Monitoring inland water via Sentinel satellite constellation: A review and perspective

ISPRS Journal of Photogrammetry and Remote Sensing, Journal Year: 2023, Volume and Issue: 204, P. 340 - 361

Published: Sept. 28, 2023

Language: Английский

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From natural to artificial cyanophages: Current progress and application prospects

Environmental Research, Journal Year: 2023, Volume and Issue: 223, P. 115428 - 115428

Published: Feb. 4, 2023

Language: Английский

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A New High-Resolution Remote Sensing Monitoring Method for Nutrients in Coastal Waters

IEEE Transactions on Geoscience and Remote Sensing, Journal Year: 2023, Volume and Issue: 61, P. 1 - 15

Published: Jan. 1, 2023

Mariculture is an important offshore economic activity, and excessive farming can lead to the deterioration of sea ecology. The concentration nutrients (mainly DIN (dissolved inorganic nitrogen) PO4 (orthophosphate-phosphorous)) main factor characterizing health condition farmed seas. Conventional field monitoring methods are spatiotemporally limited, remote sensing technology has advantages high spatial coverage long time series monitoring. Thus, Sentinel-3 reflectance data in situ measured for waters Wenzhou were matched simultaneously. Then, dataset between Sentinel-2 band obtained through spectral correspondence conversion Sentinel-3, a machine learning algorithm was used build inversion model with independent validation process. correlations nutrients, area rafts precipitation assessed, strong positive correlation found rafts, weak negative former precipitation.

Language: Английский

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Monitoring phycocyanin concentrations in high-latitude inland lakes using Sentinel-3 OLCI data: The case of Lake Hulun, China

Ecological Indicators, Journal Year: 2023, Volume and Issue: 155, P. 110960 - 110960

Published: Sept. 26, 2023

With the intensification of global warming, eutrophication in lakes at high latitudes China has become increasingly severe, with harm blue-green algae blooms also on rise. Therefore, it is urgent to conduct research water quality latitudes. In this study, taking Lake Hulun as an example, a phycocyanin (PC) inversion model applicable Sentinel-3 OLCI data was constructed and applied dataset from 2016 2022 analyze spatiotemporal variation characteristics PC concentration. The driving mechanism climate factors concentration explored, correlation between Cyanobacterial (CBs) outbreak analyzed. Results showed that based XGBoost (XGB) highest accuracy (R2 = 0.91, RMSE 76.76 μg/L, rRMSE 0.54). Monthly average higher July (44.52±64.85 μg/L) lower October (5.04±1.81 μg/L). From 2022, annual (38.82±63.34 than other years, while 2020 (4.60±1.76 lower. Temperature main impacting factor consistency proportion CBs area. summary, using imagery for long-term remote sensing monitoring pattern changes Hulun, analyzing its changing patterns, great significance early warning CBs.

Language: Английский

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Comprehensive meteorological factors analysis and lag correlation study for cyanobacterial blooms in shallow plateau lake

Ecological Indicators, Journal Year: 2023, Volume and Issue: 153, P. 110394 - 110394

Published: May 25, 2023

Cyanobacterial blooms (CBs) are a growing concern for shallow plateau lakes, and numerous studies have investigated the relationship between CBs meteorological factors. However, these typically lacked comprehensive analyses neglected impact of lag effects. This study employed Landsat satellite imagery to extract information from Xingyun Lake 1990 2019 conducted correlation analysis factors ranging 1 30 days with 1-day step CBs. The result show that Sunshine Duration displayed negative at an 8-day lag, but when was <6 h, it exhibited positive lag. And daytime precipitation had more substantial link than nighttime 13 days. aforementioned conclusions deepen our comprehension forces drive cyanobacterial in lakes. Moreover, maximum minimum wind velocities were negatively positively associated lags 20 29 days, respectively. In addition, relative humidity atmospheric pressure 13–19 3 after their onset, air temperature weak. Our research emphasizes significance incorporating delayed effects refined accurate bloom forecasting.

Language: Английский

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Early Warning of Red Tide of Phaeocystis globosa Based on Phycocyanin Concentration Retrieval in Qinzhou Bay, China

Applied Sciences, Journal Year: 2023, Volume and Issue: 13(20), P. 11449 - 11449

Published: Oct. 19, 2023

Phaeocystis globose (P. glo) are the most frequent harmful algae responsible for red tides in Qinzhou Bay, Guangxi. They pose a significant threat to coastal marine ecosystem, making it essential develop an efficient indicator method tailored P. glo outbreaks. In remote sensing water quality monitoring, there is strong correlation between and cyanobacteria, with phycocyanin (PC) serving as of cyanobacterial biomass. Consequently, existing research has predominantly focused on monitoring medium high PC concentrations. However, still challenging monitor low This paper introduced BP neural network (BPNN) particle swarm optimization algorithm (PSO). It selects spectral bands indices sensitive concentrations constructs concentration retrieval model, combination meteorological factors, offering comprehensive exploration indicative role predicting tide outbreaks Bay. The results demonstrated that based backpropagation optimized by (PSO-BPNN), better performance (MAE = 0.469, RMSE 0.615). were mainly concentrated around 2~5 μg/L. During event, area undetectable (PC < 0.04 μg/L) increased 4.97 km2, regions below 0.9 μg/L experiencing exponential growth. Considering variations along we proposed straightforward early warning threshold tides: T 20 °C. method, from perspective, analyzes process outbreaks, simplifies provides reasonably accurate prediction risk disasters.

Language: Английский

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SVR model and OLCI images reveal a declining trend in phycocyanin levels in typical lakes across Northeast China

Ecological Informatics, Journal Year: 2024, Volume and Issue: unknown, P. 102965 - 102965

Published: Dec. 1, 2024

Language: Английский

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