Copernicus Sentinel-1 Constellation Mission Operations Status

Potin, Pierre; Rosich, Betlem; Miranda, Nuno; Grimont, Patrick; Shurmer, Ian; O'Connell, Alistair; Krassenburg, Mike; Gratadour, Jean-Baptiste

doi:10.1109/igarss.2019.8898949

Cited by 28 publications

(21 citation statements)

References 5 publications

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“…Densely vegetated areas, including large portions of Japan, suffer from incoherence in C-band data, even with the short temporal baselines of Sentinel-1, compared to earlier radar satellites (see Section 3). In this study, the minimum acquisition interval is 12 days versus 6 days for Sentinel-1 across Europe [12]. Quite a few of the 12-day interferograms retain sufficient coherence over the frame, whereas most of the 24-day and longer interferograms lose coherence in the vegetated areas ( Figure S13).…”

Section: Limitationsmentioning

confidence: 90%

LiCSBAS: An Open-Source InSAR Time Series Analysis Package Integrated with the LiCSAR Automated Sentinel-1 InSAR Processor

et al. 2020

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For the past five years, the 2-satellite Sentinel-1 constellation has provided abundant and useful Synthetic Aperture Radar (SAR) data, which have the potential to reveal global ground surface deformation at high spatial and temporal resolutions. However, for most users, fully exploiting the large amount of associated data is challenging, especially over wide areas. To help address this challenge, we have developed LiCSBAS, an open-source SAR interferometry (InSAR) time series analysis package that integrates with the automated Sentinel-1 InSAR processor (LiCSAR). LiCSBAS utilizes freely available LiCSAR products, and users can save processing time and disk space while obtaining the results of InSAR time series analysis. In the LiCSBAS processing scheme, interferograms with many unwrapping errors are automatically identified by loop closure and removed. Reliable time series and velocities are derived with the aid of masking using several noise indices. The easy implementation of atmospheric corrections to reduce noise is achieved with the Generic Atmospheric Correction Online Service for InSAR (GACOS). Using case studies in southern Tohoku and the Echigo Plain, Japan, we demonstrate that LiCSBAS applied to LiCSAR products can detect both large-scale (>100 km) and localized (~km) relative displacements with an accuracy of <1 cm/epoch and ~2 mm/yr. We detect displacements with different temporal characteristics, including linear, periodic, and episodic, in Niigata, Ojiya, and Sanjo City, respectively. LiCSBAS and LiCSAR products facilitate greater exploitation of globally available and abundant SAR datasets and enhance their applications for scientific research and societal benefit.

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Section: Limitationsmentioning

confidence: 90%

LiCSBAS: An Open-Source InSAR Time Series Analysis Package Integrated with the LiCSAR Automated Sentinel-1 InSAR Processor

et al. 2020

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“…The C-band Sentinel-1 constellation launched by the European Space Agency (ESA) in 2014 and 2016 has been able to provide frequent and abundant data globally and freely (Potin et al 2019). Several public nationwide deformation monitoring services using Sentinel-1 data are in operation or planned in Denmark, Germany, Italy, the Netherlands, and Norway (Crosetto et al 2020), as well as commercial services for Denmark, Japan, France, and California in the USA (Bischoff et al 2020).…”

Section: Introductionmentioning

confidence: 99%

Nationwide urban ground deformation monitoring in Japan using Sentinel-1 LiCSAR products and LiCSBAS

