Journal articles: 'RADARSAT-1 SAR'

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Wackerman, C. C., K. S. Friedman, W. G. Pichel, P. Clemente-Colón, and X. Li. "Automatic Detection of Ships in RADARSAT-1 SAR Imagery." Canadian Journal of Remote Sensing 27, no. 4 (August 2001): 371–78. http://dx.doi.org/10.1080/07038992.2001.10854879.

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Wackerman, C. C., K. S. Friedman, W. G. Pichel, P. Clemente-Colón, and X. Li. "Automatic Detection of Ships in RADARSAT-1 SAR Imagery." Canadian Journal of Remote Sensing 27, no. 5 (October 2001): 568–77. http://dx.doi.org/10.1080/07038992.2001.10854896.

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Li, Xiaofeng, Jun A. Zhang, Xiaofeng Yang, William G. Pichel, Mark DeMaria, David Long, and Ziwei Li. "Tropical Cyclone Morphology from Spaceborne Synthetic Aperture Radar." Bulletin of the American Meteorological Society 94, no. 2 (February 1, 2013): 215–30. http://dx.doi.org/10.1175/bams-d-11-00211.1.

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In 2008, the Canadian Space Agency sponsored the Radarsat Hurricane Applications Project (RHAP), for researching new developments in the application of Radarsat-1 synthetic aperture radar (SAR) data and innovative mapping approaches to better understand the dynamics of tropical cyclone genesis, morphology, and movement. Although tropical cyclones can be detected by many remote sensors, SAR can yield high-resolution (subkilometer) and low-level storm information that cannot be seen below the clouds by other sensors. In addition to the wind field and tropical cyclone eye information, structures associated with atmospheric processes can also be detected by SAR. We have acquired 161 Radarsat-1 SAR images through RHAP between 2001 and 2007. Among these, 73 images show clear tropical cyclone eye structure. In addition, we also acquired 10 images from the European Space Agency's Envisat SAR between 2004 and 2010. Both Atlantic hurricanes and Pacific typhoons are included. In this study, we analyze these 83 (73 Radarsat-1 and 10 Envisat) images with tropical cyclone eye information along with ancillary tropical cyclone intensity information from the archive to generate tropical cyclone morphology statistics. Histograms of wave-number asymmetry and intensity are presented. The statistics show that when the storm has higher intensity, the tropical cyclone eye tends to become more symmetric, and the area of the tropical cyclone eye, defined by the minimum wind area, tends to be smaller. Examples of finescale structures within the tropical cyclone (i.e., eye/eyewall mesovortices, arc clouds, double eyewalls, and abnormally high wind or rain within eyes) are presented and discussed.

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Joughin, Ian. "Ice-sheet velocity mapping: a combined interferometric and speckle-tracking approach." Annals of Glaciology 34 (2002): 195–201. http://dx.doi.org/10.3189/172756402781817978.

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AbstractThe first and second RADARSAT Antarctic Mapping Missions (AMM-1 and -2) have now acquired interferometric synthetic aperture radar (SAR) overmuch of the ice sheet. The RADARSAT 24 day repeat cycle is nearly ideal for measuring slow ice motion (e.g. <100ma–1), but application of SAR interferometry is limited in faster-moving areas. With a 1day repeat period, ERS-1/-2 tandem SAR data are much better matched to fast motion, but are not always available. Fortunately, several authors have demonstrated the ability to measure velocity in fast-moving areas by tracking SAR speckle from image to image, which works well even in the absence of visible features. While these estimates have intrinsically lower resolution and poorer accuracy than direct phase measurements, they serve well in areas where there are no data suitable for conventional interferometry. This paper describes algorithms I have developed for merging interferometric and speckle-tracking data from multiple swaths to form a single seamless mosaic of velocity. At each point in the mosaic, all the available data are combined to produce estimates of the velocity and the associated error. This technique is demonstrated using RADARSAT data collected over Lambert Glacier, Antarctica, during AMM-1 and -2.

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Toutin, T. "Path Processing and Block Adjustment With RADARSAT-1 SAR Images." IEEE Transactions on Geoscience and Remote Sensing 41, no. 10 (October 2003): 2320–28. http://dx.doi.org/10.1109/tgrs.2003.814661.

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Jezek, Kenneth C. "RADARSAT-1 Antarctic Mapping Project: change-detection and surface velocity campaign." Annals of Glaciology 34 (2002): 263–68. http://dx.doi.org/10.3189/172756402781818030.

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AbstractThe RADARSAT-1 Antarctic Mapping Project (RAMP) is a collaboration between NASA and the Canadian Space Agency to map Antarctica using synthetic aperture radar (SAR). The first Antarctic Mapping Mission (AMM-1) was successfully completed in October 1997. Data from the acquisition phase of the 1997 campaign have been used to achieve the primary goal of producing the first high-resolution SAR image map of Antarctica. The Modified Antarctic Mapping Mission (MAMM) occurred during the fall of 2000. The acquisition strategy concentrated on collecting highest- resolution RADARSAT-1 data of Antarctica’s fast glaciers for change detection and feature-retracking estimates of surface velocity. Additionally, extensive data were acquired for interferometric analysis over the entire viewable region, which extends north of 80.1˚ S latitude. This paper summarizes the goals and strategy behind MAMM. It goes on to discuss ice-sheet margin changes observed on several ice shelves around the continent. Margin changes are documented by comparing AMM-1 and MAMM data with earlier datasets including European Remote-sensing Satellite-1 SAR imagery, Landsat imagery, the Antarctic Digital Database (version 1) coastline and Declassified Intelligence Satellite Photography. Analysis reveals a complex pattern of ice-margin advance and retreat without indicating any systematic behavior in ice-sheet extent about the ice-sheet perimeter.

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Salman Alsalman, Abdullah. "Interpretation of Radarsat-1 SAR Imagery of Riyadh for Mapping Applications." Journal of King Saud University - Engineering Sciences 22, no. 2 (July 2010): 89–98. http://dx.doi.org/10.1016/s1018-3639(18)30496-3.

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Karvonen, J., M. Simila, and M. Makynen. "Open Water Detection From Baltic Sea Ice Radarsat-1 SAR Imagery." IEEE Geoscience and Remote Sensing Letters 2, no. 3 (July 2005): 275–79. http://dx.doi.org/10.1109/lgrs.2005.847930.

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马, 智峰. "Combined Multi-Temporal Radarsat-1 and Sentinel-1 SAR Data Inversion Forest Tree Height." Geomatics Science and Technology 09, no. 02 (2021): 59–66. http://dx.doi.org/10.12677/gst.2021.92007.

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Hong Quang, Nguyen, Vu Anh Tuan, Le Thi Thu Hang, Nguyen Manh Hung, Doan Thi The, Dinh Thi Dieu, Ngo Duc Anh, and Christopher R. Hackney. "Hydrological/Hydraulic Modeling-Based Thresholding of Multi SAR Remote Sensing Data for Flood Monitoring in Regions of the Vietnamese Lower Mekong River Basin." Water 12, no. 1 (December 23, 2019): 71. http://dx.doi.org/10.3390/w12010071.

