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dc.contributor.authorCasado, Monica Rivas*
dc.date.accessioned2021-02-11T21:16:31Z
dc.date.available2021-02-11T21:16:31Z
dc.date.issued2019*
dc.date.submitted2019-12-09 16:10:12*
dc.identifier42688*
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/54860
dc.description.abstractIn recent decades, there has been an increase in the development of strategies for water ecosystem mapping and monitoring. Overall, this is primarily due to legislative efforts to improve the quality of water bodies and oceans. Remote sensing has played a key role in the development of such approaches—from the use of drones for vegetation mapping to autonomous vessels for water quality monitoring. Within the specific context of vegetation characterization, the wide range of available observations—from satellite imagery to high-resolution drone aerial imagery—has enabled the development of monitoring and mapping strategies at multiple scales (e.g., micro- and mesoscales). This Special Issue, entitled “Novel Advances in Aquatic Vegetation Monitoring in Ocean, Lakes and Rivers”, collates recent advances in remote sensing-based methods applied to ocean, river, and lake vegetation characterization, including seaweed, kelp, submerged and emergent vegetation, and floating-leaf and free-floating plants. A total of six manuscripts have been compiled in this Special Issue, ranging from area mapping substrates in riverine environments to the identification of macroalgae in marine environments. The work presented leverages current state-of-the-art methods for aquatic vegetation monitoring and will spark further research within this field.*
dc.languageEnglish*
dc.subjectGE1-350*
dc.subjectQ1-390*
dc.subject.classificationthema EDItEUR::K Economics, Finance, Business and Management::KC Economics::KCV Economics of specific sectors::KCVG Environmental economicsen_US
dc.subject.otherbottom reflectance*
dc.subject.otheraquatic vegetation*
dc.subject.othernormalized difference vegetation index (NDVI)*
dc.subject.otherLake Ulansuhai*
dc.subject.otherconcave–convex decision function*
dc.subject.otherradiative transfer*
dc.subject.othermethodological comparison*
dc.subject.otherremote sensing extraction*
dc.subject.otherinvasive plants*
dc.subject.otherCAS S. alterniflora*
dc.subject.otherspectroscopy*
dc.subject.otherChina*
dc.subject.othernuclear power station*
dc.subject.otherfloating algae index (FAI)*
dc.subject.otherLandsat OLI*
dc.subject.otherSpartina alterniflora*
dc.subject.othersubstrate*
dc.subject.otherunmanned aerial vehicle*
dc.subject.otherLake Baikal*
dc.subject.otherreflectance*
dc.subject.other1st derivative*
dc.subject.otherseaweed*
dc.subject.otherremote sensing*
dc.subject.otherWorldView-2*
dc.subject.otherspecies discrimination*
dc.subject.otherWorldView-3*
dc.subject.otherwater-column correction*
dc.subject.otherSelenga River Delta*
dc.subject.othermacroalgae*
dc.subject.otherobject-based image analysis*
dc.subject.otherseaweed enhancing index (SEI)*
dc.subject.otherfreshwater wetland*
dc.subject.otherGF-1 satellite*
dc.subject.otherriver*
dc.titleNovel Advances in Aquatic Vegetation Monitoring in Ocean, Lakes and Rivers*
dc.typebook
oapen.identifier.doi10.3390/books978-3-03921-206-4*
oapen.relation.isPublishedBy46cabcaa-dd94-4bfe-87b4-55023c1b36d0*
oapen.relation.isbn9783039212057*
oapen.relation.isbn9783039212064*
oapen.pages132*
oapen.edition1st*


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