Morishita

2021

Prog Earth Planet Sci

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Ground subsidence in urban areas is a significant problem because it increases flood risk, damages buildings and infrastructure, and results in economic loss. Continual monitoring of ground deformation is important for early detection, mechanism understanding, countermeasure implementation, and deformation prediction. The Sentinel-1 satellite constellation has globally and freely provided frequent and abundant SAR data and enabled nationwide deformation monitoring through InSAR time series analysis. LiCSAR, an automatic Sentinel-1 interferometric processing system, has produced abundant interferograms with global coverage, and the products are freely accessible and downloadable through a web portal. LiCSBAS, an open source InSAR time series analysis package integrated with LiCSAR, enables users to obtain the deformation time series easily and quickly. In this study, spatially and temporally detailed deformation time series and velocities from the LiCSAR products using LiCSBAS for 73 major urban areas in Japan during 2014–2020 were derived. All LiCSBAS processing was automatically performed using predefined parameters. Many deformation signals with various temporal and spatial features, such as linear subsidence in Hirosaki, Kujyukuri, Niigata, and Kanazawa, episodic subsidence in Sanjo, annual vertical fluctuation in Hirosaki, Yamagata, Yonezawa, Ojiya, and Nogi, and linear uplift in Chofu were detected. Unknown small nonlinear uplift signals were found in Nara and Osaka in 2018. Complex postseismic deformations from the 2016 Kumamoto earthquake were also revealed. All the deformation data obtained in this study are available on an open repository and are expected to be used for further research, investigation, or interpretation. This nationwide monitoring approach using the LiCSAR products and LiCSBAS is easy to implement and applicable to other areas worldwide.

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“…The successful launch of the European Space Agency Sentinel-1A satellite in April 2014, presented a new era of high-resolution SAR data for the scientific community. With Sentinel-1B launched in April 2016, the twin satellites provide high spatial resolution SAR images with an approximately 6-day revisit frequency [54]. As a new addition to the catalog of SAR observation platforms, application and performance of Sentinel-1A and 1B for soil moisture retrieval requires ongoing examination and assessment, particularly over vegetated surfaces and agricultural regions, where the high-resolution features of the sensors can be best utilized.…”

Section: Introductionmentioning

confidence: 99%

Retrieval of High-Resolution Soil Moisture through Combination of Sentinel-1 and Sentinel-2 Data

McCabe

2020

Remote Sensing

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Estimating soil moisture based on synthetic aperture radar (SAR) data remains challenging due to the influences of vegetation and surface roughness. Here we present an algorithm that simultaneously retrieves soil moisture, surface roughness and vegetation water content by jointly using high-resolution Sentinel-1 SAR and Sentinel-2 multispectral imagery, with an application directed towards the provision of information at the precision agricultural scale. Sentinel-2-derived vegetation water indices are investigated and used to quantify the backscatter resulting from the vegetation canopy. The proposed algorithm then inverts the water cloud model to simultaneously estimate soil moisture and surface roughness by minimizing a cost function constructed by model simulations and SAR observations. To examine the performance of VV- and VH-polarized backscatters on soil moisture retrievals, three retrieval schemes are explored: a single channel algorithm using VV (SCA-VV) and VH (SCA-VH) polarizations and a dual channel algorithm using both VV and VH polarizations (DCA-VVVH). An evaluation of the approach using a combination of a cosmic-ray soil moisture observing system (COSMOS) and Soil Climate Analysis Network measurements over Nebraska shows that the SCA-VV scheme yields good agreement at both the COSMOS footprint and single-site scales. The features of the algorithms that have the most impact on the retrieval accuracy include the vegetation water content estimation scheme, parameters of the water cloud model and the specification of initial ranges of soil moisture and roughness, all of which are comprehensively analyzed and discussed. Through careful consideration and selection of these factors, we demonstrate that the proposed SCA-VV approach can provide reasonable soil moisture retrievals, with RMSE ranging from 0.039 to 0.078 m3/m3 and R2 ranging from 0.472 to 0.665, highlighting the utility of SAR for application at the precision agricultural scale.

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Copernicus Sentinel-1 Constellation Mission Operations Status

Cited by 28 publications

References 5 publications

LiCSBAS: An Open-Source InSAR Time Series Analysis Package Integrated with the LiCSAR Automated Sentinel-1 InSAR Processor

LiCSBAS: An Open-Source InSAR Time Series Analysis Package Integrated with the LiCSAR Automated Sentinel-1 InSAR Processor

Nationwide urban ground deformation monitoring in Japan using Sentinel-1 LiCSAR products and LiCSBAS

Retrieval of High-Resolution Soil Moisture through Combination of Sentinel-1 and Sentinel-2 Data

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