Double Bounce Research Articles

The double Brewster angle effect

Abstract The Double Brewster angle effect (DBE) is an extension of the Brewster angle to double reflection on two orthogonal dielectric surfaces. It results from the combination of two pseudo-Brewster angles occurring in complementary incidence angles domains. It can be observed for a large range of incidence angles provided that double bounces mechanism is present. As a consequence of this effect, we show that the reflection coefficient at VV polarization can be at least 10 dB lower than the reflection coefficient at HH polarization over a wide range of incidence angle – typically from 20 to 70 ∘ . It is experimentally demonstrated using a Synthetic Aperture Radar (SAR) image that this effect can be seen on buildings and forests. For large buildings, the difference can reach more than 20 dB.

Three-Component Decomposition of Polarimetric SAR Data Integrating Eigen-Decomposition Results

This paper presents a novel three-component scattering power decomposition of polarimetric SAR data. There are two problems in three-component decomposition method: volume scattering component overestimation in urban areas and artificially set parameter to be a fixed value. Though volume scattering component overestimation can be partly solved by deorientation process, volume scattering still dominants some oriented urban areas. The speckle-like decomposition results introduced by artificially setting value are not conducive to further image interpretation. This paper integrates the results of eigen-decomposition to solve the aforementioned problems. Two principal eigenvectors are used to substitute the surface scattering model and the double bounce scattering model. The decomposed scattering powers are obtained using a constrained linear least-squares method. The proposed method has been verified using an ESAR PolSAR image, and the results show that the proposed method has better performance in urban area.

On the potential of Polarimetric SAR Interferometry to characterize the biomass, moisture and structure of agricultural crops at L-, C- and X-Bands

Polarimetric SAR Interferometry (Pol-InSAR) has shown great promise for estimating the height of agricultural crops through the inversion of a scattering model of the plant canopy and the soil. The inversion also provides estimates of model parameters describing the microwave attenuation within the canopy and the relative scattering contributions from canopy and soil surface.Here, we investigate how vegetation characteristics including biomass, water content (VWC) and canopy structure are related to these parameters and provide a first assessment of the potential of estimating such characteristics using Pol-InSAR time series in L-, C- and X-Bands.The overall attenuation for maize is positively related to total VWC in L- and C-Bands. Furthermore, larger attenuation in VV than HH points toward the existence of anisotropic propagation effects due to vertical orientation of the stalks.Conversely, for wheat in C- and X-Bands there is no consistent relation between attenuation loss and VWC. Rather, structural changes occurring within the plant growth cycle appear to have an appreciable polarization-dependent effect on the observed attenuation changes.In addition, the estimated normalized volume backscattering power NVP (a measure of the relative scattering contribution from the canopy compared to the underlying soil) is associated with wet biomass. However, the contrasting sign of this relation (negative for maize in L- and C-Bands; positive for wheat in C- and X-Bands) indicates again the role of crop structural properties in the Pol-InSAR measurements. For instance, the NVP for maize in L- and C-Bands appears to decrease with increasing biomass due to the increasingly important double bounce ground-stalk scattering contribution as plants become taller and thicker.Overall, these results indicate the sensitivity of the Pol-InSAR parameters to canopy structure and biomass; this sensitivity is however dependent, amongst others, on crop type and radar frequency. When choosing an appropriate baseline/frequency configuration, the Pol-InSAR attenuation loss and NVP may complement the information of the estimated crop height, especially if the latter shows very little variation over the plant growth cycle (e.g. as for wheat).

