Precipitation signature on side-looking aperture radar imaging: Sensitivity analysis to surface effects at C, X and Ku band

Polverari, Federica; Mori, Saverio; Pierdicca, Nazzareno; Marzano, Frank S.; Pulvirenti, Luca

doi:10.1109/eurad.2014.6991241

Cited by 4 publications

(3 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Although the sea backscattering coefficient increases as the frequency increases, the three responses have the same trends [37]. For moderate wind speeds, the backscattering coefficients of the C-band, X-band, and Ku-band are similar [38].…”

Section: Analyses Of the Sea Surface Current Velocity Estimationmentioning

confidence: 69%

“…In addition, for the two-scale model, the sea backscattering coefficient is related to the radar frequency, incidence angle, wind speed, etc. Although the sea backscattering coefficient increases as the frequency increases, the three responses have the same trends [37]. For moderate wind speeds, The spatial averaging processing is carried out to remove the orbital velocity of the long waves, but the choice of spatial scale will affect the estimation precision.…”

Section: Analyses Of the Sea Surface Current Velocity Estimationmentioning

confidence: 99%

See 1 more Smart Citation

Sea Surface Current Estimation Using Airborne Circular Scanning SAR with a Medium Grazing Angle

et al. 2018

View full text Add to dashboard Cite

Circular scanning synthetic aperture radar (SAR) is a novel imaging mode wherein the radar antenna rotates from 0 degrees to 360 degrees along the platform flight direction, providing us with a potentially effective technique to estimate the sea surface current velocity. In this paper, we propose a novel method to estimate the sea surface current velocity utilizing the Doppler centroid shifts of different scan angles over 360 degrees after the airborne platform motion compensation. In this method, the Doppler centroid shifts of the sea clutter at different scan angles are first extracted, and the corresponding compensation errors caused by the azimuth pointing and the incidence angle of the radar beam are considered. Finally, the least squares (LS) technique is applied to estimate the along-track velocity component and the cross-track velocity component of the sea surface current. The effectiveness of the proposed method is verified by the real data recorded by an airborne circular scanning SAR system.

show abstract

Section: Analyses Of the Sea Surface Current Velocity Estimationmentioning

confidence: 69%

Section: Analyses Of the Sea Surface Current Velocity Estimationmentioning

confidence: 99%

Sea Surface Current Estimation Using Airborne Circular Scanning SAR with a Medium Grazing Angle

et al. 2018

View full text Add to dashboard Cite

show abstract

“…This methods (image thresholding) sets as flooded all the pixels with a radar backscatter lower than a certain threshold value (Mason et al, 2012a(Mason et al, , 2012bPulvirenti et al, 2012;Schumann et al, 2010;Townsend, 2002), is computationally not demanding, provides reliable results and is ideal for rapid mapping. However, it is affected by sources of error typical of SAR flood mapping: 1) Atmospheric disturbances (Atlas and Moore, 1987;Danklmayer andChandra, 2009a, 2009b;Jameson et al, 1997;Polverari et al, 2014); 2) Bragg resonance in presence of wind (Bragg, 1913;Schaber et al, 1997); 3) Double bounce due to emerging vegetation or buildings from the inundated area (Franceschetti et al, 2002;Hong and Wdowinski, 2014;van Zyl et al, 1987;Hajnsek et al, 2009); 4) Dry and smooth bare soil exhibiting backscatter similar to that of water surfaces (O'Grady et al, 2011); 5) Vegetation masking part of the flood; 6) Soil moisture content increasing radar backscattering and limiting flood detection in mixed pixel (Jackson et al, 1996;Paloscia et al, 2013;Quesney et al, 2000;Shoshany et al, 2000;Wagner et al, 1999); and 7) User-dependence of the parameters chosen to produce the map (Martinis et al, 2009).…”

Section: Problem Formulationmentioning

confidence: 99%

Big Data Processing and Analysis Using Multi-Temporal Sentinel 1 Data to Manage Floods in North of Morocco

Lahsaini

Tabyaoui

Hammichi

2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

Abstract. Floods are the natural hazards that produce the highest number of casualties and material damage in the Western Mediterranean, especially in Morocco. An improvement in flood risk assessment and study of a possible increase in flooding occurrence are therefore needed. Earth Observation big data such as the ones acquired by the Copernicus programme are providing unprecedented opportunities to detect changes and assess economic impacts in case of disasters. This article present the different results obtained by the multi-temporal methods using the Synthetic Aperture Radar images. The spaceborne Synthetic Aperture Radar (SAR) systems are suitable tools for flood mapping thanks to their daytime and nighttime and almost all-weather imaging capability, in addition to their sensitivity to surface roughness and to Flood monitoring. The method has been developed to exploit Sentinel-1 data. It has been tested for the 2018 flood of Tetouan (Morocco).

show abstract

Combining Time-Series Variation Modeling and Fuzzy Spatiotemporal Feature Fusion: A Novel Approach for Unsupervised Flood Mapping Using Dual-Polarized Sentinel-1 SAR Images

Li,

Liu,

Liu

et al. 2023

IEEE Trans. Geosci. Remote Sensing

View full text Add to dashboard Cite

Precipitation signature on side-looking aperture radar imaging: Sensitivity analysis to surface effects at C, X and Ku band

Cited by 4 publications

References 14 publications

Sea Surface Current Estimation Using Airborne Circular Scanning SAR with a Medium Grazing Angle

Sea Surface Current Estimation Using Airborne Circular Scanning SAR with a Medium Grazing Angle

Big Data Processing and Analysis Using Multi-Temporal Sentinel 1 Data to Manage Floods in North of Morocco

Combining Time-Series Variation Modeling and Fuzzy Spatiotemporal Feature Fusion: A Novel Approach for Unsupervised Flood Mapping Using Dual-Polarized Sentinel-1 SAR Images

Contact Info

Product

Resources

About