Effect of Faraday Rotation on L-Band NRCS and Wind Speed Detection

Isoguchi, Osamu; Ishizuka, Kenta; Tadono, Takeo; Motohka, Takeshi; Shimada, Masanobu

doi:10.1109/igarss.2018.8517530

Cited by 1 publication

(2 citation statements)

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“…In case of ALOS-2 PALSAR-2, the estimated wind speed also revealed a negative bias of about −0.60 m s −1 . This implies that ALOS-2 PALSAR-2 using L-band GMF 2009 was significantly negative bias with underestimation as compared with buoy data (Isoguchi et al 2018). One of other reason of the underestimation herein might be induced by a small number of matchup or characteristics of L-band GMF 2009 as shown in Figure 5.…”

Section: Accuracy Of L-band Sar Wind Speedmentioning

confidence: 79%

“…Oceanic observations have been applied for detection of monitoring of sea ice, ship detection, oceanic currents, marine environments, and so on (Kudryavtsev et al 2015;Dabboor et al 2017;Motohka, Kankaku, and Suzuki 2017;Johansson et al 2018;Park et al 2018). In the studies of sea surface winds, the ALOS-2 PALSAR-2 data were used, the accuracy of wind speeds was evaluated by comparing with the ASCAT data and the effect of Faraday rotation on sea surface wind retrieval was investigated Isoguchi et al 2018). However, the factors, affecting the sea surface wind errors of ALOS-2 PALSAR-2, have not been previously discussed in detail, especially for the Stripmap mode.…”

Section: Introductionmentioning

confidence: 99%

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Characteristics of environmental factors contributing to ALOS-2 PALSAR wind speed errors

Jang

Park

Isoguchi

2020

International Journal of Remote Sensing

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Environmental factors affecting the errors in wind speed estimates were investigated using the Advanced Land Observing Satellite-2 Phased Array L-band Synthetic Aperture Radar-2 (ALOS-2 PALSAR-2) data for the period from 1 November 2014 to 30 November 2017. In total, 45 ALOS-2 PALSAR-2 Stripmap Fine mode images with horizontal dual-polarization were collected, and the wind speeds were calculated using the L-band Geophysical Model Function (GMF) in 2009. Validation of the SAR-derived wind speeds to in-situ wind, converted to the 10-m neutral wind, resulted in the root-meansquare error of 2.11 ms −1 , bias error of −1.16 m s −1 , and standard deviation of 1.78 m s −1. Investigation of the wind speed errors revealed the contributions of diverse oceanic environmental factors such as the ship and its side-lobe effect that is negligible at a distance of more than 200% of the ship radius, v-shaped ship wakes are accompanied by the Kelvin waves and turbulent wakes caused by ship movement. The sand ridge, formed due to the interaction of shallow bathymetry and tidal currents, contributed to the wind speed errors of more than 50%. The internal waves caused prominent wind speed errors of more than 100%. The atmospheric gravity waves, generated by the orographic effect, caused wind speed fluctuations up to 13.4 m s −1. This study addressed the importance of understanding the factors that affect the normalized radar crosssection of the SAR image in order to correctly retrieve wind speeds from SAR data.

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Section: Accuracy Of L-band Sar Wind Speedmentioning

confidence: 79%