AUTOMATIC COREGISTRATION FOR MULTIVIEW SAR IMAGES IN URBAN AREAS

Abstract. Due to the high resolution property and the side-looking mechanism of SAR sensors, complex buildings structures make the registration of SAR images in urban areas becomes very hard. In order to solve the problem, an automatic and robust coregistration approach for multiview high resolution SAR images is proposed in the paper, which consists of three main modules. First, both the reference image and the sensed image are segmented into two parts, urban areas and nonurban areas. Urban areas caused by double or multiple scattering in a SAR image have a tendency to show higher local mean and local variance values compared with general homogeneous regions due to the complex structural information. Based on this criterion, building areas are extracted. After obtaining the target regions, L-shape structures are detected using the SAR phase congruency model and Hough transform. The double bounce scatterings formed by wall and ground are shown as strong L- or T-shapes, which are usually taken as the most reliable indicator for building detection. According to the assumption that buildings are rectangular and flat models, planimetric buildings are delineated using the L-shapes, then the reconstructed target areas are obtained. For the orignal areas and the reconstructed target areas, the SAR-SIFT matching algorithm is implemented. Finally, correct corresponding points are extracted by the fast sample consensus (FSC) and the transformation model is also derived. The experimental results on a pair of multiview TerraSAR images with 1-m resolution show that the proposed approach gives a robust and precise registration performance, compared with the orignal SAR-SIFT method.

Critical Analysis of Model-Based Incoherent Polarimetric Decomposition Methods and Investigation of Deorientation Effect

This paper critically analyzes several incoherent model-based decomposition methods for assessing the effect of deorientation in characterization of various land covers. It has been found that even after performing decomposition, ambiguity still occurs in scattering response from various land covers, such as urban and vegetation. Researchers introduced the concept of deorientation to remove this ambiguity. Therefore, in this paper, a critical analysis has been carried out using seven different three- and four-component decomposition methods with and without deorientation and two Eigen decomposition-based methods to investigate the scattering response on various land covers, such as urban, vegetation, bare soil, and water. The comprehensive evaluation of decomposition and deorientation effect has been performed by both visual and quantitative analyses. Two types of quantitative analysis have been performed; first, by observing percentage of scattering power and second, by analyzing the variation in the number of pixels in different land covers for each scattering contribution. The analysis shows that deorientation increases not only the power but also the number of pixels for surface and double bounce scattering. The number of pixels representing volume scattering remain almost the same for all the methods with or without deorientation, whereas volume scattering power reduces after deorientation. Eigen decomposition-based methods are observed to solve the problem of overestimation of volume scattering power.

Adaptive model based on polarimetric decomposition using correlation coefficient in horizontal–vertical and circular basis

This paper presents two decomposition schemes for polarimetric synthetic aperture radar data. The proposed schemes intend to overcome the problem of scattering ambiguity and reduce the volume scattering power in oriented urban areas. The first proposed scheme uses an empirical volume model based on the correlation coefficients of the Pauli component in the horizontal–vertical basis, whereas the second one employs a volume model defined on correlation coefficients of the Pauli components expressed in the circular basis. The correlation coefficients are calculated from polarimetric interferometric synthetic aperture radar (PolInSAR) data. The characteristics adopted from these volume models are used to enhance the results of the decomposition schemes. The scattering powers estimated from the proposed methods give promising results compared to existing methods in the literature, particularly in urban areas since all the oriented built-up areas are well discriminated as double or odd bounce scattering. The methods are evaluated using the experimental airborne SAR sensor (E-SAR) PolInSAR L band data acquired on the Oberpfaffenhofen test site in Germany.

Scattering property based contextual PolSAR speckle filter

Reliability of the scattering model based polarimetric SAR (PolSAR) speckle filter depends upon the accurate decomposition and classification of the scattering mechanisms. This paper presents an improved scattering property based contextual speckle filter based upon an iterative classification of the scattering mechanisms. It applies a Cloude-Pottier eigenvalue-eigenvector decomposition and a fuzzy H/α classification to determine the scattering mechanisms on a pre-estimate of the coherency matrix. The H/α classification identifies pixels with homogeneous scattering properties. A coarse pixel selection rule groups pixels that are either single bounce, double bounce or volume scatterers. A fine pixel selection rule is applied to pixels within each canonical scattering mechanism. We filter the PolSAR data and depending on the type of image scene (urban or rural) use either the coarse or fine pixel selection rule. Iterative refinement of the Wishart H/α classification reduces the speckle in the PolSAR data. Effectiveness of this new filter is demonstrated by using both simulated and real PolSAR data. It is compared with the refined Lee filter, the scattering model based filter and the non-local means filter. The study concludes that the proposed filter compares favorably with other polarimetric speckle filters in preserving polarimetric information, point scatterers and subtle features in PolSAR data.