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Synthetic Aperture Radar (SAR) remote sensing data can be used as an effective alternative to detect surface water and provide useful information regarding operational flood monitoring, in particular for the improvement of rapid flood assessments. However, this application frequently requires standard and simple, yet robust, algorithms. Although thresholding approaches meet these requirements, limitations such as data inequality over large spatial regions and challenges in estimating optimal threshold values remain. Here, we propose a new method for SAR water extraction named Hammock Swing Thresholding (HST). We applied this HST approach to four SAR remote sensing datasets, namely, Sentinel-1, ALOS-2, TerraSAR-X, and RadarSAT-2 for flood inundation mapping for a case study focusing on the Tam Nong district in the Vietnam Mekong delta. A 2D calibrated Hydrologic Engineering Centers River Analysis System (HEC-RAS) model was coupled with the HST outputs in order to estimate the optimal thresholds (OTs) where the SAR-based water masks fitted best with HEC-RAS’s inundation patterns. Our results showed that water levels extracted from Sentinel-1 data best agreed with the HEC-RAS water extent (88.3%), following by ALOS-2 (85.9%), TerraSAR-X (77.2%). and RadarSAT-2 (72%) at OTs of −15, 68, 21, and 35 decibel (dB), respectively. Generated flood maps indicated changes in the flood extent of the flooding seasons from 2010 and 2014–2016 with variations in spatial extent appearing greater in the TerraSAR-X and RadarSAT-2 higher resolution maps. We recommend the use of OTs in applications of flood monitoring using SAR remote sensing data, such as for an open data cube (ODC).

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Jayaprasad, P., D. R. Rajak, R. K. Singh, S. R. Oza, R. Sharma, and R. Kumar. "Ice calving and deformation from Antarctic Ice margins using RISAT-1 circular polarization SAR data." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-8 (November 28, 2014): 525–29. http://dx.doi.org/10.5194/isprsarchives-xl-8-525-2014.

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In the present study, quantification of spatial and temporal changes has been carried out between Indian Antarctic Research station Bharati and Amery ice shelf by monitoring the ice margins using RISAT-1 Synthetic Aperture Radar (SAR) data. Spatio-temporal change detection was carried out by comparing the feature's geographic locations from geometrically rectified SAR data from RISAT-1 (Dec. 2013), Radarsat-2 (Feb. 2013), and Antarctic Mapping Mission products of Radarsat-1 (1997 & 2000). We report large scale disintegrations at two prominent glacier tongues namely Polar Record Glacier (PRG) and Polar Times Glacier(PTG). The results are verified against in-situ ground observations made during Summer period of 33rd ISEA (Dec. 2013–Feb. 2014) and MODIS images from NSIDC archive. Polar Record Glacier Tongue (PRGT) was drastically deformed by 135.8 km2 and Polar Times Glacier Tongue (PTGT) was partly calved by ~195.6 km2 and moved away by ~23 km especially between February and December 2013.

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Souza-Filho, Pedro W. M., and Waldir R. Paradella. "Use of synthetic aperture radar for recognition of Coastal Geomorphological Features, land-use assessment and shoreline changes in Bragança coast, Pará, Northern Brazil." Anais da Academia Brasileira de Ciências 75, no. 3 (September 2003): 341–56. http://dx.doi.org/10.1590/s0001-37652003000300007.

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Synthetic Aperture Radar (SAR) images are being used more extensively than ever before for geoscience applications in the moist tropics. In this investigation, a RADARSAT1-1 C-HH SAR image acquired in 1998 was used for coastal mapping and land-cover assessment in the Bragança area, in the northern Brazil. The airborne GEMS 1000 X-HH radar image acquired in 1972 during the RADAM Project was also used for evaluating coastal changes occurring over the last three decades. The research has confirmed the usefulness of RADARSAT-1 image for geomorphological mapping and land-cover assessment, particularly in macrotidal mangrove coasts. It was possible to map mangroves, salt marshes, chenier sand ridges, dunes, barrier-beach ridges, shallow water morphologies and different forms of land-use. Furthermore, a new method to estimate shoreline changes based on the superimposition of vectors extracted from both sources of SAR data has indicated that the shoreline has been subjected to severe coastal erosion responsible for retreat of 32 km² and accretion of 20 km², resulting in a mangrove land loss of almost 12 km². In an application perspective, orbital and airborne SAR data proved to be a fundamental source of information for both geomorphological mapping and monitoring coastal changes in moist tropical environments.

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Macedo, Carina Regina de, and João Antônio Lorenzzetti. "Numerical simulations of SAR microwave imaging of the Brazil current surface front." Brazilian Journal of Oceanography 63, no. 4 (December 2015): 481–96. http://dx.doi.org/10.1590/s1679-87592015082306304.

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Abstract This paper analyzes the hydrodynamic and atmospheric instability modulation mechanisms which influence the Brazilian Current's (BC) thermal front signature in Synthetic Aperture Radar (SAR) images. Simulations were made using the M4S SAR imaging model. Two SAR images of the Brazilian Southeastern Coast depicting the BC's thermal front were selected including a VV (ASAR/Envisat) and a HH polarization (RADARSAT-1) image. Conditions of current shear and divergence were reproduced for the fronts imaged, using in situ (Acoustic Doppler Current Profilers) current velocities. Wind velocity fields were simulated based on QuikSCAT data. Results showed that SAR imaging of the BC front may be influenced both by atmospheric instabilities and hydrodynamic modulations. The first mechanism prevailed on the RADARSAT image and the latter on the ASAR/Envisat image. When atmospheric instabilities prevailed, the contribution of shear and divergence was almost negligible. When hydrodynamic modulations prevailed, a better agreement between the simulated responses and SAR image responses was obtained by inforcing a reduction of 88% in the relaxation rate, and higher divergence values, of the order of 10-4 s-1. Results indicate that, for some specific cases, local increases in shear and divergence may allow the detection of the BC thermal front.

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Sahebi, Mahmod Reza, Ferdinand Bonn, and Goze B. Bénié. "Neural networks for the inversion of soil surface parameters from synthetic aperture radar satellite data." Canadian Journal of Civil Engineering 31, no. 1 (January 1, 2004): 95–108. http://dx.doi.org/10.1139/l03-079.

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This paper presents an application of neural networks to the extraction of bare soil surface parameters such as roughness and soil moisture content using synthetic aperture radar (SAR) satellite data. It uses a fast learning algorithm for training a multilayer feedforward neural network using the Kalman filter technique. Two different databases (theoretical and empirical) were used for the learning stage. Each database was configured as single and multiangular sets of input data (data acquired at two different incidence angles) that are compatible with data from one and two satellite images, respectively. All the configurations are trained and then evaluated using RADARSAT-1 and simulated data. The empirical (measured) database with the multiangular set of input data configuration had the best accuracy with a mean error of 1.54 cm for root mean square (rms) height of the surface roughness and 2.45 for soil dielectric constant in the study area. Based on these results the proposed approach was applied on RADARSAT-1 images from the Chateauguay watershed area (Quebec, Canada) and the final results are presented in the form of roughness and humidity maps.Key words: neural networks, Kalman filter, RADARSAT, SAR, soil roughness, soil moisture.

