LEADER 03911nam 22008293a 450 001 9910367566303321 005 20250203235427.0 010 $a9783039212064 010 $a3039212060 024 8 $a10.3390/books978-3-03921-206-4 035 $a(CKB)4100000010106083 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/54860 035 $a(ScCtBLL)c98d42f2-ec64-4a8c-8497-6d5ac55b315b 035 $a(OCoLC)1163840316 035 $a(oapen)doab54860 035 $a(EXLCZ)994100000010106083 100 $a20250203i20192019 uu 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aNovel Advances in Aquatic Vegetation Monitoring in Ocean, Lakes and Rivers$fMonica Rivas Casado 210 $cMDPI - Multidisciplinary Digital Publishing Institute$d2019 210 1$aBasel, Switzerland :$cMDPI,$d2019. 215 $a1 electronic resource (132 p.) 311 08$a9783039212057 311 08$a3039212052 330 $aIn 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. 606 $aEnvironmental economics$2bicssc 610 $abottom reflectance 610 $aaquatic vegetation 610 $anormalized difference vegetation index (NDVI) 610 $aLake Ulansuhai 610 $aconcave?convex decision function 610 $aradiative transfer 610 $amethodological comparison 610 $aremote sensing extraction 610 $ainvasive plants 610 $aCAS S. alterniflora 610 $aspectroscopy 610 $aChina 610 $anuclear power station 610 $afloating algae index (FAI) 610 $aLandsat OLI 610 $aSpartina alterniflora 610 $asubstrate 610 $aunmanned aerial vehicle 610 $aLake Baikal 610 $areflectance 610 $a1st derivative 610 $aseaweed 610 $aremote sensing 610 $aWorldView-2 610 $aspecies discrimination 610 $aWorldView-3 610 $awater-column correction 610 $aSelenga River Delta 610 $amacroalgae 610 $aobject-based image analysis 610 $aseaweed enhancing index (SEI) 610 $afreshwater wetland 610 $aGF-1 satellite 610 $ariver 615 7$aEnvironmental economics 700 $aCasado$b Monica Rivas$01294176 801 0$bScCtBLL 801 1$bScCtBLL 906 $aBOOK 912 $a9910367566303321 996 $aNovel Advances in Aquatic Vegetation Monitoring in Ocean, Lakes and Rivers$93023039 997 $aUNINA