Combining Landsat-8 and Sentinel-2 to investigate seasonal changes of suspended particulate matter off the abandoned distributary mouths of Yellow River Delta

2021 ◽  
Vol 441 ◽  
pp. 106622
Author(s):  
Peng Li ◽  
Shenliang Chen ◽  
Hongyu Ji ◽  
Yinghai Ke ◽  
Yutao Fu
Keyword(s):  
Particulate Matter ◽  
Suspended Particulate Matter ◽  
Seasonal Changes ◽  
Yellow River ◽  
Yellow River Delta ◽  
River Delta ◽  
Landsat 8 ◽  
Suspended Particulate ◽  
Sentinel 2

Analyzing the Distribution and Variation of Suspended Particulate Matter in the Yellow River Estuary (YRE) using Landsat 8 OLI

2020 ◽  
Author(s):  
Jin Li ◽  
Yanling Hao ◽  
Zhuangzhuang Zhang ◽  
Zhipeng Li ◽  
Ruihong Yu ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Suspended Particulate Matter ◽  
Yellow River ◽  
River Estuary ◽  
Coastal Areas ◽  
Yellow River Estuary ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Suspended Particulate ◽  
Significant Difference

Abstract Yellow River Estuary (YRE) as well as its adjacent coastal areas are famous for its high concentration of Suspended Particulate Matter (SPM). The distribution of SPM and its variations in the estuary area promoted the carbon, oxygen and nutrient cycles in coastal areas and nearby sea areas. This study took advantage of Landsat 8 Operational Land Imager (Landsat 8 OLI) data to estimate SPM in the YRE from 2013 to 2019. Remote sensing reflectance (R rs ) measured by Landsat 8 OLI has been proved to be effective through cross-validate with Geostationary Ocean Color Imager (GOCI). A simple empirical alogrithm (NIR band ratio green band and add red band) was developed to map the SPM distribution and concentration, with the APD 33.12% and R 2 0.93 based on in-situ data. Annual average distribution of SPM shows that highy turbid areas with SPM greater than 10 3 mg/L are mostly found surrounding the estuary of Yellow River, in the northwest part of the Laizhou Bay and south part of Bohai bay. High variations of SPM distributions are consistent with high SPM, and vice versa. The influences of river runoff is mainly concentrated in the estuary area, and outside 4.5 km the variability of SPM effected by river discharge is not ovbious. Significant difference is observed in seasonal SPM distribution. Higher SPM in winter is observed both in range and intensity compared to summer. Significant seasonal variations are mainly controlled by sediment resuspension processes driven by wind-wave forces. The results of this study indicate that Landsat8 OLI is an effective mean to retrieve SPM in YRE and its adjcent areas.

Using Landsat 8 data to estimate suspended particulate matter in the Yellow River estuary

2017 ◽  
Vol 122 (1) ◽  
pp. 276-290 ◽  
Author(s):  
Zhongfeng Qiu ◽  
Cong Xiao ◽  
William Perrie ◽  
Deyong Sun ◽  
Shengqiang Wang ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Suspended Particulate Matter ◽  
Yellow River ◽  
River Estuary ◽  
Yellow River Estuary ◽  
The Yellow River ◽  
Landsat 8 ◽  
Suspended Particulate

scholarly journals Consistency of Suspended Particulate Matter Concentration in Turbid Water Retrieved from Sentinel-2 MSI and Landsat-8 OLI Sensors

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1662
Author(s):  
Hanghang Wang ◽  
Jie Wang ◽  
Yuhuan Cui ◽  
Shijiang Yan
Keyword(s):  
Particulate Matter ◽  
Suspended Particulate Matter ◽  
Atmospheric Correction ◽  
Solar Spectrum ◽  
Landsat 8 ◽  
Suspended Particulate Matter Concentration ◽  
Retrieval Model ◽  
Suspended Particulate ◽  
Spm Concentration ◽  
Sentinel 2

Research on the consistency of suspended particulate matter (SPM) concentration retrieved from multisource satellite sensors can serve as long-time monitoring of water quality. To explore the influence of the atmospheric correction (AC) algorithm and the retrieval model on the consistency of the SPM concentration values, Landsat 8 Operational Land Imager (OLI) and Sentinel 2 MultiSpectral Imager (MSI) images acquired on the same day are used to compare the remote sensing reflectance (Rrs) SPM retrieval values in two high-turbidity lakes. An SPM retrieval model for Shengjin Lake is established based on field measurements and applied to OLI and MSI images: two SPM concentration products are highly consistent (R2 = 0.93, Root Mean Squared Error (RMSE) = 20.67 mg/L, Mean Absolute Percentage Error (MAPE) = 6.59%), and the desired results are also obtained in Chaohu Lake. Among the four AC algorithms (Management Unit of the North Seas Mathematical Models (MUMM), Atmospheric Correction for OLI’lite’(ACOLITE), Second Simulation of Satellite Signal in the Solar Spectrum (6S), Landsat 8 Surface Reflectance Code & Sen2cor (LaSRC & Sen2cor)), the two Rrs products, as well as the final SPM concentration products retrieved from OLI and MSI images, have the best consistency when using the MUMM algorithm in SeaWIFS Data Analyst System (SeaDAS) software. The consistency of SPM concentration values retrieved from OLI and MSI images using the same model or same form of models is significantly better than that retrieved by applying the optimal models with different forms.

scholarly journals The Advantages of Landsat 8-OLI-Derived Suspended Particulate Matter Maps for Monitoring the Subtidal Extension of Amazonian Coastal Mud Banks (French Guiana)

2018 ◽  
Vol 10 (11) ◽  
pp. 1733 ◽  
Author(s):  
Noelia Abascal Zorrilla ◽  
Vincent Vantrepotte ◽  
Erwan Gensac ◽  
Nicolas Huybrechts ◽  
Antoine Gardel
Keyword(s):  
Particulate Matter ◽  
Suspended Particulate Matter ◽  
French Guiana ◽  
Landsat 8 ◽  
Migration Rates ◽  
Suspended Particulate ◽  
High Concentrations ◽  
Spm Concentration ◽  
And Migration ◽  
Comparison Of The Results

The coast of French Guiana is characterised by the northwestward migration of large mud banks alongshore and by high concentrations of suspended particulate matter (SPM) resulting from the strong influence of the Amazon River outflow. Surface OLI SPM concentration, linked to the footprint of the subtidal part of mud banks due to resuspension and migration processes, was used to develop a method to estimate the location of this footprint. A comparison of the results from this method with those obtained by locating the limit of the wave damping, which characterises muddy coasts, revealed good performance of the method based on recurring SPM values. The migration rates of the mud banks in French Guiana were calculated according to the delimitation of their subtidal parts, and showed slightly higher values (2.31 km/year) than suggested by earlier studies. In comparison with other methods, the migration rate estimated using the method proposed within the framework of this study takes into account the variability of the shape of the subtidal part for the first time. It was also shown that the mud banks existing on the coastal area of French Guiana present two different shapes. Our results clearly demonstrate the advantage of ocean colour data to describe mud banks according to their subtidal part, delimited using the assessment of SPM temporal variability.

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