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Kumar, V., and Y. S Rao. "Comparative analysis of RISAT-1 and simulated RADARSAT-2 hybrid polarimetric SAR data for different land features." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-8 (November 28, 2014): 799–802. http://dx.doi.org/10.5194/isprsarchives-xl-8-799-2014.

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The purpose of this study is to compare the performance of first hybrid polarimetric spaceborne satellite RISAT-1 data and simulated hybrid polarimetric data from quad-pol RADARSAT-2 data for different land use land cover (LULC) classes. The present study compares Stokes (g0, g1, g2 and g3) and its decomposed parameters (m, chi, delta and CPR) for satellite data acquired from RISAT- 1 and RADARSAT-2 over Vijayawada, Andhra Pradesh, India. Further, backscattering coefficients are also compared for different LULC types. The results indicate that both the satellites are following approximately the same trend for different classes except for settlements in RISAT-1.

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Denize, Julien, Laurence Hubert-Moy, and Eric Pottier. "Polarimetric SAR Time-Series for Identification of Winter Land Use." Sensors 19, no. 24 (December 17, 2019): 5574. http://dx.doi.org/10.3390/s19245574.

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In the past decade, high spatial resolution Synthetic Aperture Radar (SAR) sensors have provided information that contributed significantly to cropland monitoring. However, the specific configurations of SAR sensors (e.g., band frequency, polarization mode) used to identify land-use types remains underexplored. This study investigates the contribution of C/L-Band frequency, dual/quad polarization and the density of image time-series to winter land-use identification in an agricultural area of approximately 130 km² located in northwestern France. First, SAR parameters were derived from RADARSAT-2, Sentinel-1 and Advanced Land Observing Satellite 2 (ALOS-2) time-series, and one quad-pol and six dual-pol datasets with different spatial resolutions and densities were calculated. Then, land use was classified using the Random Forest algorithm with each of these seven SAR datasets to determine the most suitable SAR configuration for identifying winter land-use. Results highlighted that (i) the C-Band (F1-score 0.70) outperformed the L-Band (F1-score 0.57), (ii) quad polarization (F1-score 0.69) outperformed dual polarization (F1-score 0.59) and (iii) a dense Sentinel-1 time-series (F1-score 0.70) outperformed RADARSAT-2 and ALOS-2 time-series (F1-score 0.69 and 0.29, respectively). In addition, Shannon Entropy and SPAN were the SAR parameters most important for discriminating winter land-use. Thus, the results of this study emphasize the interest of using Sentinel-1 time-series data for identifying winter land-use.

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Leblon, Brigitte, Amine Merzouki, David A. MacLean, and Armand LaRocque. "Photo-interpretation and remote sensing at the Faculty of Forestry and Environmental Management, UNB." Forestry Chronicle 84, no. 4 (August 1, 2008): 534–38. http://dx.doi.org/10.5558/tfc84534-4.

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Classically, remote sensing has been used as input data for land cover mapping. Through remote sensing studies at the University of New Brunswick Faculty of Forestry and Environmental Management, broader applications have been developed. These include: 1) fuel moisture mapping using optical and thermal infrared NOAA-AVHRR and MODIS images, as well as synthetic aperture radar (SAR) images (single-polarized images from ERS-1 and RADARSAT-1 and polarimetric images from RADARSAT-2); 2) determination of plant nitrogen and chlorophyll content using narrow-band hyperspectral data; and 3) imaging system applications in the wood industry. The third type of applications include: 1) mapping of internal wood features using X-ray computer tomography images, 2) monitoring of wood deformations using digital images acquired in the visible band, and 3) use of near-infrared spectroscopy to identify and sort wood by species, colour, physical properties, and surfacing/aging history. This last technology will also be used to determine lignin, cellulose and hemi-cellulose contents of wood products for value-added applications. Key words: optical, thermal infrared, radar, fuel moisture, crop nitrogen, X-ray CT images, image correlation, wood scanning, NOAA-AVHRR, MODIS, ERS-1, RADARSAT-1, radar polarimetry, RADARSAT-2

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Van Wychen, Wesley, Paris W. Vachon, John Wolfe, and Katerina Biron. "Synergistic RADARSAT-2 and Sentinel-1 SAR Images for Ocean Feature Analysis." Canadian Journal of Remote Sensing 45, no. 5 (September 3, 2019): 591–602. http://dx.doi.org/10.1080/07038992.2019.1662284.

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Merzouki, A., A. Bannari, P. M. Teillet, and D. J. King. "Statistical properties of soil moisture images derived from Radarsat-1 SAR data." International Journal of Remote Sensing 32, no. 19 (August 19, 2011): 5443–60. http://dx.doi.org/10.1080/01431161.2010.502154.

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Al Fugura, A’kif, Lawal Billa, and Biswajeet Pradhan. "Semi-automated procedures for shoreline extraction using single RADARSAT-1 SAR image." Estuarine, Coastal and Shelf Science 95, no. 4 (December 2011): 395–400. http://dx.doi.org/10.1016/j.ecss.2011.10.009.

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Pradhan, Biswajeet, Hossein Rizeei, and Abdinur Abdulle. "Quantitative Assessment for Detection and Monitoring of Coastline Dynamics with Temporal RADARSAT Images." Remote Sensing 10, no. 11 (October 29, 2018): 1705. http://dx.doi.org/10.3390/rs10111705.

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This study aims to detect coastline changes using temporal synthetic aperture radar (SAR) images for the state of Kelantan, Malaysia. Two active images, namely, RADARSAT-1 captured in 2003 and RADARSAT-2 captured in 2014, were used to monitor such changes. We applied noise removal and edge detection filtering on RADARSAT images for preprocessing to remove salt and pepper distortion. Different segmentation analyses were also applied to the filtered images. Firstly, multiresolution segmentation, maximum spectral difference and chessboard segmentation were performed to separate land pixels from ocean ones. Next, the Taguchi method was used to optimise segmentation parameters. Subsequently, a support vector machine algorithm was applied on the optimised segments to classify shorelines with an accuracy of 98% for both temporal images. Results were validated using a thematic map from the Department of Survey and Mapping of Malaysia. The change detection showed an average difference in the shoreline of 12.5 m between 2003 and 2014. The methods developed in this study demonstrate the ability of active SAR sensors to map and detect shoreline changes, especially during low or high tides in tropical regions where passive sensor imagery is often masked by clouds.

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Jones, Benjamin M., Russell Rykhus, Zhong Lu, Christopher D. Arp, and David J. Selkowitz. "Radar imaging of winter seismic survey activity in the National Petroleum Reserve-Alaska." Polar Record 44, no. 3 (July 2008): 227–31. http://dx.doi.org/10.1017/s0032247407007206.

