Aspect Entropy Extraction Using Circular SAR Data and Scattering Anisotropy Analysis

In conventional synthetic aperture radar (SAR) working modes, targets are assumed isotropic because the viewing angle is small. However, most man-made targets are anisotropic. Therefore, anisotropy should be considered when the viewing angle is large. From another perspective, anisotropy is also a useful feature. Circular SAR (CSAR) can detect the scattering variation under different azimuthal look angles by a 360-degree observation. Different targets usually have varying degrees of anisotropy, which aids in target discrimination. However, there is no effective method to quantify the degree of anisotropy. In this paper, aspect entropy is presented as a descriptor of the scattering anisotropy. The range of aspect entropy is from 0 to 1, which corresponds to anisotropic to isotropic. First, the method proposed extracts aspect entropy at the pixel level. Since the aspect entropy of pixels can discriminate isotropic and anisotropic scattering, the method prescreens the target from the isotropic clutters. Next, the method extracts aspect entropy at the target level. The aspect entropy of targets can discriminate between different types of targets. Then, the effect of noise on aspect entropy extraction is analyzed and a denoising method is proposed. The Gotcha public release dataset, an X-band circular SAR data, is used to validate the method and the discrimination capability of aspect entropy.

Download Full-text

An Anisotropic Scattering Analysis Method Based on the Statistical Properties of Multi-Angular SAR Images

Remote Sensing ◽

10.3390/rs12132152 ◽

2020 ◽

Vol 12 (13) ◽

pp. 2152

Author(s):

Fei Teng ◽

Yun Lin ◽

Yanping Wang ◽

Wenjie Shen ◽

Shanshan Feng ◽

...

Keyword(s):

Rayleigh Distribution ◽

Anisotropic Scattering ◽

Statistical Properties ◽

Synthetic Aperture ◽

Ratio Test ◽

Analysis Method ◽

Sar Images ◽

X Band ◽

Sar Data ◽

Single Polarization

The scatterings of many targets are aspect dependent, which is called anisotropy. Multi-angular synthetic aperture radar (SAR) is a suitable means of detecting this kind of anisotropic scattering behavior by viewing targets from different aspect angles. First, the statistical properties of anisotropic and isotropic scatterings are studied in this paper. X-band chamber circular SAR data are used. The result shows that isotropic scatterings have stable distributions in different aspect viewing angles while the distributions of anisotropic scatterings are various. Then the statistical properties of single polarization high-resolution multi-angular SAR images are modeled by different distributions. G 0 distribution performs best in all types of areas. An anisotropic scattering analysis method based on the multi-angular statistical properties is proposed. A likelihood ratio test based on G 0 distribution is used to measure the anisotropy. Anisotropic scatterings can be discriminated from isotropic scatterings by thresholding. Besides, the scattering direction can also be estimated by our method. AHH polarization C-band circular SAR data are used to validate our method. The result of using G 0 distribution is compared with the result of using Rayleigh distribution. The result of using G 0 distribution is the better one.

Download Full-text

Brief Communication: Rapid mapping of landslide events: the 3 December 2013 Montescaglioso landslide, Italy

Natural Hazards and Earth System Science ◽

10.5194/nhess-14-1835-2014 ◽

2014 ◽

Vol 14 (7) ◽

pp. 1835-1841 ◽

Cited By ~ 43

Author(s):

A. Manconi ◽

F. Casu ◽

F. Ardizzone ◽

M. Bonano ◽

M. Cardinali ◽

...

Keyword(s):

High Resolution ◽

Synthetic Aperture Radar ◽

Southern Italy ◽

Surface Deformation ◽

Synthetic Aperture ◽

Sar Images ◽

Main Road ◽

Rapid Mapping ◽

X Band ◽

Sar Data

Abstract. We present an approach to measure 3-D surface deformations caused by large, rapid-moving landslides using the amplitude information of high-resolution, X-band synthetic aperture radar (SAR) images. We exploit SAR data captured by the COSMO-SkyMed satellites to measure the deformation produced by the 3 December 2013 Montescaglioso landslide, southern Italy. The deformation produced by the deep-seated landslide exceeded 10 m and caused the disruption of a main road, a few homes and commercial buildings. The results open up the possibility of obtaining 3-D surface deformation maps shortly after the occurrence of large, rapid-moving landslides using high-resolution SAR data.

Download Full-text

Digital Beamforming Synthetic Aperture Radar (DBSAR): Experiments and Performance Analysis in Support of 16-Channel Airborne X-Band SAR Data

IEEE Transactions on Geoscience and Remote Sensing ◽

10.1109/tgrs.2020.3027691 ◽

2020 ◽

pp. 1-15

Author(s):

Yashi Zhou ◽

Wei Wang ◽

Zhen Chen ◽

Pei Wang ◽

Huachun Zhang ◽

...

