果表明:该算法能够精确地连续测量多股道溜放车组的瞬时速度.     

Remotely sensed measurements of forest structure and fuel loads in the Pinelands of New Jersey

We used a single-beam, first return profiling LIDAR (Light Detection and Ranging) measurements of canopy height, intensive biometric measurements in plots, and Forest Inventory and Analysis (FIA) data to quantify forest structure and ladder fuels (defined as vertical fuel continuity between the understory and canopy) in the New Jersey Pinelands. The LIDAR data were recorded at 400 Hz over three intensive areas of 1 km² where transects were spaced at 200 m, and along 64 transects spaced 1 km apart (total of ca. 2500 km²). LIDAR and field measurements of canopy height were similar in the three intensive study areas, with the 80th percentile of LIDAR returns explaining the greatest amount of variability (79%). Correlations between LIDAR data and aboveground tree biomass measured in the field were highly significant when all three 1 km² areas were analyzed collectively, with the 80th percentile again explaining the greatest amount of variability (74%). However, when intensive areas were analyzed separately, correlations were poor for Oak/Pine and Pine/Scrub Oak stands. Similar results were obtained using FIA data; at the landscape scale, mean canopy height was positively correlated with aboveground tree biomass, but when forest types were analyzed separately, correlations were significant only for some wetland forests (Pitch Pine lowlands and mixed hardwoods; r² = 0.74 and 0.59, respectively), and correlations were poor for upland forests (Oak/Pine, Pine/Oak and Pine/Scrub Oak, r² = 0.33, 0.11 and 0.21, respectively). When LIDAR data were binned into 1-m height classes, more LIDAR pulses were recorded from the lowest height classes in stands with greater shrub biomass, and significant differences were detected between stands where recent prescribed fire treatments had been conducted and unburned areas. Our research indicates that single-beam LIDAR can be used for regional-scale (forest biomass) estimates, but that relationships between height and biomass can be poorer at finer scales within individual forest types. Binned data are useful for estimating the presence of ladder fuels (vertical continuity of leaves and branches) and horizontal fuel continuity below the canopy.     

The use of segmentation and shape recognition techniques in synthetic aperture radar images

This paper discusses the use of shape recognition techniques in the context of Synthetic Aperture Radar (SAR) images. Results of a study using small bright targets in simulated imagery are presented.     

Decomposition of polarimetric synthetic aperture radar backscatter from upland and flooded forests

The goal of this research was to decompose polarimetric Synthetic Aperture Radar (SAR) imagery of upland and flooded forests into three backscatter types: single reflection, double reflection, and cross-polarized backscatter. We used a decomposition method that exploits the covariance matrix of backscatter terms. First we applied this method to SAR imagery of dihedral and trihedral corner reflectors positioned on a smooth, dry lake bed, and verified that it accurately isolated the different backscatter types. We then applied the method to decompose multi-frequency Jet Propulsion Laboratory (JPL) airborne SAR (AIRSAR) backscatter from upland and flooded forests to explain scattering components in SAR imagery from forested surfaces. For upland ponderosa pine forest in California, as SAR wavelength increased from C-band to P-band, scattering with an odd number of reflections decreased and scattering with an even number of reflections increased. There was no obvious trend with wavelength for cross-polarized scattering. For a bald cypress-tupelo floodplain forest in Georgia, scattering with an odd number of reflections dominated at C-band. Scattering power with an even number of reflections from the flooded forest was strong at L-band and strongest at P-band. Cross-polarized scattering may not be a major component of total backscatter at all three wavelengths. Various forest structural classes and land cover types were readily distinguishable in the imagery derived by the decomposition method. More importantly, the decomposition method provided a means of unraveling complex interactions between radar signals and vegetated surfaces in terms of scattering mechanisms from targets. The decomposed scattering components were additions to the traditional HH and V V backscatter. One cautionary note: the method was not well suited to targets with low backscatter and a low signal-to-noise ratio.     

