Flattening Gamma: Radiometric Terrain Correction for SAR Imagery

Small, David

doi:10.1109/tgrs.2011.2120616

Cited by 401 publications

(318 citation statements)

References 13 publications

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“…Since a SAR image is a range-Doppler image, for each DEM cell, the corresponding coordinate in the range direction can be calculated through the slant range between the DEM cell and radar sensor, while the coordinate in the azimuth direction can be obtained by finding out the corresponding zero-Doppler frequency shift position. Details can be found in the papers by Loew and Mauser [16], Meier et al [15], and Small [17].…”

Section: Sar Geometric Terrain Correctionmentioning

confidence: 99%

“…Radar backscatter β is defined as the ratio of scattered power P S to the incident power P I [17]. For distributed targets, radar brightness β 0 is defined as averaged backscatter ratio per unit area in the image plane (i.e., the slant range plane) [31]; backscatter coefficient σ 0 is defined as averaged backscatter ratio per unit ground area.…”

Section: Sar Radiometric Terrain Correctionmentioning

confidence: 99%

“…For distributed targets, radar brightness β 0 is defined as averaged backscatter ratio per unit area in the image plane (i.e., the slant range plane) [31]; backscatter coefficient σ 0 is defined as averaged backscatter ratio per unit ground area. For flat areas, the backscatter coefficient σ 0 can be retrieved using [17] incident angle θ…”

Section: Sar Radiometric Terrain Correctionmentioning

confidence: 99%

“…For correction of geometric distortions, the traditional geometric correction method through polynomial transformation does not work in finding out the corresponding relationship of coordinates between the SAR image coordinates and the real world coordinates. According to [15][16][17], the range direction coordinate in SAR image is determined by the slant range, while the azimuth direction coordinate can be calculated by solving the zero-Doppler shift equation. Chen [18] adopted another geometric correction method using SAR simulation [19,20] and registration.…”

Section: Introductionmentioning

confidence: 99%

“…Tilley and Bonwit [26] and Bolter et al [27] proposed to normalize the brightness values of SAR image pixels in foreshortening and layover areas by dividing the value equally among all ground patches contributing to that particular SAR pixel. Small et al [17,28] proposed a correction method by normalizing the backscatter coefficient with the local illuminated area projected onto the plane perpendicular to the radar line of sight. For polarization distortion, researchers proposed to perform the correction through polarization orientation angle shift compensation [12][13][14]29].…”

Section: Introductionmentioning

confidence: 99%

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An Improved Sar Radiometric Terrain Correction Method and Its Application in Polarimetric Sar Terrain Effect Reduction

Chen¹

2013

PIER B

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Abstract-A new SAR radiometric terrain correction method was proposed to reduce the terrain effects in sloped regions. Based on this method, a procedure for polarimetric SAR terrain effect reduction was proposed, including geometric correction, shadow detection, radiometric terrain correction, and polarization orientation angle shift compensation. Experiments using RADARSAT-2 polarimetric SAR data of the Three Gorges Area, China demonstrated the effectiveness of the proposed radiometric terrain correction method. Both visual and quantitative analyses showed that after the proposed radiometric terrain correction method was applied, the contrast between different slopes that caused by local incidence angle differences, foreshortening, and layover was significantly reduced. The difference of backscattering intensity on slopes facing the radar sensor and facing away from the sensor was reduced from 12.5 dB before radiometric correction to 1.3 dB. The overall accuracy of land use/land cover classification was improved by 11.2 percent using the terrain corrected polarimetric SAR data.

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Section: Sar Geometric Terrain Correctionmentioning

confidence: 99%

Section: Sar Radiometric Terrain Correctionmentioning

confidence: 99%

Section: Sar Radiometric Terrain Correctionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An Improved Sar Radiometric Terrain Correction Method and Its Application in Polarimetric Sar Terrain Effect Reduction

Chen¹

2013

PIER B

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Winter Sentinel‐1 Backscatter as a Predictor of Spring Arctic Sea Ice Melt Pond Fraction

Scharien

Segal

Nasonova

et al. 2017

Geophysical Research Letters

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Spring melt pond fraction (f p) has been shown to influence September sea ice extent and, with a growing need to improve melt pond physics in climate and forecast models, observations at large spatial scales are needed. We present a novel technique for estimating f p on sea ice at high spatial resolution from the Sentinel-1 satellite during the winter period leading up to spring melt. A strong correlation (r = À0.85) is found between winter radar backscatter and f p from first-year and multiyear sea ice data collected in the Canadian Arctic Archipelago (CAA) in 2015. Observations made in the CAA in 2016 are used to validate a f p retrieval algorithm, and a f p prediction for the CAA in 2017 is made. The method is effective using the horizontal transmit and receive polarization channel only and shows promise for providing seasonal, pan-Arctic, f p maps for improved understanding of melt pond distributions and forecast model skill. Plain Language Summary Recent and well-documented changes in Arctic sea ice have introduced the need for timely and accurate seasonal forecasts of ice conditions. Seasonal forecasts of ice conditions will reduce the risks to humans and help preserve the fragile Arctic ecosystem by preventing accidents and spills. Recent studies have shown a link between the amount of surface meltwater flooding that occurs on sea ice in the spring, termed melt pond fraction, and the extent of sea ice that remains at the end of summer. This link is due to the ability of surface meltwater to absorb more sunlight compared to bare ice and snow. This study provides a new way to estimate the amount of surface meltwater flooding expected to occur on the sea ice in spring, using satellite data collected during the winter period. The results presented here provide a key link between winter and late summer sea ice conditions that will enhance the ability of forecasters to make accurate seasonal predictions several months in advance of the active summer period.

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Vegetation Cartography from Sentinel‐1 Radar Images

Frison¹,

Lardeux²

2018

QGIS and Applications in Agriculture and Forest

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Flattening Gamma: Radiometric Terrain Correction for SAR Imagery

Cited by 401 publications

References 13 publications

An Improved Sar Radiometric Terrain Correction Method and Its Application in Polarimetric Sar Terrain Effect Reduction

An Improved Sar Radiometric Terrain Correction Method and Its Application in Polarimetric Sar Terrain Effect Reduction

Winter Sentinel‐1 Backscatter as a Predictor of Spring Arctic Sea Ice Melt Pond Fraction

Vegetation Cartography from Sentinel‐1 Radar Images

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