scholarly journals WETLAND MAPPING WITH MULTITEMPORAL SENTINEL RADAR REMOTE SENSING IN THE SOUTHEAST REGION OF BRAZIL

2020 ◽  
Vol XLII-3/W12-2020 ◽  
pp. 237-242
Author(s):  
J. B. G. Salinas ◽  
M. K. P. Eggerth ◽  
M. E. Miller ◽  
R. R. B. Meza ◽  
J. T. A. Chacaltana ◽  
...  
Keyword(s):  
Synthetic Aperture Radar ◽  
Land Reclamation ◽  
Google Earth ◽  
Synthetic Aperture ◽  
Southeastern Brazil ◽  
Wetland Mapping ◽  
Artificial Wetlands ◽  
Imagery Condition ◽  
Sar Imagery ◽  
Aperture Radar

Abstract. A classification method with multi-temporal images of synthetic aperture radar (SAR) combined with Geographic information system, geoinformation data, and field validation, was applied for wetland mapping accuracy and typology. Wetland mapping is vital for management and conservation, particularly under environmental pressures such as wetland drainage and land reclamation. The aim of this study is to develop an accurate mapping of wetlands and open water systems of the Lower Doce River Valley - LDRV (Southeastern Brazil) with Synthetic Aperture Radar (SAR) imagery, using multitemporal classification techniques and ground truth validation. Sentinel-1B SAR imagery from 2016 and 2019 was processed with Google Earth Engine (GEE). Monthly median imagery condition for the rainy season was obtained and K-means unsupervised classification was applied. The study yields 4,157 wetlands, 262.27 km2 with predominant small patches. Fieldwork revealed three main wetlands categories: coastal wetlands, inland wetlands and artificial wetlands. The results have shown an overall accuracy of 81.9% and a Kappa coefficient of 0.71. Wetlands, non-wetlands, and open waters classes present accuracy of 50, 80 and 95%, respectively.

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.

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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