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dc.contributor.authorQuang, Nguyen Hong
dc.contributor.authorNguyen, Minh Nguyen
dc.contributor.authorPaget, Matt
dc.contributor.authorAnstee, Janet
dc.contributor.authorViet, Nguyen Duc
dc.contributor.authorNones, Michael
dc.contributor.authorTuan, Vu Anh
dc.date.accessioned2022-09-28T10:52:22Z
dc.date.available2022-09-28T10:52:22Z
dc.date.issued2022-09-27
dc.identifier.citationRemote Sensingen_US
dc.identifier.otherDOI: 10.3390/rs14194822
dc.identifier.urihttps://dspace.igf.edu.pl/xmlui/handle/123456789/110
dc.description.abstractChlorophyll-a is one of the most important water quality parameters that can be observed by satellite imagery. It plays a significant function in the aquatic environments of rapidly developing coastal cities such as Ha Long City, Vietnam. Urban population growth, coal mining, and tourist activities have affected the water quality of Ha Long Bay. This work uses Sentinel-2/Multispectral Instrument (MSI) imagery data to a calibrated ocean chlorophyll 2-band (OC-2) model to retrieve chlorophyll-a (chl-a) concentration in the bay from 2019 to 2021. The variability of chlorophyll-a during seasons over the study area was inter-compared. The chlorophyll-a concentration was mapped by analyzing the time series of water cover on the Google Earth Engine platform. The results show that the OC-2 model was calibrated well to the conditions of the study areas. The calibrated model accuracy increased nearly double compared with the uncalibrated OC-2 model. The seasonal assessment of chl-a concentration showed that the phytoplankton (algae) developed well in cold weather during fall and winter. Spatially, algae grew densely inside and in the surroundings of aquaculture, urban, and tourist zones. In contrast, coal mining activities did not result in algae development. We recommend using the Sentinel-2 data for seawater quality monitoring and assessment. Future work might focus on model calibration with a longer time simulation and more in situ measured data. Moreover, manual atmospheric correction of optical remote sensing is crucial for coastal environmental studies.en_US
dc.language.isoenen_US
dc.publisherMDPIen_US
dc.relation.ispartofseries14(19);4822
dc.subjectanthropogenic impacts; chlorophyll-a; Ha Long Bay; optical remote sensing; seawater; water qualityen_US
dc.titleAssessment of Human-Induced Effects on Sea/Brackish Water Chlorophyll-a Concentration in Ha Long Bay of Vietnam with Google Earth Engineen_US
dc.typeArticleen_US


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