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ABSTRACTDuring the spring of 2006, Radarsat-1 synthetic aperture radar (SAR) imagery was acquired on a continual basis for the Teshekpuk Lake Special Area (TLSA), in the northeast portion of the National Petroleum Reserve, Alaska (NPR-A) in order to monitor lake ice melting processes. During data processing, it was discovered that the Radarsat-1 imagery detected features associated with winter seismic survey activity. Focused analysis of the image time series revealed various aspects of the exploration process such as the grid profile associated with the seismic line surveys as well as trails and campsites associated with the mobile survey crews. Due to the high temporal resolution of the dataset it was possible to track the progress of activities over a one month period. Spaceborne SAR imagery can provide information on the location of winter seismic activity and could be used as a monitoring tool for land and resource managers as increased petroleum-based activity occurs in the TLSA and NPR-A.

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Chauhan, S., R. Darvishzadeh, M. Boschetti, and A. Nelson. "UNDERSTANDING OF CROP LODGING INDUCED CHANGES IN SCATTERING MECHANISMS USING RADARSAT-2 AND SENTINEL-1 DERIVED METRICS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2020 (August 21, 2020): 267–74. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2020-267-2020.

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Abstract. Crop lodging – the bending of crop stems from the vertical – is a major yield-reducing factor in cereal crops and causes deterioration in grain quality. Accurate assessment of crop lodging is important for improving estimates of crop yield losses, informing insurance loss adjusters and influencing management decisions for subsequent seasons. The role of remote sensing data, particularly synthetic aperture radar (SAR) data has been emphasized in the recent literature for crop lodging assessment. However, the effect of lodging on SAR scattering mechanisms is still unknown. Therefore, this research aims to understand the possible change in scattering mechanisms due to lodging by investigating SAR image pairs before and after lodging. We conducted the study in 26 wheat fields in the Bonifiche Ferraresi farm, located in Jolanda di Savoia, Ferrara, Italy. We measured temporal crop biophysical (e.g. crop angle) parameters and acquired multi-incidence angle RADARSAT-2 (R-2 FQ8-27° and R-2 FQ21-41°) and Sentinel-1 (S-1 40°) images corresponding to the time of field observations. We extracted metrics of SAR scattering mechanisms from RADARSAT-2 and Sentinel-1 image pairs in different zones using the unsupervised H/α decomposition algorithm and Wishart classifier. Contrasting results were obtained at different incidence angles. Bragg surface scattering increased in the case of S-1 (6.8%), R-2 FQ8 (1.8%) while at R-2 FQ21, it decreased (8%) after lodging. The change in double bounce scattering was more prominent at low incidence angle. These observations can guide future use of SAR-based information for operational crop lodging assessment in particular, and sustainable agriculture in general.

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Rudorff, Frederico de Moraes, and Douglas Francisco Marcolino Gherardi. "Coral reef detection using SAR/RADARSAT-1 images at Costa dos Corais, PE/AL, Brazil." Brazilian Journal of Oceanography 56, no. 2 (June 2008): 85–96. http://dx.doi.org/10.1590/s1679-87592008000200002.

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The present work aimed to examine the potentials of SAR RADARSAT-1 images to detect emergent coral reefs at the Environmental Protection Area of "Costa dos Corais". Multi-view filters were applied and tested for speckle noise reduction. A digital unsupervised classification based on image segmentation was performed and the classification accuracy was evaluated by an error matrix built between the SAR image classification and a reference map obtained from a TM Landsat-5 classification. The adaptative filters showed the best results for speckle suppression and border preservation, especially the Kuan, Gamma MAP, Lee, Frost and Enhanced Frost filters. Small similarity and area thresholds (5 and 10, respectively) were used for the image segmentation due to the reduced dimensions and the narrow and elongated forms of the reefs. The classification threshold of 99% had a better user's accuracy, but a lower producer's accuracy because it is a more restrictive threshold; therefore, it may be possible that it had a greater omission on reef classification. The results indicate that SAR images have a good potential for the detection of emergent coral reefs.

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Millard, Koreen, Patrick Kirby, Sacha Nandlall, Amir Behnamian, Sarah Banks, and Fabrizio Pacini. "Using Growing-Season Time Series Coherence for Improved Peatland Mapping: Comparing the Contributions of Sentinel-1 and RADARSAT-2 Coherence in Full and Partial Time Series." Remote Sensing 12, no. 15 (July 31, 2020): 2465. http://dx.doi.org/10.3390/rs12152465.

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Differences in topographic structure, vegetation structure, and surface wetness exist between peatland classes, making active remote sensing techniques such as SAR and LiDAR promising for peatland mapping. As the timing of green-up, senescence, and hydrologic conditions vary differently in peatland classes, and in comparison with upland classes, full growing-season time series SAR imagery was expected to produce higher accuracy classification results than using only a few select SAR images. Both interferometric coherence, amplitude and difference in amplitude time series datasets were assessed, as it was hypothesized that these may be able to capture subtle changes in phenology and hydrology, which in turn differentiate classes throughout a growing season. Groups of variables were compared for their effectiveness in Random Forest classification for both Sentinel-1 and Radarsat-2. The Shapley value was used to determine the contribution of each group of variables in thirty scenarios, and Mean Decrease in Accuracy was compared to evaluate its ability to rank variables by relative importance. Despite being dual-pol, the results of classifications using Sentinel-1 coherence (12-day repeat) were significantly better than using fully polarimetric RADARSAT-2 coherence (24-day repeat), likely owing to the difference in baseline and specific acquisition dates of the data in this study. Overall, full growing season Sentinel-1 coherence time series produced higher accuracy results than fully polarimetric quad pol RADARSAT-2 coherence amplitude, difference in amplitude and polarimetric decomposition time series. Using a full growing season of time-series imagery in classification resulted in higher accuracy than using a few dates over a growing season. Using mean decrease in accuracy to rank and reduce variables resulted in a weaker classification than if the entire time series is used.

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Srivastava, H. S., P. Patel, Y. Sharma, and R. R. Navalgund. "Large-Area Soil Moisture Estimation Using Multi-Incidence-Angle RADARSAT-1 SAR Data." IEEE Transactions on Geoscience and Remote Sensing 47, no. 8 (August 2009): 2528–35. http://dx.doi.org/10.1109/tgrs.2009.2018448.

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Marghany, Maged, Arthur P. Cracknell, and Mazlan Hashim. "Modification of fractal algorithm for oil spill detection from RADARSAT-1 SAR data." International Journal of Applied Earth Observation and Geoinformation 11, no. 2 (April 2009): 96–102. http://dx.doi.org/10.1016/j.jag.2008.09.002.

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Schellenberger, T., T. Dunse, A. Kääb, J. Kohler, and C. H. Reijmer. "Surface speed and frontal ablation of Kronebreen and Kongsbreen, NW Svalbard, from SAR offset tracking." Cryosphere 9, no. 6 (December 15, 2015): 2339–55. http://dx.doi.org/10.5194/tc-9-2339-2015.