Noise reduction in synthetic aperture radar images using fuzzy logic and genetic algorithm

Synthetic aperture radar (SAR) is a self-illuminating imaging technique; it produces high resolution images in all weather conditions, day and night. SAR images are widely accepted and used by many application scientists. However, the SAR images are corrupted with speckle noise. Speckle noises are caused by random interference of electromagnetic signals scattered by the object surface within one resolution element. The amount of noise and distribution of noise corrupting the image is unpredictable. Conventional noise filters are quantitative in nature; they are not well suited for uncertainty problems. Fuzzy logic is capable of handling uncertainty. In this work, noisy pixels in the images are identified by using fuzzy rules and filtered using fuzzy weighted mean, keeping the healthy pixels unchanged. The optimum value of parameters used in defining fuzzy membership function is determined by using genetic algorithm (GA). Reducing noise and simultaneously preserving image details are the two most desirable characteristics of noise filters. Peak signal-to-noise ratio (PSNR) and edge preserving factor (EPF) are used to evaluate the performance of the proposed fuzzy filter. SAR images affected by varying amounts of speckle noise are used to evaluate the performance. It was observed that the proposed filter suppresses noise and preserves image edges.

     

Cover. Wind energy mapping of coastal zones by synthetic aperture radar (SAR) for siting potential windmill locations

MERIS (Medium Resolution Imaging Spectrometer) is a fine spectral and medium spatial resolution satellite sensor and is part of the core instrument payload of Envisat, the European Space Agency's (ESA) environmental research satellite, launched in March 2002. Designed primarily for ocean (‘MER’) and coastal zone remote sensing, this imaging spectrometer (‘IS’) now has a much broader environmental remit covering also land and atmospheric applications. This paper reviews (i) MERIS's development history, focusing on its changing mission objectives; (ii) MERIS's technical specification, including its radiometric, spectral and geometric characteristics, programmability and onboard calibration; (iii) decisions that led to modifications of MERIS's spectral, geometric and radiometric performance for land applications; (iv) MERIS's data products; and (v) some of the ways in which MERIS data might be used to provide information on terrestrial vegetation.     

The use of biophysical indices and coefficient of variation derived from airborne synthetic aperture radar for monitoring the spread of aquatic vegetation in tropical reservoirs

This paper compares the use of biophysical indices and coefficients of variation derived from airborne synthetic aperture radar for discriminating and characterising land cover classes in the Tucurui reservoir. It assumes that the structural and dielectric properties of the land cover classes are sufficiently distinct to permit their discrimination using airborne C-band SAR data at different polarizations. Analyses of the results show that any of the proposed indices can be used effectively to discriminate among the land cover classes in the Tucurui reservoir. Certain combinations of polarizations and biophysical indices can, however, improve the saparability of the land cover classes.     

Wetland mapping in the Congo Basin using optical and radar remotely sensed data and derived topographical indices

This study reports results of a classification tree approach to mapping the wetlands of the Congo Basin, focusing on the Cuvette Centrale of the Congo River watershed, an area of 1,176,000 km². Regional expert knowledge was used to train passive optical remotely sensed imagery of the Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) sensors, JERS-1 active radar L-band imagery, and topographical indices derived from 3 arc sec elevation data of the Shuttle Radar Topography Mission (SRTM). All data inputs were resampled to a common 57 m resolution grid. A classification tree bagging procedure was employed to produce a final map of per-grid cell wetland probability. Thirty bagged trees were ranked and the median result was selected to produce the final wetland probability map. Thresholding the probability map at < 0.5 yielded a proportion of wetland cover for the study area of 32%, equivalent to 360,000 km². Wetlands predominate in the CARPE Lake Tele-Lake Tumba landscape located in the western part of the Democratic Republic of the Congo and the south-eastern Republic of Congo, where they constitute 56% of the landscape. Local topography depicting relative elevation for sub-catchments proved to be the most valuable discriminator of wetland cover. However, all sources of information (i.e. optical, radar and topography) featured prominently in contributing to the classification tree procedure, reinforcing the idea that multi-source data are useful in the characterization of wetland land cover. The method employed freely available data and a fully automated process, except for training data collection. Comparisons to existing maps and in situ field observations indicate improvements compared to previous efforts.     

