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• W2987335592 abstract "Submerged aquatic vegetation (SAV) comprised of mixed seagrass and algae species in shallow water has gathered more attention in recent studies at local, regional, and global scales. The objective of this research is to validate and to investigate the potential of several spectral indices for percentage of submerged aquatic vegetation cover (PSAVC) density mapping in the southwest of Arabian-Gulf. The analysis was based on Landsat-OLI data and field sampling (seabed-truth). Statistical test has been undertaken using regression analysis with a confidence interval of prediction p < 0.05. Image data were radiometrically calibrated, atmospherically corrected, as well as geometrically rectified. For validation purposes, field sampling campaign was organised simultaneously with OLI image acquisition for 55 selected sampling locations associated with shallow water areas (−0.5 to −7 m depth) with variable biomass cover. The, predicted percentage cover was derived from OLI image data and statistically validated against seabed-truth (observations) extracted from underwater vertical digital photos for each sampling location using Isodata classier. The results obtained showed that only four indices are characterized by significant fits. The best fit (R2 of 0.93) was obtained using Difference-Index exploiting the blue and green bands, followed by Simple-Ratio the VIN (R2 of 0.81), then the MNDWI (R2 of 0.76), and finally the VARI (R2 of 0.66)." @default.
• W2987335592 created "2019-11-22" @default.
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• W2987335592 date "2019-07-01" @default.
• W2987335592 modified "2023-09-23" @default.
• W2987335592 title "Mapping Submerged Aquatic Vegetation in Shallow Water of Arabian Gulf Using Water Spectral Indices, Field Observations and Landsat-OLI Data" @default.
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• W2987335592 doi "https://doi.org/10.1109/igarss.2019.8898883" @default.
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