Semi-automated classification of river ice types on the Peace River using RADARSAT-1 synthetic aperture radar (SAR) imagery

2003 ◽  
Vol 30 (1) ◽  
pp. 11-27 ◽  
Author(s):  
Frank Weber ◽  
Dan Nixon ◽  
Jeff Hurley
Keyword(s):  
British Columbia ◽  
Synthetic Aperture Radar ◽  
Ice Cover ◽  
Synthetic Aperture ◽  
River Ice ◽  
Automated Classification ◽  
Operational Environment ◽  
Peace River ◽  
Sar Imagery ◽  
Aperture Radar

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.

scholarly journals RASF and DEDR-POCS Image Fusion through Multi-layer Perceptron in SAR Imagery Systems

2019 ◽  
pp. 20-26
Author(s):  
Israel Yañez-Vargas ◽  
Joel Quintanilla-Domínguez ◽  
Gabriel Aguilera-Gonzalez
Keyword(s):  
Synthetic Aperture Radar ◽  
Image Fusion ◽  
Low Cost ◽  
Synthetic Aperture ◽  
Discrete Wavelet ◽  
Multi Layer Perceptron ◽  
Robust Adaptive ◽  
Sar Imagery ◽  
Design Regularization ◽  
Aperture Radar

This paper presents a novel multi-layer perceptron (MLP) based image fusion technique, which fuses two synthetic aperture radar (SAR) images, obtained from the same spatial reflectivity map, acquired with a conventional low-cost fractional synthetic aperture radar (Fr-SAR) system, enhanced via two different methodologies. The first image is enhanced using the traditional descriptive experiment design regularization (DEDR) framework through the projection onto convex solution sets (POCS) method; the second image is enhanced with the DEDR framework by incorporating the robust adaptive spatial filtering (RASF) solution operator. This work describes a MLP based technique applied to the pixel level multi-focus fusion problem characterized by the use of image windows with the idea of reducing noise and determining which pixel is clearer between the two images. Experimental results show that the proposed novel method outperforms the discrete wavelet transform based most competing approach.

scholarly journals Refocusing of Multiple Moving Targets Based on the Joint Sparse Processing of One Channel Synthetic Aperture Radar Imagery Patches

Electronics ◽  
2019 ◽  
Vol 8 (11) ◽  
pp. 1215 ◽  
Author(s):  
Xin Wang ◽  
Ling Qiao
Keyword(s):  
Synthetic Aperture Radar ◽  
Moving Objects ◽  
Radar Data ◽  
Synthetic Aperture ◽  
Moving Targets ◽  
Lp Norm ◽  
Radar Imagery ◽  
Sar Imagery ◽  
Norm Constraint ◽  
Aperture Radar

A sparse-based refocusing methodology for multiple slow-moving targets (MTs) located inside strong clutter regions is proposed in this paper. The defocused regions of MTs in synthetic aperture radar (SAR) imagery were utilized here instead of the whole original radar data. A joint radar projection operator for the static and moving objects was formulated and employed to construct an optimization problem. The Lp norm constraint was utilized to promote the separation of MT data and the suppression of clutter. After the joint sparse imaging processing, the energy of strong static targets could be suppressed significantly in the reconstructed MT imagery. The static scene imagery could be derived simultaneously without the defocused MT. Finally, numerical simulations were used verify the validity and robustness of the proposed methodology.

Better Utilization of SAR Dynamic Range

1977 ◽  
Vol 21 (3) ◽  
pp. 235-240
Author(s):  
Edward J. Dragavon
Keyword(s):  
Computer Simulation ◽  
Synthetic Aperture Radar ◽  
Real Time ◽  
Image Enhancement ◽  
Dynamic Range ◽  
Synthetic Aperture ◽  
Analytic Methods ◽  
Sar Imagery ◽  
Gray Shade ◽  
Aperture Radar

Three general classes of image enhancement techniques for synthetic aperture radar (SAR) video were investigated through non-real-time computer simulation. The general categories were 1) monochromatic adaptive gray shade transformations, 2) pseudocolor encoding, and 3) feature analytic methods. The class of feature analytic techniques was found to have the greatest potential for improving the operational utility of SAR imagery.

scholarly journals Consistent ice and open water classification combining historical synthetic aperture radar satellite images from ERS-1/2, Envisat ASAR, RADARSAT-2 and Sentinel-1A/B

2020 ◽  
Vol 61 (82) ◽  
pp. 40-50 ◽  
Author(s):  
A. Malin Johansson ◽  
Eirik Malnes ◽  
Sebastian Gerland ◽  
Anca Cristea ◽  
Anthony P. Doulgeris ◽  
...  
Keyword(s):  
Sea Ice ◽  
Synthetic Aperture Radar ◽  
Satellite Images ◽  
Satellite Image ◽  
Open Water ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
Synthetic Aperture ◽  
Envisat Asar ◽  
Aperture Radar

AbstractSynthetic Aperture Radar (SAR) satellite images are used to monitor Arctic sea ice, with systematic data records dating back to 1991. We propose a semi-supervised classification method that separates open water from sea ice and can utilise ERS-1/2, Envisat ASAR, RADARSAT-2 and Sentinel-1 SAR images. The classification combines automatic segmentation with a manual segment selection stage. The segmentation algorithm requires only the backscatter intensities and incidence angle values as input, therefore can be used to establish a consistent decadal sea ice record. In this study we investigate the sea ice conditions in two Svalbard fjords, Kongsfjorden and Rijpfjorden. Both fjords have a seasonal ice cover, though Rijpfjorden has a longer sea ice season. The satellite image dataset has weekly to daily records from 2002 until now, and less frequent records between 1991 and 2002. Time overlap between different sensors is investigated to ensure consistency in the reported sea ice cover. The classification results have been compared to high-resolution SAR data as well as in-situ measurements and sea ice maps from Ny-Ålesund. For both fjords the length of the sea ice season has shortened since 2002 and for Kongsfjorden the maximum sea ice coverage is significantly lower after 2006.

Ship hull characteristics from surface wake synthetic aperture radar (SAR) imagery

1996 ◽  
Vol 23 (5) ◽  
pp. 363-383 ◽  
Author(s):  
Owen M. Griffin ◽  
Henry T. Wang ◽  
Guy A. Meadows
Keyword(s):  
Synthetic Aperture Radar ◽  
Ship Hull ◽  
Synthetic Aperture ◽  
Sar Imagery ◽  
Aperture Radar

Color Coding of Synthetic Aperture Radar Imagery

1984 ◽  
Vol 28 (4) ◽  
pp. 303-307
Author(s):  
Frank Ward ◽  
Denise Wilson ◽  
Donald Wallquist ◽  
Gilbert Kuperman
Keyword(s):  
Synthetic Aperture Radar ◽  
Transmission Lines ◽  
Urban Areas ◽  
Power Transmission ◽  
Synthetic Aperture ◽  
Power Transmission Lines ◽  
Oil Refineries ◽  
Black And White ◽  
Sar Imagery ◽  
Aperture Radar

The purpose of our study was to investigate four types of coding strategies using the same Synthetic Aperture Radar (SAR) imagery. We digitized unclassified SAR imagery to include scenes from urban areas, seaports, oil refineries, industrial sites, an airfield, and power transmission lines. Two color and two black and white (BW) coding schemes were applied to the imagery. Five experienced radar interpreters were briefed and viewed 35 mm slides of the imagery. They judged image usefulness by reference to an interpretability scale. Analysis of the ratings showed that the BW codes received significantly higher interpretability ratings than the color codes.

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