Range ambiguity suppression in a synthetic aperture radar using pulse phase coding and two-pulse cancellation

ABSTRACT

In the presence of range ambiguity, the synthetic aperture radar (SAR) systems suffer from image aliasing, which dramatically degrades the quality of SAR images. In this article, an easy-to-implement technique for range ambiguity suppression is investigated, which is based on phase coding in the transmit pulse dimension, referred to as pulse phase coding (PPC). By properly designing the PPC series, it is possible to discriminate the range ambiguous echoes from different range areas in the Doppler frequency domain. To further suppress the range ambiguous echo, a two-pulse cancellation (TPC)-based SAR imaging method is proposed, which improves the quality of SAR images in the presence of range ambiguity. The proposed two-pulse cancellation is performed followed by the azimuth compression. The simulation results demonstrate the effectiveness of the proposed method.     

A technique for the identification and analysis of icebergs in synthetic aperture radar images of Antarctica

This paper describes an image analysis technique developed to identify icebergs depicted in synthetic aperture radar images of Antarctica and to determine the outlines of these icebergs. The technique uses a pixel bonding process to delineate the edges of the icebergs. It then separates them from the background water and sea ice by an edge-guided image segmentation process. Characteristics such as centroid position and iceberg area were calculated for each iceberg segment and placed in a file for input to appropriate statistical data analysis software. The technique has been tested on three ERS-1 SAR sub-images in which it succeeded in identifying virtually all segments containing icebergs of size six pixels or larger. The images were first passed through an averaging filter to reduce speckle. This process produced a pixel size of 100m x 100m. As implemented, the technique overestimates iceberg areas by about 20% on average and the detection rate falls off rapidly for icebergs less than six pixels in size. Performance in these areas is expected to improve when additional stages, based on a more detailed analysis of pixel intensity, are implemented.     

Assessment of C-band synthetic aperture radar data for mapping and monitoring Coastal Plain forested wetlands in the Mid-Atlantic Region,U.S.A.

Multi-temporal C-band SAR data (C-HH and C-VV), collected by ERS-2 and ENVISAT satellite systems, are compared with field observations of hydrology (i.e., inundation and soil moisture) and National Wetland Inventory maps (U.S. Fish and Wildlife Service) of a large forested wetland complex adjacent to the Patuxent and Middle Patuxent Rivers, tributaries of the Chesapeake Bay. Multi-temporal C-band SAR data were shown to be capable of mapping forested wetlands and monitoring hydroperiod (i.e., temporal fluctuations in inundation and soil moisture) at the study site, and the discrimination of wetland from upland was improved with 10 m digital elevation data. Principal component analysis was used to summarize the multi-temporal SAR data sets and to isolate the dominant temporal trend in inundation and soil moisture (i.e., relative hydroperiod). Significant positive, linear correlations were found between the first principal component and percent area flooded and soil moisture. The correlation (r²) between the first principal component (PC1) of multi-temporal C-HH SAR data and average soil moisture was 0.88 (p = < .0001) during the leaf-off season and 0.87 (p = < .0001) during the leaf-on season, while the correlation between PC1 and average percent area inundated was 0.82 (p = < .0001) and 0.47 (p = .0016) during the leaf-off and leaf-on seasons, respectively. When compared to field data, the SAR forested wetland maps identified areas that were flooded for 25% of the time with 63–96% agreement and areas flooded for 5% of the time with 44–89% agreement, depending on polarization and time of year. The results are encouraging and justify further studies to attempt to quantify the relative SAR-derived hydroperiod classes in terms of physical variables and also to test the application of SAR data to more diverse landscapes at a broader scale. The present evidence suggests that the SAR data will significantly improve routine wooded wetland mapping.     

Review Article. The imaging of waves by satelliteborne synthetic aperture radar: the effects of sea-surface motion

The effects of sea-surface velocities in the imaging of waves by synthetic aperture radar (SAR) are considered using the ‘facet’ concept of the backscattering process. It is shown that if the sea wave spectrum is divided at the nominal limit of resolution of the SAR the effect of the long and short wavelength parts can be considered separately, the former being treated by numerical simulation and the latter by statistical methods. It is found that the motions due to: the short wavelengths produce an azimuthal smearing which can be represented by a Gaussian low-pass filter acting on the azimuthal component of wavenumber in the image. The cut-off wavelength is typically some hundreds of metres in moderate winds. Images obtained with the SEASAT SAR frequently show such an effect.     

