An Empirical Algorithm to Retrieve Significant Wave Height from Sentinel-1 Synthetic Aperture Radar Imagery Collected under Cyclonic Conditions

Shao, Weizeng; Hu, Yuan; Yang, Jingsong; Nunziata, Ferdinando; Sun, Jian; Li, Huan; Zuo, Juncheng

doi:10.3390/rs10091367

Cited by 21 publications

(21 citation statements)

References 45 publications

(61 reference statements)

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“…Data for new assessments could have been done every 6 days after that, providing four assessments over time before the the full analysis from optical images was available. Sentinel-1 data has also proved its use for weather-related parameters in relation to cyclones [15] as in the case of Idai in Beira.…”

Section: Introductionmentioning

confidence: 99%

Sentinel-1 Change Detection Analysis for Cyclone Damage Assessment in Urban Environments

et al. 2020

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For disaster emergency response, timely information is critical and satellite data is a potential source for such information. High-resolution optical satellite images are often the most informative, but these are only available on cloud-free days. For some extreme weather disasters, like cyclones, access to cloud-free images is unlikely for days both before and after the main impact. In this situation, Synthetic Aperture Radar (SAR) data is a unique first source of information, as it works irrespective of weather and sunlight conditions. This paper shows, in the context of the cyclone Idai that hit Mozambique in March 2019, that Change Detection between pairs of SAR data is a perfect match with weather data, and therefore captures impact from the severe cyclone. For emergency operations, the filtering of Change Detections by external data on the location of houses prior to an event allows assessment of the impact on houses as opposed to impact on the surrounding natural environment. The free availability of SAR data from Sentinel-1, with further automated processing of it, means that this analysis is a cost-effective and quick potential first indication of cyclone destruction.

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Section: Introductionmentioning

confidence: 99%

Sentinel-1 Change Detection Analysis for Cyclone Damage Assessment in Urban Environments

et al. 2020

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“…Satellite data used for real-time wave observations include altimeter data [16] and synthetic aperture radar (SAR) data [17]. Spaceborne SARs, such as the Chinese Gaofen-3 SAR, feature a large swath width (>500 km) and fine spatial resolution (e.g., 150 m), thereby enabling high-resolution monitoring of typhoon winds [17][18][19] and waves [20][21][22][23] on large spatial scales. However, SAR data are only acquired on demand and are therefore unavailable for long-term studies.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Typhoon-Induced Waves along Typhoon Tracks in the Western North Pacific Ocean, 1998–2017

Shao

Wei

et al. 2020

JMSE

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In this study, Version 5.16 of the WAVEWATCH-III (WW3) model is used to simulate parameters of typhoon-generated wave fields in the Western North Pacific Ocean during the period 1998–2017. From a database of more than 300 typhoons, typhoon tracks are partitioned into six groups by their direction of motion and longitude of recurvature track. For typhoons that recurve east of 140° E, or track toward mainland Asia, regions of high significant wave height (SWH) values are separated by a minimum in SWH near 30° N. Partitioning SWH into wind sea and swell components demonstrates that variations in typhoon tracks produce a much stronger signal in the wind sea component of the wave system. Empirical orthogonal function (EOF) analysis is used to compute the four leading modes of variation in average SWH simulated by the WW3 model. The first EOF mode contributes to 17.3% of the total variance; all other modes contribute less than 10%. The first EOF mode also oscillates on an approximately 1-year cycle during the period 1998–2017. Overall, typhoon-induced wave energy dominates north of 30° N. Temporal analysis of the leading principal component of SWH indicates that (a) the intensity of the wave pattern produced by westward-tracking typhoons decreased during the last 20 years, and (b) typhoons that recurve east of 140° E and those that track westward toward southeast Asia are largely responsible for the decadal variability of typhoon-induced wave distribution.

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“…Under such conditions, GMF algorithms cannot be applied to wind retrieval. Cross-polarization NRCS is useful for retrieving wind speed (Fois et al, 2015) and significant wave height (Shao et al, 2018b) in cyclones. Fois et al (2015) reported that future ocean scatterometry will take advantage of the cross-polarization backscattering signal to observe strong winds.…”

Section: Introductionmentioning

confidence: 99%

Semi-Empirical Algorithm for Wind Speed Retrieval from Gaofen-3 Quad-Polarization Strip Mode SAR Data

Zhu

Shao

Marino

et al. 2019

J. Ocean Univ. China

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Synthetic aperture radar (SAR) is a suitable tool to obtain reliable wind retrievals with high spatial resolution. The geophysical model function (GMF), which is widely employed for wind speed retrieval from SAR data, describes the relationship between the SAR normalized radar cross-section (NRCS) at the copolarization channel (verticalvertical and horizontalhorizontal) and a wind vector. SAR-measured NRCS at cross-polarization channels (horizontalvertical and verticalhorizontal) correlates with wind speed. In this study, a semi-empirical algorithm is presented to retrieve wind speed from the noisy Chinese Gaofen-3 (GF-3) SAR data with noise-equivalent sigma zero correction using an empirical function. GF-3 SAR can acquire data in a quad-polarization strip mode, which includes cross-polarization channels. The semi-empirical algorithm is tuned using acquisitions collocated with winds from the European Center for Medium-Range Weather Forecasts. In particular, the proposed algorithm includes the dependences of wind speed and incidence angle on cross-polarized NRCS. The accuracy of SAR-derived wind speed is around 2.10 m/s root mean square error, which is validated against measurements from the Advanced Scatterometer onboard the Metop-A/B and the buoys from the National Data Buoy Center of the National Oceanic and Atmospheric Administration. The results obtained by the proposed algorithm considering the incidence angle in a GMF are relatively more accurate than those achieved by other algorithms. This work provides an alternative method to generate operational wind products for GF-3 SAR without relying on ancillary data for wind direction.

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An Empirical Algorithm to Retrieve Significant Wave Height from Sentinel-1 Synthetic Aperture Radar Imagery Collected under Cyclonic Conditions

Cited by 21 publications

References 45 publications

Sentinel-1 Change Detection Analysis for Cyclone Damage Assessment in Urban Environments

Sentinel-1 Change Detection Analysis for Cyclone Damage Assessment in Urban Environments

Analysis of Typhoon-Induced Waves along Typhoon Tracks in the Western North Pacific Ocean, 1998–2017

Semi-Empirical Algorithm for Wind Speed Retrieval from Gaofen-3 Quad-Polarization Strip Mode SAR Data

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