Sensitivity of Sentinel-1 backscatter to characteristics of buildings

ABSTRACTIn this study, Sentinel-1 interferometric wide swath (IW) mode backscatter is analysed with respect to physical parameters of buildings in Tallinn, Estonia. Dependence on height, alignment, density, shape, and material is shown and discussed. Distribution of backscatter was estimated with respect to each of the parameters, and a correlation matrix of all physical parameters and backscatter values was computed. Height has the strongest effect on backscatter values for both polarization bands, while shape and alignment to orbit has weaker effect on the backscatter. Relationship of co-polarized and cross-polarized backscatter with how a building is aligned with respect to the satellite’s look angle indicates that double bounce from wall–ground interactions is still the dominant scattering mechanism detected by Sentinel-1 in IW mode with 20 m resolution. In order to establish possible detection problems related to specifically oriented buildings at different latitudes, dihedral backscatter is modelled for buildings of oblong and square shapes. Results from this study should be used to improve existing and develop new urban area detection methods based on Sentinel-1 data.

Sea Wind Extraction From RADARSAT-2 and Scatterometer Data Over the Gulf of Mexico

A marine wind field extraction methodology that produced results with $1.5 \times 1.5$ km of spatial resolution using RADARSAT-2 wide and ScanSAR narrow acquisition modes was applied over the Gulf of Mexico. Bootstrap method with median values was applied on the spatial resampling step and showed to be efficient to eliminate extreme $\sigma _{0}$ values from double bounce by targets on the water, which are undesirable for wind estimation, without the need of postprocess to exclude outliers. An empirical CMOD-IFR2 model was used with wind direction information to initialize the model obtained from QuikSCAT scatterometer. The estimated values were compared with measurements from four anemometers. Modeled wind fields were resampled at the same QuikSCAT spatial resolution with the bootstrap method, and correlation coefficients were found to be greater than 0.75 for all ScanSAR narrow images. The initial spatial resolution probably plays an important issue on the results, as the correlation coefficients for all wide images were almost zero. This hypothesis must be further investigated.

Multi-incidence angle RISAT-1 Hybrid Polarimetric SAR data for large area mapping of maize crop – a case study in Khagaria district, Bihar, India

ABSTRACTAnalysis of hybrid polarimetric synthetic aperture radar data has gained importance in the last couple of years with the availability of spaceborne data from Radar Imaging Satellite-1 (RISAT-1). RISAT-1 provides right circular transmit and linear receive data in Fine Resolution Stripmap-1 (FRS-1) mode with a swath of 25 km approximately covering 625 km2 areas. But an administrative unit, like a district, in India cannot be covered in single FRS-1 acquisition. In this article, the possibility of acquisition of multi-incidence angle FRS-1 data to cover a larger area in three consecutive days over Khagaria district of Bihar State, India, for maize crop discrimination and mapping was investigated. It was assumed that the difference of 3 days in imaging does not affect the backscatter response from maize crop as there will not be much change in the maize crop characteristics in 3 days. The backscatter response of maize crop, which is in maximum vegetative stage, was studied at three incidence angles (viz. 28°, 42°, and 52°). The analysis was carried out for the discrimination of maize crop at each incidence angle in Raney derived hybrid decomposition parameters viz. Odd bounce, Double bounce, and Volume scattering mechanisms. The result shows that there is a slight difference in the backscatter response from maize crop due to the changes in incidence angle from 28° to 42° and has not shown any significant difference from 42° to 52°. However, the maize crop got well discriminated in the scatter plots of volume and double bounce scattering at both 28° and 42° and with odd and volume scattering combinations at 52°. The classification of the multi-incidence angle data resulted in 47,732 ha of maize cropped area in Khagaria district during rabi (winter season), 2014–15 with the producer’s accuracy of 92.00%.