Mapping hydrologically sensitive areas on the Boreal Plain: a multitemporal analysis of ERS synthetic aperture radar data

Characterizing the spatial and temporal dynamics of hydrologically sensitive areas (HSAs) is vital to the effective management of the boreal forest. HSAs are defined as saturated or inundated areas that, if disturbed, might result in a significant change in the movement of water, nutrients and biota within landscapes. This study presents a remote sensing technique that uses archived European Remote Sensing Satellite (ERS)‐1 and ERS‐2 synthetic aperture radar (SAR) images to monitor HSAs in the Willow River watershed (1030 km²) on the western Boreal Plain of Canada. ERS images were used to generate a probability of HSA occurrence map for a 10‐year period (1991–2000). This map revealed the complexity of HSAs on the western Boreal Plain, where some areas remained consistently dry or wet whereas others were dynamic, transitioning from dry to wet and vice versa. A probability map of HSA occurrence provides spatial and temporal information previously unavailable for this region that may expand our understanding of the hydrological behaviour of drainage basins and serve as a planning tool for land management decisions.     

Patterns of irrigated rice growth and malaria vector breeding in Mali using multi-temporal ERS-2 synthetic aperture radar

We explored the use of the European Remote Sensing Satellite 2 Synthetic Aperture Radar (ERS-2 SAR) to trace the development of rice plants in an irrigated area near Niono, Mali and relate that to the density of anopheline mosquitoes, especially An. gambiae. This is important because such mosquitoes are the major vectors of malaria in sub-Saharan Africa, and their development is often coupled to the cycle of rice development. We collected larval samples, mapped rice fields using GPS and recorded rice growth stages simultaneously with eight ERS-2 SAR acquisitions. We were able to discriminate among rice growth stages using ERS-2 SAR backscatter data, especially among the early stages of rice growth, which produce the largest numbers of larvae. We could also distinguish between basins that produced high and low numbers of anophelines within the stage of peak production. After the peak, larval numbers dropped as rice plants grew taller and thicker, reducing the amount of light reaching the water surface. ERS-2 SAR backscatter increased concomitantly. Our data support the belief that ERS-2 SAR data may be helpful for mapping the spatial patterns of rice growth, distinguishing different agricultural practices, and monitoring the abundance of vectors in nearby villages.     

Ocean sand ridge signatures in the Bohai Sea observed by satellite ocean color and synthetic aperture radar measurements

Satellite measurements from Synthetic Aperture Radar (SAR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua platform are used to study the ocean sand ridges in the eastern Bohai Sea in China. Even though the imaging mechanisms for SAR and MODIS-Aqua remote sensing are different, the sand ridges are shown to have exactly the same patterns in images from both sensors. Therefore, the location, extension and coverage of the ocean sand ridges can be detected and cross-examined by both SAR and MODIS-Aqua observations. Satellite images show quite different sand ridge distribution pattern from the published bathymetry map (based on in situ data) that shows six sand ridges in the area. 10 finger-shaped sand ridges are identified from satellite observations. The tidal-current/sand-ridge interaction driven physical and optical changes are assessed and evaluated. The existence of sand ridges causes enhanced water diffuse attenuation coefficient K_d(490) and elevated normalized water-leaving radiance at the red and near-infrared (NIR) wavelengths. The sea surface over the sand ridges experiences significant seasonal variability of water turbidity and shows remarkable differences from nearby ocean regions. During winter, K_d(490) values are about 2-3 m^− 1 over the ridges, while the maximum K_d(490) in the neighboring oceans is approximately 1.5 m^− 1. In summer, the enhancement of the sea surface turbidity is less significant than that which occurs in winter.     

A technique to estimate topsoil thickness in arid and semi-arid areas of north-eastern Jordan using synthetic aperture radar data

