IHS-GTF: A Fusion Method for Optical and Synthetic Aperture Radar Data

Optical and Synthetic Aperture Radar (SAR) fusion is addressed in this paper. Intensity–Hue–Saturation (IHS) is an easily implemented fusion method and can separate Red–Green–Blue (RGB) images into three independent components; however, using this method directly for optical and SAR images fusion will cause spectral distortion. The Gradient Transfer Fusion (GTF) algorithm is proposed firstly for infrared and gray visible images fusion, which formulates image fusion as an optimization problem and keeps the radiation information and spatial details simultaneously. However, the algorithm assumes that the spatial details only come from one of the source images, which is inconsistent with the actual situation of optical and SAR images fusion. In this paper, a fusion algorithm named IHS-GTF for optical and SAR images is proposed, which combines the advantages of IHS and GTF and considers the spatial details from the both images based on pixel saliency. The proposed method was assessed by visual analysis and ten indices and was further tested by extracting impervious surface (IS) from the fused image with random forest classifier. The results show the good preservation of spatial details and spectral information by our proposed method, and the overall accuracy of IS extraction is 2% higher than that of using optical image alone. The results demonstrate the ability of the proposed method for fusing optical and SAR data effectively to generate useful data.

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Mapping of wheat lodging susceptibility with synthetic aperture radar data

Remote Sensing of Environment ◽

10.1016/j.rse.2021.112427 ◽

2021 ◽

Vol 259 ◽

pp. 112427

Author(s):

Sugandh Chauhan ◽

Roshanak Darvishzadeh ◽

Sander H. van Delden ◽

Mirco Boschetti ◽

Andrew Nelson

Keyword(s):

Synthetic Aperture Radar ◽

Radar Data ◽

Synthetic Aperture ◽

Synthetic Aperture Radar Data ◽

Aperture Radar

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Comparison of Target Detectors to Identify Icebergs in Quad-Polarimetric L-Band Synthetic Aperture Radar Data

Remote Sensing ◽

10.3390/rs13091753 ◽

2021 ◽

Vol 13 (9) ◽

pp. 1753

Author(s):

Johnson Bailey ◽

Armando Marino ◽

Vahid Akbari

Keyword(s):

Sea Ice ◽

Synthetic Aperture Radar ◽

Roc Curves ◽

Radar Data ◽

Open Ocean ◽

Synthetic Aperture ◽

False Alarms ◽

Synthetic Aperture Radar Data ◽

Whitening Filter ◽

Aperture Radar

Icebergs represent hazards to ships and maritime activities and therefore their detection is essential. Synthetic Aperture Radar (SAR) satellites are very useful for this, due to their capability to acquire data under cloud cover and during day and night passes. In this work, we compared six state-of-the-art polarimetric target detectors to test their performance and ability to detect small-sized icebergs <120 m in four locations in Greenland. We used four single-look complex (SLC) ALOS-2 quad-polarimetric images from JAXA for quad-polarimetric detection and we compared with dual-polarimetric detectors using only the channels HH and HV. We also compared these detectors with single-polarimetric intensity channels and we tested using two scenarios: open ocean and sea ice. Our results show that the multi-look polarimetric whitening filter (MPWF) and the optimal polarimetric detector (OPD) provide the most optimal performance in quad- and dual-polarimetric mode detection. The analysis shows that, overall, quad-polarimetric detectors provide the best detection performance. When the false alarm rate (PF) is fixed to 10-5, the probabilities of detection (PD) are 0.99 in open ocean and 0.90 in sea ice. Dual-polarimetric or single-polarimetric detectors show an overall reduction in performance (the ROC curves show a decrease), but this degradation is not very large (<0.1) when the value of false alarms is relatively high (i.e., we are interested in bigger icebergs with a brighter backscattering >120 m, as they are easier to detect). However, the differences between quad- and dual- or single-polarimetric detectors became much more evident when the PF value was fixed to low detection probabilities 10-6 (i.e., smaller icebergs). In the single-polarimetric mode, the HV channel showed PD values of 0.62 for open ocean and 0.26 for sea ice, compared to values of 0.81 (open ocean) and 0.77 (sea ice) obtained with quad-polarimetric detectors.

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Fully polarimetric synthetic aperture radar data classification using probabilistic and non-probabilistic kernel methods

European Journal of Remote Sensing ◽

10.1080/22797254.2021.1924081 ◽

2021 ◽

pp. 1-8

Author(s):

Iman Khosravi ◽

Yury Razoumny ◽

Javad Hatami Afkoueieh ◽

Seyed Kazem Alavipanah

Keyword(s):

Synthetic Aperture Radar ◽

Kernel Methods ◽

Data Classification ◽

Radar Data ◽

Synthetic Aperture ◽

Polarimetric Synthetic Aperture Radar ◽

Synthetic Aperture Radar Data ◽

Aperture Radar

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Earth Environmental Monitoring Using Multi-Temporal Synthetic Aperture Radar: A Critical Review of Selected Applications

Remote Sensing ◽

10.3390/rs13040604 ◽

2021 ◽

Vol 13 (4) ◽

pp. 604

Author(s):

Donato Amitrano ◽

Gerardo Di Martino ◽

Raffaella Guida ◽

Pasquale Iervolino ◽

Antonio Iodice ◽

...

Keyword(s):

Remote Sensing ◽

Synthetic Aperture Radar ◽

Microwave Remote Sensing ◽

Radar Data ◽

Synthetic Aperture ◽

Special Focus ◽

Arid Environments ◽

Synthetic Aperture Radar Data ◽

Multi Temporal ◽

Aperture Radar

Microwave remote sensing has widely demonstrated its potential in the continuous monitoring of our rapidly changing planet. This review provides an overview of state-of-the-art methodologies for multi-temporal synthetic aperture radar change detection and its applications to biosphere and hydrosphere monitoring, with special focus on topics like forestry, water resources management in semi-arid environments and floods. The analyzed literature is categorized on the base of the approach adopted and the data exploited and discussed in light of the downstream remote sensing market. The purpose is to highlight the main issues and limitations preventing the diffusion of synthetic aperture radar data in both industrial and multidisciplinary research contexts and the possible solutions for boosting their usage among end-users.

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