A semianalytical algorithm for estimating particulate composition in inland waters based on Sentinel-3 OLCI images

Xu, Jiafeng; Zhao, Ying; Lyu, Heng; Liu, Huaiqing; Dong, Xinhua; Li, Yunmei; Cao, Kai; Xu, Jie; Li, Yangyang; Wang, Huaijing; Guo, Honglei

doi:10.1016/j.jhydrol.2022.127617

Cited by 8 publications

(1 citation statement)

References 74 publications

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“…The Sentinel-3 satellite monitors the global ocean and land in real time. Among them, sea temperature, sea color, and sea level height data can be used to monitor climate change, ocean pollution, biological productivity [42][43][44], terrestrial forest fires, terrestrial vegetation health, and water levels of lakes and rivers [45][46][47]. The satellite has an orbital altitude of 800-830 km and a revisit period of less than 2 days.…”

Section: Images and Preprocessingmentioning

confidence: 99%

Reconstruction of Sentinel Images for Suspended Particulate Matter Monitoring in Arid Regions

et al. 2023

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Missing data is a common issue in remote sensing. Data reconstruction through multiple satellite data sources has become one of the most powerful ways to solve this issue. Continuous monitoring of suspended particulate matter (SPM) in arid lakes is vital for water quality solutions. Therefore, this research aimed to develop and evaluate the performance of two image reconstruction strategies, spatio-temporal fusion reflectance image inversion SPM and SPM spatio-temporal fusion, based on the measured SPM concentration data with Sentinel-2 and Sentinel-3. The results show that (1) ESTARFM (Enhanced Spatio-temporal Adaptive Reflection Fusion Model) performed better than FSDAF (Flexible Spatio-temporal Data Fusion) in the fusion image generation, particularly the red band, followed by the blue, green, and NIR (near-infrared) bands. (2) A single-band linear and non-linear regression model was constructed based on Sentinel-2 and Sentinel-3. Analysis of the accuracy and stability of the model led us to the conclusion that the red band model performs well, is fast to model, and has a wide range of applications (Sentinel-2, Sentinel-3, and fused high-accuracy images). (3) By comparing the two data reconstruction strategies of spatio-temporal fused image inversion SPM and spatio-temporal fused SPM concentration map, we found that the fused SPM concentration map is more effective and more stable when applied to multiple fused images. The findings can provide an important scientific reference value for further expanding the inversion research of other water quality parameters in the future and provide a theoretical basis as well as technical support for the scientific management of Ebinur Lake’s ecology and environment.

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Section: Images and Preprocessingmentioning

confidence: 99%

Reconstruction of Sentinel Images for Suspended Particulate Matter Monitoring in Arid Regions

et al. 2023

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Nanoparticles containing hazardous elements and the spatial optics of the Sentinel-3B OLCI satellite in Amazonian rivers: a potential tool to understand environmental impacts

Silva

Bodah

Lozano

et al. 2023

Environ Sci Pollut Res

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The Amazon River is the longest river in the world. The Tapajós River is a tributary to the Amazon. At their junction, a marked decrease in water quality is evident from negative impacts from the constant activity of clandestine gold mining in the Tapajós River watershed. The accumulation of hazardous elements (HEs), capable of compromising environmental quality across large regions is evident in the waters of the Tapajós. Sentinel-3B OLCI (Ocean Land Color Instrument) Level-2 satellite imagery with Water Full Resolution (WFR) of 300 m was utilized to detect the highest potential for the absorption coefficient of detritus and gelbstoff in 443 m −1 (ADG443_NN), chlorophyll-a (CHL_NN) and total suspended matter concentration (TSM_NN), at 25 points in the Amazon and Tapajós rivers (in 2019 and 2021). Physical samples of riverbed sediment collected in the field at the same locations were analyzed for NPs and ultra-fine particles to verify the geospatial findings. The riverbed sediment samples collected in the field were studied by Transmission electron microscopy (TEM) and scanning transmission electron microscopy (STEM), with selected area electron diffraction (SAED), following laboratory analytical procedures. The Sentinel-3B OLCI images, based on the Neural Network (NN) were calibrated by the European Space Agency (ESA), with a standard average normalization of 0.83 µg/mg, containing a maximum error of 6.62% applied to the sampled points. The analysis of the riverbed sediment samples revealed the presence of the following hazardous elements: As, Hg, La, Ce, Th, Pb, Pd, among several others. The Amazon River has significant potential to transport ADG443_NN (55.475 m −1 ) and TSM_NN (70.787 gm −3 ) in sediments, with the possibility of negatively impacting marine biodiversity, in addition to being harmful to human health over very large regions.

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Long-term remote observations of particulate organic phosphorus concentration in eutrophic Lake Taihu based on a novel algorithm

et al. 2023

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A semianalytical algorithm for estimating particulate composition in inland waters based on Sentinel-3 OLCI images

Cited by 8 publications

References 74 publications

Reconstruction of Sentinel Images for Suspended Particulate Matter Monitoring in Arid Regions

Reconstruction of Sentinel Images for Suspended Particulate Matter Monitoring in Arid Regions

Nanoparticles containing hazardous elements and the spatial optics of the Sentinel-3B OLCI satellite in Amazonian rivers: a potential tool to understand environmental impacts

Long-term remote observations of particulate organic phosphorus concentration in eutrophic Lake Taihu based on a novel algorithm

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