Novel Advances in Aquatic Vegetation Monitoring in Ocean, Lakes and Rivers

In 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 approach...

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Bibliographic Details
Main Author: Casado, Monica Rivas (auth)
Format: Electronic Book Chapter
Language:English
Published: MDPI - Multidisciplinary Digital Publishing Institute 2019
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245 1 0 |a Novel Advances in Aquatic Vegetation Monitoring in Ocean, Lakes and Rivers 
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520 |a In 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. 
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650 7 |a Environmental economics  |2 bicssc 
653 |a bottom reflectance 
653 |a aquatic vegetation 
653 |a normalized difference vegetation index (NDVI) 
653 |a Lake Ulansuhai 
653 |a concave-convex decision function 
653 |a radiative transfer 
653 |a methodological comparison 
653 |a remote sensing extraction 
653 |a invasive plants 
653 |a CAS S. alterniflora 
653 |a spectroscopy 
653 |a China 
653 |a nuclear power station 
653 |a floating algae index (FAI) 
653 |a Landsat OLI 
653 |a Spartina alterniflora 
653 |a substrate 
653 |a unmanned aerial vehicle 
653 |a Lake Baikal 
653 |a reflectance 
653 |a 1st derivative 
653 |a seaweed 
653 |a remote sensing 
653 |a WorldView-2 
653 |a species discrimination 
653 |a WorldView-3 
653 |a water-column correction 
653 |a Selenga River Delta 
653 |a macroalgae 
653 |a object-based image analysis 
653 |a seaweed enhancing index (SEI) 
653 |a freshwater wetland 
653 |a GF-1 satellite 
653 |a river 
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