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Abstract. Kronebreen and Kongsbreen are among the fastest-flowing glaciers on Svalbard and, therefore, important contributors to the total dynamic mass loss from the archipelago. Here, we present a time series of area-wide surface velocity fields from April 2012 to December 2013 based on offset tracking on repeat high-resolution Radarsat-2 Ultrafine data. Surface speeds reached up to 3.2 m d−1 near the calving front of Kronebreen in summer 2013 and 2.7 m d−1 at Kongsbreen in late autumn 2012. Additional velocity fields from Radarsat-1, Radarsat-2 and TerraSAR-X data since December 2007 together with continuous GPS measurements on Kronebreen since September 2008 revealed complex patterns in seasonal and interannual speed evolution. Part of the ice-flow variations seem closely linked to the amount and timing of surface meltwater production and rainfall, both of which are known to have a strong influence on the basal water pressure and hence basal lubrication. In addition, terminus retreat and the associated reduction in back stress appear to have influenced the speed close to the calving front, especially at Kongsbreen in 2012 and 2013. Since 2007, Kongsbreen retreated up to 1800 m, corresponding to a total area loss of 2.5 km2. In 2011 the retreat of Kronebreen of up to 850 m, responsible for a total area loss of 2.8 km2, was triggered after a phase of stable terminus position since ~ 1990. Retreat is an important component of the mass balance of both glaciers, in which frontal ablation is the largest component. Total frontal ablation between April 2012 and December 2013 was estimated to 0.21–0.25 Gt a−1 for Kronebreen and 0.14–0.16 Gt a−1 for Kongsbreen.

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Schellenberger, T., T. Dunse, A. Kääb, J. Kohler, and C. H. Reijmer. "Surface speed and frontal ablation of Kronebreen and Kongsbreen, NW-Svalbard, from SAR offset tracking." Cryosphere Discussions 8, no. 6 (December 18, 2014): 6193–233. http://dx.doi.org/10.5194/tcd-8-6193-2014.

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Abstract. Kronebreen and Kongsbreen are among the fastest flowing glaciers on Svalbard, and therefore important contributors to glacier mass loss from the archipelago through frontal ablation. Here, we present a time series of area-wide surface velocity fields from April 2012 to December 2013 based on offset tracking on repeat high-resolution Radarsat-2 Ultrafine data. Surface speeds reached up to 3.2 m d−1 near the calving front of Kronebreen in summer 2013 and 2.7 m d−1 at Kongsbreen in late autumn 2012. Additional velocity fields from Radarsat-1, Radarsat-2 and TerraSAR-X data since December 2007 together with continuous GPS measurements on Kronebreen since September 2008 revealed complex patterns in seasonal and interannual speed evolution. Part of the ice-flow variations seem closely linked to the amount and timing of surface melt water production and rainfall, both of which are known to have a strong influence on the basal water pressure and lubrication. In addition, terminus retreat and the associated reduction in backstress appear to have influenced the speed close to the calving front, especially at Kongsbreen in 2012 and 2013. Since 2007, Kongsbreen retreated up to 1800 m, corresponding to a total area loss of 2.5 km2. In 2011 the retreat of Kronebreen of up to 850 m, responsible for a total area loss of 2.8 km2, was triggered after a phase of stable terminus position since ~1990. The retreat is an important component of the mass balance of both glaciers, in which frontal ablation is the largest component. Total frontal ablation between April 2012 and December 2013 was estimated to 0.21–0.25 Gt a−1 for Kronebreen and 0.14–0.16 Gt a−1 for Kongsbreen.

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SANTOS, ATHOS RIBEIRO DOS, WALDIR RENATO PARADELLA, and PAULO VENEZIANI. "AVALIAÇÃO DA ESTEREOSCOPIA SAR (STANDART-RADARSAT-1) E HÍBRIDA (STANDART-RADARSAT-1 & TM-LANDSAT-5) EM MAPEAMENTO GEOLÓGICO NA PROVÍNCIA MINERAL DE CARAJÁS." Revista Brasileira de Geociências 33, no. 2 (June 1, 2003): 153–60. http://dx.doi.org/10.25249/0375-7536.200333s2153160.

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Weber, Frank, Dan Nixon, and Jeff Hurley. "Semi-automated classification of river ice types on the Peace River using RADARSAT-1 synthetic aperture radar (SAR) imagery." Canadian Journal of Civil Engineering 30, no. 1 (February 1, 2003): 11–27. http://dx.doi.org/10.1139/l02-073.

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The winter regime of the Peace River in northern British Columbia and Alberta is a determining factor for the operation of the British Columbia Hydro and Power Authority Williston Reservoir. Therefore, fine beam RADARSAT-1 synthetic aperture radar (SAR) satellite images were acquired in winter and spring 2000 and 2001 and analyzed for ice cover types. Video footage of the ice conditions on the Peace River was obtained from aerial ice observations that were conducted simultaneously with the image acquisitions. The analysis of the images was done (i) visually and (ii) using an unsupervised Fuzzy K-means classification. To streamline the process in an operational environment, the unsupervised ice classification was semi-automated. The unsupervised classification broke the data into seven classes, which represent the major ice cover types observed on the Peace River. The spatial distribution of ice cover types as generated by the ice classification generally coincides well with air-truth information and backscatter signatures from SAR images. The location of the boundaries between the ice types appears to be accurate, but it may not be precise. The ice maps can be used for ice monitoring, decision-making purposes, or the verification of ice models.Key words: river ice, remote sensing, RADARSAT-1, Peace River, semi-automated classification.

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Kuang, Gangyao, Zhiguo He, and Jonathan Li. "Detecting Water Bodies on RADARSAT Imagery." GEOMATICA 65, no. 1 (March 2011): 15–25. http://dx.doi.org/10.5623/cig2011-005.

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This paper presents a novel geodesic active contour (GAC) model based on an edge detector for rapid detection of water bodies from spaceborne synthetic aperture radar (SAR) imagery with high speckle noise. The original edge indicator function based on gradients is replaced by an edge indicator function based on the ratio of exponentially weighted averages (ROEWA) operator. Thus, the capability of edge detection and the accuracy of locating edges are greatly improved, which makes the model more appropriate for SAR images. In addition, an enhancing term is added to the original model's energy function in order to boost the strength for the contour's evolution. An unconditionally stable additive operator splitting (AOS) scheme and a fast algorithm for re-initialization of the level set function are adopted, which not only enhances the model's stability, but also speeds up the model's convergence remarkably. The experimental results on simulated and real RADARSAT-1/-2 images show its efficiency and accuracy.

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Young, G. S., T. N. Sikora, and N. S. Winstead. "Use of Synthetic Aperture Radar in Finescale Surface Analysis of Synoptic-Scale Fronts at Sea." Weather and Forecasting 20, no. 3 (June 1, 2005): 311–27. http://dx.doi.org/10.1175/waf853.1.