Keyword(s):

Performance Analysis ◽

Synthetic Aperture Radar ◽

Synthetic Aperture ◽

Digital Beamforming ◽

X Band ◽

Sar Data ◽

And Performance ◽

Aperture Radar

Download Full-text

Full and Simulated Compact Polarimetry SAR Responses to Canadian Wetlands: Separability Analysis and Classification

Remote Sensing ◽

10.3390/rs11050516 ◽

2019 ◽

Vol 11 (5) ◽

pp. 516 ◽

Cited By ~ 16

Author(s):

◽

Keyword(s):

Remote Sensing ◽

Spatial Distribution ◽

Newfoundland And Labrador ◽

Earth Observation ◽

Synthetic Aperture ◽

Conservation Strategies ◽

Wetland Classification ◽

Wetland Mapping ◽

Discrimination Capability ◽

Sar Data

Detailed information on spatial distribution of wetland classes is crucial for monitoring this important productive ecosystem using advanced remote sensing tools and data. Although the potential of full- and dual-polarimetric (FP and DP) Synthetic Aperture Radar (SAR) data for wetland classification has been well examined, the capability of compact polarimetric (CP) SAR data has not yet been thoroughly investigated. This is of great significance, since the upcoming RADARSAT Constellation Mission (RCM), which will soon be the main source of SAR observations in Canada, will have CP mode as one of its main SAR configurations. This also highlights the necessity to fully exploit such important Earth Observation (EO) data by examining the similarities and dissimilarities between FP and CP SAR data for wetland mapping. Accordingly, this study examines and compares the discrimination capability of extracted features from FP and simulated CP SAR data between pairs of wetland classes. In particular, 13 FP and 22 simulated CP SAR features are extracted from RADARSAT-2 data to determine their discrimination capabilities both qualitatively and quantitatively in three wetland sites, located in Newfoundland and Labrador, Canada. Seven of 13 FP and 15 of 22 CP SAR features are found to be the most discriminant, as they indicate an excellent separability for at least one pair of wetland classes. The overall accuracies of 87.89%, 80.67%, and 84.07% are achieved using the CP SAR data for the three wetland sites (Avalon, Deer Lake, and Gros Morne, respectively) in this study. Although these accuracies are lower than those of FP SAR data, they confirm the potential of CP SAR data for wetland mapping as accuracies exceed 80% in all three sites. The CP SAR data collected by RCM will significantly contribute to the efforts ongoing of conservation strategies for wetlands and monitoring changes, especially on large scales, as they have both wider swath coverage and improved temporal resolution compared to those of RADARSAT-2.

Download Full-text

COMPARISON OF C-BAND AND X-BAND POLARIMETRIC SAR DATA FOR RIVER ICE CLASSIFICATION ON THE PEACE RIVER

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xli-b7-543-2016 ◽

2016 ◽

Vol XLI-B7 ◽

pp. 543-548

Author(s):

H. Łoś ◽

K. Osińska-Skotak ◽

J. Pluto-Kossakowska ◽

M. Bernier ◽

Y. Gauthier ◽

...

Keyword(s):

Supervised Classification ◽

Open Water ◽

Covariance Matrices ◽

Synthetic Aperture ◽

River Ice ◽

Data Sets ◽

Satellite Systems ◽

Peace River ◽

X Band ◽

Sar Data

In this study, synthetic aperture radar (SAR) data from TerraSAR-X were compared with RADARSAT-2 data to evaluate their effectiveness for river ice monitoring on the Peace River. For several years RADARSAT-2 data have been successfully used for river ice observation. However, it is important to take into account data from other satellites as they may provide solutions when it is not possible to obtain images from the preferred system (e.g., in the case of acquisition priority conflicts). In this study we compared three TerraSAR-X (X-band) and three RADARSAT-2 (C-band) datasets acquired in December 2013 on a section of the Peace River, Canada. For selected classes (open water, skim ice, juxtaposed skim ice, agglomerated skim ice, frazil run and consolidated ice) we compared backscattering values in HH and VV polarisation and performed Wishart supervised classification. Covariance matrices that were previously filtered using a refined Lee filter were used as input data for classification. For all data sets the overall accuracy was higher than 80%. Similar errors associated with classification output were observed for data from both satellite systems.

Download Full-text

A multiscale approach for detection and mapping differential subsidence using multi-platform InSAR products

Proceedings of the International Association of Hydrological Sciences ◽

10.5194/piahs-382-173-2020 ◽

2020 ◽

Vol 382 ◽

pp. 173-177

Author(s):

Dario E. Solano-Rojas ◽

Shimon Wdowinski ◽

Enrique Cabral-Cano ◽

Batuhan Osmanoglu ◽

Emre Havazli ◽

...

Keyword(s):

Synthetic Aperture Radar ◽

Data Availability ◽

Synthetic Aperture ◽

Multiscale Approach ◽

Interferometric Synthetic Aperture Radar ◽

Case Examples ◽

X Band ◽

Data Coverage ◽

Sar Data ◽

Aperture Radar

Abstract. Detecting and mapping subsidence is currently supported by interferometric synthetic aperture radar (InSAR) products. However, several factors, such as band-dependent processing, noise presence, and strong subsidence limit the use of InSAR for assessing differential subsidence, which can lead to ground instability and damage to infrastructure. In this work, we propose an approach for measuring and mapping differential subsidence using InSAR products. We consider synthetic aperture radar (SAR) data availability, data coverage over time and space, and the region's subsidence rates to evaluate the need of post-processing, and only then we interpret the results. We illustrate our approach with two case-examples in Central Mexico, where we process SAR data from the Japanese ALOS (L-band), the German TerraSAR-X (X-band), the Italian COSMO-SkyMed (X-band) and the European Sentinel-1 (C-band) satellites. We find good agreement between our results on differential subsidence and field data of existing faulting and find potential to map yet-to-develop faults.

