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Impact of Atmospheric Correction on Classification and Quantification of Seagrass Density from WorldView-2 Imagery
Citation:
Hill, V., R. Zimmerman, P. Bissett, D. Kohler, B. Schaeffer, M. Coffer, J. Li, AND K. Islam. Impact of Atmospheric Correction on Classification and Quantification of Seagrass Density from WorldView-2 Imagery. Remote Sensing. MDPI, Basel, Switzerland, 15(19):4715, (2023). https://doi.org/10.3390/rs15194715
Impact/Purpose:
Atmospheric correction methods of empirical line height and dark object subtraction were evaluated on how well a neural network classified seagrass and density from commercial satellite imagery.Accuracy in atmospheric correction was found to be not as important as precision in enabling separation of seagrass from other benthic targets. The calculation of seagrass density does require accurate atmospheric correction as under or over correction has a considerable impact on the retrieval.
Description:
Mapping the seagrass distribution and density in the underwater landscape can improve global Blue Carbon estimates. However, atmospheric absorption and scattering introduce errors in space-based sensors’ retrieval of sea surface reflectance, affecting seagrass presence, density, and above-ground carbon (AGCseagrass) estimates. This study assessed atmospheric correction’s impact on mapping seagrass using WorldView-2 satellite imagery from Saint Joseph Bay, Saint George Sound, and Keaton Beach in Florida, USA. Coincident in situ measurements of water-leaving radiance (Lw), optical properties, and seagrass leaf area index (LAI) were collected. Seagrass classification and the retrieval of LAI were compared after empirical line height (ELH) and dark-object subtraction (DOS) methods were used for atmospheric correction. DOS left residual brightness in the blue and green bands but had minimal impact on the seagrass classification accuracy. However, the brighter reflectance values reduced LAI retrievals by up to 50% compared to ELH-corrected images and ground-based observations. This study offers a potential correction for LAI underestimation due to incomplete atmospheric correction, enhancing the retrieval of seagrass density and above-ground Blue Carbon from WorldView-2 imagery without in situ observations for accurate atmospheric interference correction.
URLs/Downloads:
DOI: Impact of Atmospheric Correction on Classification and Quantification of Seagrass Density from WorldView-2 Imagery