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Abstract The viability of synthetic aperture radar (SAR) as a tool for finescale marine meteorological surface analyses of synoptic-scale fronts is demonstrated. In particular, it is shown that SAR can reveal the presence of, and the mesoscale and microscale substructures associated with, synoptic-scale cold fronts, warm fronts, occluded fronts, and secluded fronts. The basis for these findings is the analysis of some 6000 RADARSAT-1 SAR images from the Gulf of Alaska and from off the east coast of North America. This analysis yielded 158 cases of well-defined frontal signatures: 22 warm fronts, 37 cold fronts, 3 stationary fronts, 32 occluded fronts, and 64 secluded fronts. The potential synergies between SAR and a range of other data sources are discussed for representative fronts of each type.

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Wang, Zezhong, Jian Jiao, Qiming Zeng, and Junyi Liu. "A Three-Hierarchy Evaluation of Polarimetric Performance of GF-3, Compared with ALOS-2/PALSAR-2 and RADARSAT-2." Sensors 19, no. 7 (March 27, 2019): 1493. http://dx.doi.org/10.3390/s19071493.

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GaoFen-3 (GF-3) is the first Chinese civilian multi-polarization synthetic aperture radar (SAR) satellite, launched on 10 August of 2016, and put into operation at the end of January 2017. The polarimetric SAR (PolSAR) system of GF-3 is able to provide quad-polarization (quad-pol) images in a variety of geophysical research and applications. However, this ability increases the complexity of maintaining image quality and calibration. As a result, to evaluate the quality of polarimetric data, polarimetric signatures are necessary to guarantee accuracy. Compared with some other operational space-borne PolSAR systems, such as ALOS-2/PALSAR-2 (ALOS-2) and RADARSAT-2, GF-3 has less reported calibration and image quality files, forcing users to validate the quality of polarimetric imagery of GF-3 before quantitative applications. In this study, without the validation data obtained from a calibration infrastructure, an innovative, three-hierarchy strategy was proposed to assess PolSAR data quality, in which the performance of GF-3 data was evaluated with ALOS-2 and RADARSAT-2 data as references. Experimental results suggested that: (1) PolSAR data of GF-3 satisfied backscatter reciprocity, similar with that of RADARSAT-2; (2) most of the GF-3 PolSAR images had no signs of polarimetric distortion affecting decomposition, and the system of GF-3 may have been improved around May 2017; and (3) the classification accuracy of GF-3 varied from 75.0% to 91.4% because of changing image-acquiring situations. In conclusion, the proposed three-hierarchy approach has the ability to evaluate polarimetric performance. It proved that the residual polarimetric distortion of calibrated GF-3 PolSAR data remained at an insignificant level, with reference to that of ALOS-2 and RADARSAT-2, and imposed no significant impact on the polarimetric decomposition components and classification accuracy.

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Struckmeyer, H. I. M., A. K. Williams, R. Cowley, J. M. Totterdell, G. Lawrence, and G. W. O’Brien. "EVALUATION OF HYDROCARBON SEEPAGE IN THE GREAT AUSTRALIAN BIGHT." APPEA Journal 42, no. 1 (2002): 371. http://dx.doi.org/10.1071/aj01020.

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The regional assessment of hydrocarbon seepage is built around a combination of Radarsat and ERS Synthetic Aperture Radar (SAR) data, acquired during 1998 and 1999, as part of a collaborative project between Geoscience Australia, Nigel Press Associates, Radarsat International and AUSLIG (specifically the Australian Centre for Remote Sensing). In total, 55 Radarsat Wide 1 Beam Mode scenes and one ERS scene from the Great Australian Bight (GAB) region were analysed. The data were integrated with regional geological information, and other hydrocarbon migration and seepage indicators such as reprocessed and reinterpreted legacy Airborne Laser Fluorosensor (ALF) data, to provide an assessment of the possible charge characteristics of the region.The results of the study suggest that active, though areally restricted, liquid hydrocarbon seepage is occurring within the Bight Basin. The majority of seepage slicks occur along the outer margin of the major depocentre, the Ceduna Sub-basin, in areas where significant Late Tertiary to Recent faulting extends to the seafloor. Very little evidence of seepage was observed on the SAR data above the main depocentre, which is an area of minimal Late Tertiary to Recent faulting. Reprocessed ALF data reveal three main areas with relatively dense fluors. Although they are not directly coincident with locations of seepage interpreted from SAR data, their distribution support the pattern of preferred leakage along the basin margins.Integration of regional geological models with the results of this study suggests that structural features related to active tectonism have focused laterally migrating hydrocarbons to produce active seepage at specific locations in the basin. Where these features are absent, seepage may be passive and/or be governed by long distance migration to points of seal failure. Together with oil and gas shows in exploration wells, observations from this study provide further evidence that liquid hydrocarbons have been generated in the Great Australian Bight.

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Patruno, Jolanda, Magdalena Fitrzyk, and Jose Manuel Delgado Blasco. "Monitoring and Detecting Archaeological Features with Multi-Frequency Polarimetric Analysis." Remote Sensing 12, no. 1 (December 18, 2019): 1. http://dx.doi.org/10.3390/rs12010001.

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In remote sensing for archaeology, an unequivocal method capable of automatic detection of archaeological features still does not exists. Applications of Synthetic Aperture Radar (SAR) remote sensing for archaeology mainly focus on high spatial resolution SAR sensors, which allow the recognition of structures of small dimension and give information of the surface topography of sites. In this study we investigated the potential of combined dual and fully polarized SAR data and performed polarimetric multi-frequency and multi-incidence angle analysis of C-band Sentinel-1, L-band Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar (ALOS PALSAR) and of C-band Radar Satellite-2 (RADARSAT-2) datasets for the detection of surface and subsurface archaeological structures over the United Nations Educational, Scientific and Cultural Organization (UNESCO) site of Gebel Barkal (Sudan). While PALSAR offers a good historical reference, Sentinel-1 time series provide recent and systematic monitoring opportunities. RADARSAT-2 polarimetric data have been specifically acquired in 2012/2013, and have been scheduled to achieve a multi-temporal observation of the archaeological area under study. This work demonstrated how to exploit a complex but significant dataset composed of SAR full polarimetric and dual polarimetric acquisitions, with the purpose of identifying the most suitable earth observation technique for the preservation and identification of archaeological features. The scientific potential of the illustrated analysis fits perfectly with the current delicate needs of cultural heritage; such analysis demonstrates how multi-temporal and multi-data cultural heritage monitoring can be applied not only for documentation purposes, but can be addressed especially to those areas exposed to threats of different nature that require a constant and prompt intervention plans.

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Brisco, Brian, Masoud Mahdianpari, and Fariba Mohammadimanesh. "Hybrid Compact Polarimetric SAR for Environmental Monitoring with the RADARSAT Constellation Mission." Remote Sensing 12, no. 20 (October 9, 2020): 3283. http://dx.doi.org/10.3390/rs12203283.