Identification of Altered Minerals Based on Synthetic Aperture Radar (SAR) For Mineral Exploration in a Tropical Area

Geological investigation by remote sensing using surface physical properties in tropical regions is challenging. To minimize the effects of atmosphere and vegetation in the obtained optical images, we used the synthetic aperture radar (SAR) images. The phased array L-band synthetic aperture radar (PALSAR) onboard the advanced land observing satellite (ALOS) was selected due to ability of the L-band to penetrate clouds and canopy vegetation. The polarimetric decomposition method based on Cloude–Pottier classification was used as the basis for backscattering analyses. The Ciseuti area in West Java, Indonesia was selected as the study site due to the existence of mining activities, including gold and galena mines. The identification is focused on the spatial distribution of prospected minerals regardless of cloud and vegetation canopy. The classified prospect zones could be extended using the Cloude– Pottier polarimetric decomposition into moderate random entropy and alpha double bounce scattering at argillic alterations, moderate random entropy and alpha surface scattering at intermediate argillic alterations, and highly moderate random entropy and alpha volume diffusion at advanced argillic alterations. The entropy and alpha extracted from ALOS PALSAR data based on Cloude–Pottier decomposition were very useful for identifying alteration zones.

Scattering Property Analysis of Supraglacial Debris Using Target Decomposition on Polarimetric SAR Imagery

Supraglacial debris is widely distributed in the ablation zones of the glaciers in mountain valleys, and it influences glacier melting considerably. Polarimetric Synthetic Aperture Radar (SAR) presents promising results in terms of glacier classification and monitoring, but the scattering mechanism of debris has been unclear until now. In this paper, we attempted to verify the main scattering components of debris in the L- and C-bands polarimetric SAR images. A newly developed target decomposition method that is specially designed for debris is used to quantitatively analyze the scattering component. The method combines the X-Bragg surface scattering, double bounce, and completely random volume scattering models. The results from the target decomposition agree well with the scattering property analysis from the phase difference and entropy-alpha methods. The Keqikaer glacier, which is in the southern Tianshan Mountains, is selected as the study area. Phased-Array L-band SAR (PALSAR) images from the Advanced Land Observing Satellite (ALOS), PALSAR-2 images from ALOS-2, and RADARSAT-2 polarimetric SAR images are employed. The results show that in the C-band, surface scattering is dominant in debris, and it accounts for approximately 70% of the total power; in the L-band, volume scattering increases to a larger portion (approximately 40%), but remains slightly weaker than surface scattering (approximately 56%).

Modeling method on acoustic scattering from penetrable objects using a hybrid Kirchhoff/ray approach

A method is put forward to investigate the acoustic scattering from double-sided water loaded targets which is penetrable even in high frequency. The present approach is an extension of the TriKirch method which was elaborated for non-penetrable targets [J. Acoust. Soc. Am. 140(3), 1878-1886 (2016)] and complex targets are dispersed into many triangular planar facets. Reflection coefficient of plane facet is introduced to calculate the scattering amplitude of each non-rigid triangular facets combined with TirKirch method, and the total scattering amplitude of target is obtained by superposing the amplitude of all facets’ contributions coherently. Double bounce (DB) contributions to the scattering is calculating by ray-tracing method. Computations are made for a double-sided water loaded finite cylindrical shell with perforated ring ribs, and are compared with the experimental results，and both results show good agreement.

PENGOLAHAN CITRA SATELIT ALOS PALSAR MENGGUNAKAN METODE POLARIMETRI UNTUK KLASIFIKASI LAHAN WILAYAH KOTA PADANG


 
 
 
 The image processing of Alos PalSAR satellite data level 1.1 for land classification in Padang City is described in this work. The full polarimetry method is adopted in classification process which can receive and process all combinations of the four polarizations of HH, HV, VH, and VV. Yamaguchi Decomposition is applied in polarimetry method and four classification objects are obtained. Based on the modification of class simplification, the surface scattering is presented in blue color which generally describes the waters on the surface of the earth, green color for volumetric scattering, which describes about plants and forest, red or pink for the double bounce scattering depicting the settlement, urban and building and yellow for helix scattering which is the same as double bounce but the helix will more clearly identify the plant-covered settlements.
 
