International Journal of Remote Sensing · 2005 · 62 citations · 13 references
Natural SciencesEarth SciencesEcologyEcosystem EcologyMarine EcologyRemote SensingLand Cover ClassificationLand Cover MappingVegetation Cover AssessmentVegetation MonitoringBenthic HabitatsBiomass MonitoringReflectanceRemote Sensing Biomass EstimationRemote Sensing Of BiomassRemote Sensing ReflectanceSupervised Classification AlgorithmsVegetation Cover Mapping
Remote sensing is a useful tool for characterizing submerged aquatic vegetation and other benthic habitats in shallow water areas with clear water transparency. In the present study, the visible bands of the Thematic Mapper (TM) sensor aboard Landsat 7 satellite were used in a supervised classification of benthic habitats and for the assessment of submerged vegetation biomass in Los Roques Archipelago National Park, Venezuela. Initially, the TM visible bands were log‐transformed and linearly combined to reduce the depth‐dependent variance in the bottom reflectance signal. The supervised classification had an overall accuracy of 74%. Eight bottom types could be spectrally separated: sand, dispersed communities over sand (shallow and deep), dense seagrass, dispersed seagrass meadows over sand, reef communities, mixed vegetation over muddy bottom, and lagoons. Regression analyses were performed between the depth‐invariant band combinations and field samples of vegetation biomass. The regression using the TM band 2 and 3 combination accounted for 64% of the variability of submerged vegetation biomass. According to these estimates, seagrass meadows with biomass between 64–96 g m−2 and 96–128 g m−2 predominate in the Los Roques Archipelago National Park.
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Photogrammetric Engineering and Remote Sensing
John Nicol, B. King · UCL Discovery (University College London) · 2007 · 9.4K citations
Ingenta · 1965 · 5.4K citations
Coral reef habitat mapping: how much detail can remote sensing provide?
Peter J. Mumby, E. P. Green, Ashley Edwards et al. · Marine Biology · 1997 · 310 citations