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

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Title

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

Subject

bottom reflectance; aquatic vegetation; normalized difference vegetation index (NDVI); Lake Ulansuhai; concave–convex decision function; radiative transfer; methodological comparison; remote sensing extraction; invasive plants; CAS S. alterniflora; spectroscopy; China; nuclear power station; floating algae index (FAI); Landsat OLI; Spartina alterniflora; substrate; unmanned aerial vehicle; Lake Baikal; reflectance; 1st derivative; seaweed; remote sensing; WorldView-2; species discrimination; WorldView-3; water-column correction; Selenga River Delta; macroalgae; object-based image analysis; seaweed enhancing index (SEI); freshwater wetland; GF-1 satellite; river

Description

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.

Creator

Casado, Monica Rivas

Source

https://directory.doabooks.org/handle/20.500.12854/54860

Publisher

MDPI - Multidisciplinary Digital Publishing Institute

Date

2019

Contributor

Jadik Wijayanto

Rights

https://creativecommons.org/licenses/by-nc-nd/4.0/

Relation

https://mdpi.com/books/pdfview/book/1507

Format

PDF

Language

English

Type

Textbooks

Identifier

DOI : 10.3390/books978-3-03921-206-4
ISBN : 9783039212057, 9783039212064

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