Ocean color measurements with the Operational Land Imager on Landsat-8: implementation and evaluation in SeaDAS

Franz, Bryan A.; Bailey, Sean W.; Kuring, Norman; Werdell, P. Jeremy

doi:10.1117/1.jrs.9.096070

Cited by 133 publications

(105 citation statements)

References 42 publications

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“…The SWIR-based atmospheric correction method has been proven to be reliable and integrated into SEADAS for the operational product generations over turbid waters from MODIS images [57,58]. Recently, it is also modified and successfully applied to Landsat 8 OLI, a precursor of Sentinel 2 MSI [28,59,60]. Although the Sentinel 2 MSI SWIR bands is about one third of the Landsat 8 OLI SWIR bands in terms of SNR specification, the SNR can be improved through average filtering [44].…”

Section: Discussionmentioning

confidence: 99%

Application of Sentinel 2 MSI Images to Retrieve Suspended Particulate Matter Concentrations in Poyang Lake

et al. 2017

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Suspended particulate matter (SPM) is one of the dominant water constituents in inland and coastal waters, and SPM concnetration (C SPM ) is a key parameter describing water quality. This study, using in-situ spectral and C SPM measurements as well as Sentinel 2 Multispectral Imager (MSI) images, aimed to develop C SPM retrieval models and further to estimate the C SPM values of Poyang Lake, China. Sixty-eight in-situ hyperspectral measurements and relative spectral response function were applied to simulate Sentinel 2 MIS spectra. Thirty-four samples were used to calibrate and the left samples were used to validate C SPM retrieval models, respectively. The developed models were then applied to two Sentinel 2 MSI images captured in wet and dry seasons, and the derived C SPM values were compared with those derived from MODIS B1 (λ = 645 nm). Results showed that the Sentinel 2 MSI B4-B8b models achieved acceptable to high fitting accuracies, which explained 81-93% of the variation of C SPM . The validation results also showed the reliability of these six models, and the estimated C SPM explained 77-93% of the variation of measured C SPM with the mean absolute percentage error (MAPE) ranging from 36.87% to 21.54%. Among those, a model based on B7 (λ = 783 nm) appeared to be the most accurate one. The Sentinel 2 MSI-derived C SPM values were generally consistent in spatial distribution and magnitude with those derived from MODIS. The C SPM derived from Sentinel 2 MSI B7 showed the highest consistency with MODIS on 15 August 2016, while the Sentinel 2 MSI B4 (λ = 665 nm) produced the highest consistency with MODIS on 2 April 2017. Overall, this study demonstrated the applicability of Sentinel 2 MSI for C SPM retrieval in Poyang Lake, and the Sentinel 2 MSI B4 and B7 are recommended for low and high loadings of SPM, respectively.

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Section: Discussionmentioning

confidence: 99%

Application of Sentinel 2 MSI Images to Retrieve Suspended Particulate Matter Concentrations in Poyang Lake

et al. 2017

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“…The RSR curves in the visible and NIR bands are shown as dashed lines in Figure 2. Although L8/OLI is not designed for ocean monitoring, its advantages of high spatial resolution and the increased number of bands, combined with its improved signal-tonoise ratio and data quality, make it increasingly used in ocean color remote sensing research and especially in estuarine and coastal research [26][27][28][29][30][31][32][33].…”

Section: Satellite Imagesmentioning

confidence: 99%

Fusion of Landsat-8/OLI and GOCI Data for Hourly Mapping of Suspended Particulate Matter at High Spatial Resolution: A Case Study in the Yangtze (Changjiang) Estuary

2018

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Suspended particulate matter (SPM) concentrations ([SPM]) in the Yangtze estuary, which has third-order bifurcations and four outlets, exhibit large spatial and temporal variations. Studying the characteristics of these variations in [SPM] is important for understanding sediment transport and pollutant diffusion in the estuary as well as for the construction of port and estuarine engineering structures. The 1-h revisit frequency of the Geostationary Ocean Color Imager (GOCI) sensor and the 30-m spatial resolution of the Landsat 8 Operational Land Imager (L8/OLI) provide a new opportunity to study the large spatial and temporal variations in the [SPM] in the Yangtze estuary. In this study, [SPM] images with a temporal resolution of 1 h and a spatial resolution of 30 m are generated through the product-level fusion of [SPM] data derived from L8/OLI and GOCI images using the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM). The results show that the details and accuracy of the spatial and temporal variations are maintained well in the [SPM] images that are predicted based on the fused images. Compared to the [SPM] observations at fixed field stations, the mean relative error (MRE) of the predicted SPM is 17.7%, which is lower than that of the GOCI-derived [SPM] (27.5%). In addition, thanks to the derived high-resolution [SPM] with high spatiotemporal dynamic changes, both natural phenomena (dynamic variation of the maximum turbid zone) and human engineering changes leading to the dynamic variability of SPM in the channel are observed.

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“…L8 aims to provide data continuity to the global NASA Landsat Earth observation program that started in the 1970s. The OLI sensor has been evaluated to be suitable for the assessment of water quality and water constituents in many water bodies such as lakes, estuaries, rivers and coastal zones Vanhellemont & Ruddick, 2014;Brando et al, 2015;Franz et al, 2015;Lobo et al, 2015;Slonecker et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Mapping phytoplankton blooms in deep subalpine lakes from Sentinel-2A and Landsat-8

et al. 2018

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For effective lakes' management, highfrequent water quality data on a synoptic scale are essential. The aim of this study is to test the suitability of the latest generation of satellite sensors to provide information on lake water quality parameters for the five largest Italian subalpine lakes. In situ data of phytoplankton composition, chlorophyll-a (chl-a) concentration and water reflectance were used in synergy with satellite observations to map some algal blooms in 2016. Chl-a concentration maps were derived from satellite data by applying a bio-optical model to satellite data, previously corrected for atmospheric effects. Results were compared with in situ data, showing good agreement. The shape and magnitude of water reflectance from different satellite data were consistent. Output chl-a concentration maps, show the distribution within each lake during blooming events, suggesting a synoptic view is required for these events monitoring. Maps show the dynamic of bloom events with concentration increasing from 2 up to 7 mg m -3 and dropping again to initial value in less than 20 days. Latest generation sensors were shown to be valuable tools for lakes monitoring, thanks to frequent, free of charge data availability over long time periods.

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Ocean color measurements with the Operational Land Imager on Landsat-8: implementation and evaluation in SeaDAS

Cited by 133 publications

References 42 publications

Application of Sentinel 2 MSI Images to Retrieve Suspended Particulate Matter Concentrations in Poyang Lake

Application of Sentinel 2 MSI Images to Retrieve Suspended Particulate Matter Concentrations in Poyang Lake

Fusion of Landsat-8/OLI and GOCI Data for Hourly Mapping of Suspended Particulate Matter at High Spatial Resolution: A Case Study in the Yangtze (Changjiang) Estuary

Mapping phytoplankton blooms in deep subalpine lakes from Sentinel-2A and Landsat-8

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