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Canada’s successful space-based earth-observation (EO) radar program has earned widespread and expanding user acceptance following the launch of RADARSAT-1 in 1995. RADARSAT-2, launched in 2007, while providing data continuity for its predecessor’s imaging capabilities, added new polarimetric modes. Canada’s follow-up program, the RADARSAT Constellation Mission (RCM), launched in 2019, while providing continuity for its two predecessors, includes an innovative suite of polarimetric modes. In an effort to make polarimetry accessible to a wide range of operational users, RCM uses a new method called hybrid compact polarization (HCP). There are two essential elements to this approach: (1) transmit only one polarization, circular; and (2) receive two orthogonal polarizations, for which RCM uses H and V. This configuration overcomes the conventional dual and full polarimetric system limitations, which are lacking enough polarimetric information and having a small swath width, respectively. Thus, HCP data can be considered as dual-pol data, while the resulting polarimetric classifications of features in an observed scene are of comparable accuracy as those derived from the traditional fully polarimetric (FP) approach. At the same time, RCM’s HCP methodology is applicable to all imaging modes, including wide swath and ScanSAR, thus overcoming critical limitations of traditional imaging radar polarimetry for operational use. The primary image data products from an HCP radar are different from those of a traditional polarimetric radar. Because the HCP modes transmit circularly polarized signals, the data processing to extract polarimetric information requires different approaches than those used for conventional linearly polarized polarimetric data. Operational users, as well as researchers and students, are most likely to achieve disappointing results if they work with traditional polarimetric processing tools. New tools are required. Existing tutorials, older seminar notes, and reference papers are not sufficient, and if left unrevised, could succeed in discouraging further use of RCM polarimetric data. This paper is designed to provide an initial response to that need. A systematic review of studies that used HCP SAR data for environmental monitoring is also provided. Based on this review, HCP SAR data have been employed in oil spill monitoring, target detection, sea ice monitoring, agriculture, wetland classification, and other land cover applications.

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Srivastava, Hari Shanker, Parul Patel, and Ranganath R. Navalgund. "Incorporating soil texture in soil moisture estimation from extended low‐1 beam mode RADARSAT‐1 SAR data." International Journal of Remote Sensing 27, no. 12 (June 2006): 2587–98. http://dx.doi.org/10.1080/01431160500497838.

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Kumar, Praveen, and Akhouri Pramod Krishna. "InSAR-Based Tree Height Estimation of Hilly Forest Using Multitemporal Radarsat-1 and Sentinel-1 SAR Data." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 12, no. 12 (December 2019): 5147–52. http://dx.doi.org/10.1109/jstars.2019.2963443.

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Merzouki, Amine, Heather McNairn, Jarrett Powers, and Matthew Friesen. "Synthetic Aperture Radar (SAR) Compact Polarimetry for Soil Moisture Retrieval." Remote Sensing 11, no. 19 (September 25, 2019): 2227. http://dx.doi.org/10.3390/rs11192227.

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Soil moisture is a factor for risk analysis in the agricultural sector, yet access to temporally and spatially detailed data is challenging for much of the world’s agricultural extend. Significant effort has been focused on developing methodologies to estimate soil moisture from microwave satellite sensors. Canada’s RADARSAT Constellation Mission (RCM) is capable of acquiring imagery in a number of modes with a Compact Polarimetry (CP) configuration at different spatial resolutions (1 to 100 m). RCM offers greater polarization diversity, wide swaths and improved temporal frequency (4-day exact revisit time); all important considerations for large area monitoring of agricultural resources. The major goal of this study was to examine whether CP could accurately estimate surface soil moisture over bare fields. A methodology was developed using the calibrated Integral Equation Model (IEM) multi-polarization inversion approach. RADARSAT-2 data was acquired between 2012 and 2017 over a test site in eastern Canada. CP backscatter for two RCM modes (medium resolution 30 m and 50 m (MR30 and MR50)) was simulated using 63 RADARSAT-2 fully polarimetric images. A simple transfer function was developed between RH (right circular-horizontal) and HH (horizontal-horizontal) intensity, as well as RV (right circular-vertical) and VV (vertical-vertical). These HH- and VV-like intensities were then used in the multi-polarization inversion scheme to retrieve soil moisture. CP soil moisture retrievals were validated against soil moisture measurements from a long term in-situ network instrumented with five soil moisture stations. Retrieved and measured soil moisture were well correlated (R > 0.70) with an unbiased root mean square error (ubRMSE) less than 0.06 m3/m3. Overall, the developed method clearly captured the dry down and wetting trends observed through the five years study period. However, results demonstrated that the inversion method introduced a consistent bias (~0.10 m3/m3). Comparison of CP soil moisture estimates to those from the Soil Moisture Active Passive (SMAP) passive microwave satellite confirmed this bias. This study demonstrates the potential of C-band CP data to deliver accurate soil moisture products over wide swaths for regional and national soil moisture monitoring.

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Mulas, M., M. Petitta, A. Corsini, S. Schneiderbauer, F. V. Mair, and C. Iasio. "Long-term monitoring of a deep-seated, slow-moving landslide by mean of C-band and X-band advanced interferometric products: the Corvara in Badia case study (Dolomites, Italy)." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-7/W3 (April 29, 2015): 827–29. http://dx.doi.org/10.5194/isprsarchives-xl-7-w3-827-2015.

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The availability of data from various Synthetic Aperture Radar (SAR) operating in X-Band and C-Band acquired in the last decades enables to monitor slopes affected by landslides. The ASI-founded project ‘LAWINA’ (2010 – 2012) aimed at the improvement of SAR – based monitoring techniques as well as at the integration of SAR data with data stemming from other sensors. Test case area of LAWINA has been a slow-moving landslide located up-stream of Corvara in Badia village in the Dolomites, Italy. Within the scope of the project different time-series obtained through 35 Envisat2, 40 Radarsat-1 and 46 Cosmo-SkyMed covering this test area have been processed in order to explore the potentials to analyse historical and near real time landslide dynamics. The SAR data are characterized by various geometric and temporal resolutions having been acquired by 3 sensors operating at different bands in different periods between 2003 and 2011. TeleRilevamento Europa (TRE) exploited these data in order to retrive displacement timeseries applying its proprietary SqueeSAR algorithm. After re-projecting Envisat-2 and Radarsat datasets according to the CSK Line Of Sight a comparison of displacements recorded by each sensor has been possible. For this purpose, we have selected areas characterized by the presence of Persistent Scatterers or Diffused Scatterers from at least two datasets. This multi-sensor approach allowed determining the slope displacement tracking during 8 years. Even though the different time series are not formally integrated each other, the result is accurate enough to allow the evaluation of the landslide’s behaviour and trend over several years.

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Smith, A. J. E. "A practical method for computing SAR satellite revisit times: application to RADARSAT‐1 and ENVISAT." International Journal of Remote Sensing 28, no. 6 (March 15, 2007): 1123–35. http://dx.doi.org/10.1080/01431160500307094.