A Japanese Earth Resources Satellite (JERS)-1 L-band synthetic aperture radar (SAR) dataset was used for estimating topsoil thickness, of different types, in arid and semi-arid areas in north-eastern Jordan. In this research, the relationship between remotely sensed data, backscattering coefficient and the thickness of topsoil was investigated. Based on the dielectric constant properties of the topsoil samples, the relationship between the backscattering coefficient and the topsoil thickness was obtained by developing a multilayer modelling analysis. Using this model, the topsoil thickness had been estimated by means of the derived backscattering coefficients from JERS-1 SAR image. The estimated thickness values of the different topsoil types were found to be comparable with field ground data. The estimated minimum thickness for hardpan topsoil is 55?cm; Qaa topsoil, 74?cm; and topsoil of herbaceous area, 46?cm, while the estimated maximum thickness is more than 98?cm, more than 100?cm, and 82?cm, respectively. Ground data, on the other hand, revealed the minimum thickness for hardpan topsoil to be 50?cm; Qaa topsoil, 70?cm; and topsoil of herbaceous area, 40?cm, while the maximum thickness is more than 120?cm, more than 100?cm, and 80?cm, respectively.     

Multi-temporal monitoring of wetland water levels in the Florida Everglades using interferometric synthetic aperture radar (InSAR)

Interferometric synthetic aperture radar (InSAR) techniques can successfully detect phase variations related to the water level changes in wetlands and produce spatially detailed high-resolution maps of water level changes. Despite the vast details, the usefulness of the wetland InSAR observations is rather limited, because hydrologists and water resources managers need information on absolute water level values and not on relative water level changes. We present an InSAR technique called Small Temporal Baseline Subset (STBAS) for monitoring absolute water level time series using radar interferograms acquired successively over wetlands. The method uses stage (water level) observation for calibrating the relative InSAR observations and tying them to the stage's vertical datum. We tested the STBAS technique with two-year long Radarsat-1 data acquired during 2006-2008 over the Water Conservation Area 1 (WCA1) in the Everglades wetlands, south Florida (USA). The InSAR-derived water level data were calibrated using 13 stage stations located in the study area to generate 28 successive high spatial resolution maps (50 m pixel resolution) of absolute water levels. We evaluate the quality of the STBAS technique using a root mean square error (RMSE) criterion of the difference between InSAR observations and stage measurements. The average RMSE is 6.6 cm, which provides an uncertainty estimation of the STBAS technique to monitor absolute water levels. About half of the uncertainties are attributed to the accuracy of the InSAR technique to detect relative water levels. The other half reflects uncertainties derived from tying the relative levels to the stage stations' datum.     

Topographic features of the Bristol Channel sea-bed: a comparison of SEASAT (synthetic aperture radar) and side-scan sonar images

Side-scan sonar data collected in 1977 and 1983 from the Bristol Channel are compared with 1978 SEASAT images, in order to determine the limiting physical dimensions of positive and negative topographic features detectable by SEASAT. The identification of sea-bed topography is related to a change in current speed which, in turn, is controlled bythe relief:water-depth ratio. In a water depth of 45mwith a surface current speed of about 70cms ^?1, for example, features > 11 m in relief and with a spacing > 500 m are visible.

The widths of tone-change bands on SEASAT images are found to be related to the ‘effective’ widths of the topographic features that are modifying the flow conditions. The tone-change band sequence is related to positive and negative relief of the bed, under a particular current direction.     

Laser remote sensing of canopy habitat heterogeneity as a predictor of bird species richness in an eastern temperate forest, USA

Habitat heterogeneity has long been recognized as a fundamental variable indicative of species diversity, in terms of both richness and abundance. Satellite remote sensing data sets can be useful for quantifying habitat heterogeneity across a range of spatial scales. Past remote sensing analyses of species diversity have largely been limited to correlative studies based on the use of vegetation indices or derived land cover maps. A relatively new form of laser remote sensing (lidar) provides another means to acquire information on habitat heterogeneity. Here we examine the efficacy of lidar metrics of canopy structural diversity as predictors of bird species richness in the temperate forests of Maryland, USA. Canopy height, topography and the vertical distribution of canopy elements were derived from lidar imagery of the Patuxent National Wildlife Refuge and compared to bird survey data collected at referenced grid locations. The canopy vertical distribution information was consistently found to be the strongest predictor of species richness, and this was predicted best when stratified into guilds dominated by forest, scrub, suburban and wetland species. Similar lidar variables were selected as primary predictors across guilds. Generalized linear and additive models, as well as binary hierarchical regression trees produced similar results. The lidar metrics were also consistently better predictors than traditional remotely sensed variables such as canopy cover, indicating that lidar provides a valuable resource for biodiversity research applications.