 
 

Soil Moisture Estimation over Vegetated Agricultural Areas: Tigris Basin, Turkey from Radarsat-2 Data by Polarimetric Decomposition Models and a Generalized Regression Neural Network

Determining the soil moisture in agricultural fields is a significant parameter to use irrigation systems efficiently. In contrast to standard soil moisture measurements, good results might be acquired in a shorter time over large areas by remote sensing tools. In order to estimate the soil moisture over vegetated agricultural areas, a relationship between Radarsat-2 data and measured ground soil moistures was established by polarimetric decomposition models and a generalized regression neural network (GRNN). The experiments were executed over two agricultural sites on the Tigris Basin, Turkey. The study consists of four phases. In the first stage, Radarsat-2 data were acquired on different dates and in situ measurements were implemented simultaneously. In the second phase, the Radarsat-2 data were pre-processed and the GPS coordinates of the soil sample points were imported to this data. Then the standard sigma backscattering coefficients with the Freeman–Durden and H/A/α polarimetric decomposition models were employed for feature extraction and a feature vector with four sigma backscattering coefficients (σhh, σhv, σvh, and σvv) and six polarimetric decomposition parameters (entropy, anisotropy, alpha angle, volume scattering, odd bounce, and double bounce) were generated for each pattern. In the last stage, GRNN was used to estimate the regional soil moisture with the aid of feature vectors. The results indicated that radar is a strong remote sensing tool for soil moisture estimation, with mean absolute errors around 2.31 vol %, 2.11 vol %, and 2.10 vol % for Datasets 1–3, respectively; and 2.46 vol %, 2.70 vol %, 7.09 vol %, and 5.70 vol % on Datasets 1 & 2, 2 & 3, 1 & 3, and 1 & 2 & 3, respectively.

Estimation of supraglacial debris thickness using a novel target decomposition on L‐band polarimetric SAR images in the Tianshan Mountains

AbstractDebris is widely distributed in the ablation zones of mountain glaciers in the Tianshan Mountains. Supraglacial debris can accelerate or hamper glacier ablation, depending on its thickness. Thus, it plays an important role in the mass balance of debris‐covered glaciers. This paper proposes a novel method to estimate supraglacial debris thickness by using L‐band polarimetric synthetic aperture radar. A new model‐based target decomposition is used to extract the surface scattering, double bounce, and volume scattering components. The surface scatter model uses the extended Bragg scatter, which considers the depolarization effect for rough surfaces. The volume scatter model uses elliptical scatterers, which approximate the shape of the solids in the debris. The volume scattering power is related to the dielectric properties of the debris, the radar wavelength, the incidence angle, and the elliptical scatter shape. Once the target decomposition is performed, the debris thickness can be inverted from the volume scattering power and other known parameters. Through comparison with a large number of field measurements, the inversion is shown to be reasonable, and the accuracy is validated to be ±0.12 m. Based on the inversion map in the study area, the debris thicknesses of the Koxkar glacier and its neighboring glaciers are presented and analyzed.

A Low-Cost Laboratory-Based Polarimetric Synthetic Aperture Radar System for Scattering Analysis [Education Corner

The scattering mechanisms captured using polarimetric synthetic aperture radar (PolSAR) imaging enable applications like target detection and image classification. This article presents PolSAR images from a unique low-cost, laboratory-based imaging system that captures the basic scattering mechanisms using radar calibration targets, such as a flat plate and dihedral and trihedral corner reflectors. The characterization of the basic scattering mechanisms with good ground truth information is important for classification with PolSAR imagery and for modeling polarimetric signatures. The PolSAR instrument is calibrated using a corner reflector, and the calibration is then validated using an independent data set. The calibration is done in terms of radar cross section (RCS) in decibels referenced to a square meter (dBsm). Results show the system is capable of capturing the basic scattering mechanisms of the single and double bounce. Validation results of the calibration process are off by about 3 dBsm and 4.5 dBsm from the theoretical values of the RCS for the vertical transmit-vertical receive (VV) and horizontal transmit-horizontal receive (HH) channel calibration, respectively. This is acceptable for a low-cost system capable of differentiating scattering mechanisms. This PolSAR system can be used for experimentation within the laboratory for phenomenology studies.