Download Full-text

COMPARISON OF C-BAND AND X-BAND POLARIMETRIC SAR DATA FOR RIVER ICE CLASSIFICATION ON THE PEACE RIVER

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsarchives-xli-b7-543-2016 ◽

2016 ◽

Vol XLI-B7 ◽

pp. 543-548

Author(s):

H. Łoś ◽

K. Osińska-Skotak ◽

J. Pluto-Kossakowska ◽

M. Bernier ◽

Y. Gauthier ◽

...

Keyword(s):

Supervised Classification ◽

Open Water ◽

Covariance Matrices ◽

Synthetic Aperture ◽

River Ice ◽

Data Sets ◽

Satellite Systems ◽

Peace River ◽

X Band ◽

Sar Data

Download Full-text

URBAN AREA EXTRACTION USING AIRBORNE X-BAND FULLY POLARIMETRIC PI-SAR2 IMAGERY

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsarchives-xl-3-w2-219-2015 ◽

2015 ◽

Vol XL-3/W2 ◽

pp. 219-226 ◽

Cited By ~ 1

Author(s):

J. Susaki ◽

M. Kishimoto

Keyword(s):

Synthetic Aperture Radar ◽

Urban Areas ◽

Orientation Angle ◽

Information And Communications Technology ◽

Synthetic Aperture ◽

Total Power ◽

Component Decomposition ◽

X Band ◽

Sar Data ◽

Aperture Radar

In this paper, we present a method to extract urban areas from X-band fully polarimetric synthetic aperture radar (SAR) data. It is known that very high resolution (VHR) SAR can extract buildings, but it requires more processes to map urban areas that should include other objects. The proposed method is mainly composed of two classifications. One classification uses total power of scattering and volume scattering derived by using four component decomposition method with correction of the polarization orientation angle (POA) effect. The other classification uses polarimetric coherency between SHH and SVV . The two results are intersected and final urban areas are extracted after post-classification processing. We applied the proposed method to airborne X-band fully polarimetric SAR data of Polarimetric and Interferometric Airborne Synthetic Aperture Radar System (Pi-SAR2), developed by the National Institute of Information and Communications Technology (NICT), Japan. The validation show that the results of the proposed method were acceptable, with an overall accuracy of approximately 80 to 90% at 100-m spatial scale.

Download Full-text

Forest Fuel Loads Estimation from Landsat ETM+ and ALOS PALSAR Data

Remote Sensing ◽

10.3390/rs13061189 ◽

2021 ◽

Vol 13 (6) ◽

pp. 1189

Author(s):

Yanxi Li ◽

Xingwen Quan ◽

Zhanmang Liao ◽

Binbin He

Keyword(s):

Synthetic Aperture Radar ◽

Synthetic Aperture ◽

Optical Data ◽

Fuel Load ◽

Load Estimation ◽

Fuel Loads ◽

Different Types ◽

L Band ◽

Sar Data ◽

Aperture Radar

Fuel load is the key factor driving fire ignition, spread and intensity. The current literature reports the light detection and ranging (LiDAR), optical and airborne synthetic aperture radar (SAR) data for fuel load estimation, but the optical and SAR data are generally individually explored. Optical and SAR data are expected to be sensitive to different types of fuel loads because of their different imaging mechanisms. Optical data mainly captures the characteristics of leaf and forest canopy, while the latter is more sensitive to forest vertical structures due to its strong penetrability. This study aims to explore the performance of Landsat Enhanced Thematic Mapper Plus (ETM+) and Advanced Land Observing Satellite (ALOS) Phased Arrayed L-band Synthetic Aperture Radar (PALSAR) data as well as their combination on estimating three different types of fuel load—stem fuel load (SFL), branch fuel load (BFL) and foliage fuel load (FFL). We first analyzed the correlation between the three types of fuel load and optical and SAR data. Then, the partial least squares regression (PLSR) was used to build the fuel load estimation models based on the fuel load measurements from Vindeln, Sweden, and variables derived from optical and SAR data. Based on the leave-one-out cross-validation (LOOCV) method, results show that L-band SAR data performed well on all three types of fuel load (R2 = 0.72, 0.70, 0.72). The optical data performed best for FFL estimation (R2 = 0.66), followed by BFL (R2 = 0.56) and SFL (R2 = 0.37). Further improvements were found for the SFL, BFL and FFL estimation when integrating optical and SAR data (R2 = 0.76, 0.81, 0.82), highlighting the importance of data selection and combination for fuel load estimation.

Download Full-text