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Song, Yeong-Sun, Hong-Gyoo Sohn, and Choung-Hwan Park. "Efficient Water Area Classification Using Radarsat-1 SAR Imagery in a High Relief Mountainous Environment." Photogrammetric Engineering & Remote Sensing 73, no. 3 (March 1, 2007): 285–96. http://dx.doi.org/10.14358/pers.73.3.285.

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DeLancey, Evan R., Brian Brisco, Logan J. T. McLeod, Richard Hedley, Erin M. Bayne, Kevin Murnaghan, Fiona Gregory, and Jahan Kariyeva. "Modelling, Characterizing, and Monitoring Boreal Forest Wetland Bird Habitat with RADARSAT-2 and Landsat-8 Data." Water 13, no. 17 (August 25, 2021): 2327. http://dx.doi.org/10.3390/w13172327.

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Earth observation technologies have strong potential to help map and monitor wildlife habitats. Yellow Rail, a rare wetland obligate bird species, is a species of concern in Canada and provides an interesting case study for monitoring wetland habitat with Earth observation data. Yellow Rail has highly specific habitat requirements characterized by shallowly flooded graminoid vegetation, the availability of which varies seasonally and year-to-year. Polarimetric Synthetic Aperture Radar (SAR) in combination with optical data should, in theory, be a great resource for mapping and monitoring these habitats. This study evaluates the use of RADARSAT-2 data and Landsat-8 data to characterize, map, and monitor Yellow Rail habitat in a wetland area within the mineable oil sands region. Specifically, we investigate: (1) The relative importance of polarimetric SAR and Landsat-8 data for predicting Yellow Rail habitat; (2) characterization of wetland habitat with polarimetric SAR data; (3) yearly trends in available habitat; and (4) predictions of potentially suitable habitat across northeastern Alberta. Results show that polarimetric SAR using the Freeman–Durden decomposition and polarization ratios were the most important predictors when modeling the Yellow Rail habitat. These parameters also effectively characterize this habitat based on high congruence with existing descriptions of suitable habitat. Applying the prediction model across all wetland areas showed accurate predictions of occurrence (validated on field occurrence data), and high probability habitats were constrained to very specific wetland areas. Using the RADARSAT-2 data to monitor yearly changes to Yellow Rail habitat was inconclusive, likely due to the different image acquisition times of the 2014 and 2016 images, which may have captured seasonal, rather than inter-annual, wetland dynamics. Polarimetric SAR has proved to be very useful for capturing the specific hydrology and vegetation structure of the Yellow Rail habitat, which could be a powerful technology for monitoring and conserving wetland species habitat.

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Chen, Yong, Hui Chang Zhao, Si Chen, and Shu Ning Zhang. "An Improved Focusing Algorithm for Missile-Borne SAR with High Squint." Applied Mechanics and Materials 608-609 (October 2014): 761–65. http://dx.doi.org/10.4028/www.scientific.net/amm.608-609.761.

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Due to that the Doppler parameters vary according to slant and the resolution is lower using imaging algorithm of traditional pulse compression in processing raw echo data of the missile-borne synthetic aperture radar (SAR). Moreover, an algorithm is proposed to solve these problems, which is based on the fractional Fourier transform (FrFT) for missile-borne SAR imaging. Firstly, an echo signal model is built for the terminal guidance stage of the missile-borne SAR. Secondly, measure the chirp rate of the echo signal through the local optimum processing and get the optimum angles for the FrFT, and then the entire SAR image can be obtained by using FrFT with the optimum angles of the azimuth and range. Finally, the performances of the algorithms are assessed using simulated and real Radarsat-1 data sets. The results confirm that the FrFT-based missile-borne SAR processing methods provide enhanced resolution yielding both lower side lobes effects and improved target detection. The method introduced in this paper has important theoretical significance in detection and recognition for military targets and precision guidance.

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Brown, Carl E., and Mervin F. Fingas. "NEW SPACE-BORNE SENSORS FOR OIL SPILL RESPONSE." International Oil Spill Conference Proceedings 2001, no. 2 (March 1, 2001): 911–16. http://dx.doi.org/10.7901/2169-3358-2001-2-911.

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ABSTRACT In the next few years, several new satellite sensors will be launched by various national remote-sensing/earth observation agencies around the globe. It is hoped that these space-borne sensors will provide oil spill response personnel with more than just a synoptic overview of the spill scene. The state-of-the-art capabilities of these new sensors should provide responders with information that can be used in a tactical role as opposed to older-generation sensors that perform a strictly strategic role. Of primary use to spill response coordinators is the Synthetic Aperture Radar (SAR) sensor. The next generation of SAR satellites will have enhanced capabilities when compared to their predecessors. The enhancements include the addition of Polarimetric modes for satellites, including Envisat-1 and RADARSAT-2. RADARSAT-2 will be quad-polarimetric, with resolutions of 8 × 8 m in Polarimetric mode and down to 3 × 3 m in co- or cross-pole modes. The ASAR sensor on Envisat-1 will follow up the successful missions of the European Space Agencies ERS-1, −2 satellites. ASAR will have an alternating polarization mode, and transmit and receive polarization can be selected, thus allowing scenes to be imaged simultaneously in two polarizations. In addition to SAR satellites, several new optical satellites have been or will be launched over the next few years. While optical sensors often are plagued by periods of foul weather that frequently accompany oil spills, some of these sensors will provide valuable information that can be used in conjunction with the radar data in a corroborative fashion. The most useful of the new optical satellites might well be those used to collect data for weather forecasting. This paper will review the operating characteristics and modes of recent and planned satellite sensors, with an eye toward their usefulness for tactical remote sensing of oil spills.

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Yarai, Hiroshi, Taku Ozawa, Takuya Nishimura, Mikio Tobita, and Tetsuro Imakiire. "Crustal deformation associated with the northern Miyagi earthquake detected by RADARSAT-1 and ENVISAT SAR interferometry." Earth, Planets and Space 56, no. 2 (February 2004): 103–7. http://dx.doi.org/10.1186/bf03353394.

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Sahebi, M. R., F. Bonn, and Q. H. J. Gwyn. "Estimation of the moisture content of bare soil from RADARSAT-1 SAR using simple empirical models." International Journal of Remote Sensing 24, no. 12 (January 2003): 2575–82. http://dx.doi.org/10.1080/0143116031000072948.

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Lee, Hoonyol, Heesam Chae, and Seong-Jun Cho. "Radar Backscattering of Intertidal Mudflats Observed by Radarsat-1 SAR Images and Ground-Based Scatterometer Experiments." IEEE Transactions on Geoscience and Remote Sensing 49, no. 5 (May 2011): 1701–11. http://dx.doi.org/10.1109/tgrs.2010.2084094.

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Aly, Ziad, Ferdinand J. Bonn, and Ramata Magagi. "Analysis of the Backscattering Coefficient of Salt-Affected Soils Using Modeling and RADARSAT-1 SAR Data." IEEE Transactions on Geoscience and Remote Sensing 45, no. 2 (February 2007): 332–41. http://dx.doi.org/10.1109/tgrs.2006.887163.

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Journal articles on the topic 'RADARSAT-1 SAR'

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