A Fully Polarimetric SAR Imagery Classification Scheme for Mud and Sand Flats in Intertidal Zones

Sediments on exposed intertidal flats are very dynamic and perform vital ecosystem functions. This paper proposes a new classification scheme for mud and sand flats on intertidal flats using fully polarimetric synthetic aperture radar (SAR) data. Freeman–Durden (FD) and Cloude–Pottier (CP) polarimetric decomposition components as well as double bounce eigenvalue relative difference (DERD) are introduced into the feature sets instead of the original intensity polarimetric channels. Classification is carried out using the random forest (RF) theory, and the results are evaluated using confusion matrices, kappa coefficients, and RF variable importance indices. Three study sites with different environmental conditions are chosen to demonstrate the effectiveness of the proposed classification chain. To further assess the performance of the proposed feature set, we set different feature combinations and process with the same processing chain. Results show that the DERD parameter can detail the sediment mappings on exposed intertidal flats and is a useful SAR feature to distinguish mud and sand flats efficiently. The combined FD and CP components have the ability to describe the polarimetric characteristics of sediments more correctly than the commonly used original intensity channels. Meanwhile, the RF theory shows great potential in distinguishing sediments in intertidal zones accurately and time efficiently.

Two Component Decomposition of Dual Polarimetric HH/VV SAR Data: Case Study for the Tundra Environment of the Mackenzie Delta Region, Canada

This study investigates a two component decomposition technique for HH/VV-polarized PolSAR (Polarimetric Synthetic Aperture Radar) data. The approach is a straight forward adaption of the Yamaguchi decomposition and decomposes the data into two scattering contributions: surface and double bounce under the assumption of a negligible vegetation scattering component in Tundra environments. The dependencies between the features of this two and the classical three component Yamaguchi decomposition were investigated for Radarsat-2 (quad) and TerraSAR-X (HH/VV) data for the Mackenzie Delta Region, Canada. In situ data on land cover were used to derive the scattering characteristics and to analyze the correlation among the PolSAR features. The double bounce and surface scattering features of the two and three component scattering model (derived from pseudo-HH/VV- and quad-polarized data) showed similar scattering characteristics and positively correlated-R2 values of 0.60 (double bounce) and 0.88 (surface scattering) were observed. The presence of volume scattering led to differences between the features and these were minimized for land cover classes of low vegetation height that showed little volume scattering contribution. In terms of separability, the quad-polarized Radarsat-2 data offered the best separation of the examined tundra land cover types and will be best suited for the classification. This is anticipated as it represents the largest feature space of all tested ones. However; the classes “wetland” and “bare ground” showed clear positions in the feature spaces of the C- and X-Band HH/VV-polarized data and an accurate classification of these land cover types is promising. Among the possible dual-polarization modes of Radarsat-2 the HH/VV was found to be the favorable mode for the characterization of the aforementioned tundra land cover classes due to the coherent acquisition and the preserved co-pol. phase. Contrary, HH/HV-polarized and VV/VH-polarized data were found to be best suited for the characterization of mixed and shrub dominated tundra.

An Approach to Extended Fresnel Scattering for Modeling of Depolarizing Soil-Trunk Double-Bounce Scattering

Focusing on scattering from natural media, dihedral (double bounce) scattering is often characterized as a soil-trunk double Fresnel reflection, like for instance, in most model-based decompositions. As soils are predominantly rough in agriculture, the classical Rank 1 dihedral scattering component has to be extended to account for soil roughness-induced depolarization. Therefore, an azimuthal Line of Sight (LoS) rotation is applied solely on the soil plane of the double-bounce reflection to generate a depolarized dihedral scattering signal in agriculture. The results of the sensitivity analysis are shown for a distributed target in coherency matrix representation. It reveals that the combination of coherency matrix elements T22XD + T33XD is quasi-independent of the roughness-induced depolarization, while (T22XD − T33XD)/(T22XD + T33XD) is quasi-independent of the dielectric properties of the reflecting media. Therefore, a depolarization-independent retrieval of soil moisture or a direct roughness retrieval from the extended dihedral scattering component might be possible in stalk-dominated agriculture under certain conditions (e.g., the influence of a differential phase stays at a low level: ϕ < 15°). The first analyses with L-band airborne-SAR data of DLR’s E-SAR and F-SAR systems in agricultural regions during the AgriSAR, OPAQUE, SARTEO and TERENO project campaigns state the existence and potential of the extended Fresnel scattering mechanism to represent dihedral scattering between a rough (tilled) soil and the stalks of the agricultural plants.