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Landsat 8 OLI satellite data for mapping of the Posidonia oceanica and benthic habitats of coastal ecosystems

Borfecchia, Flavio, Consalvi, Natalizia, Micheli, Carla, Carli, Filippo M., Cognetti De Martiis, Selvaggia, Gnisci, Valentina, Piermattei, Viviana, Belmonte, Alessandro, De Cecco, Luigi, Bonamano, Simone, Marcelli, Marco
International journal of remote sensing 2019 v.40 no.4 pp. 1548-1575
Landsat, Posidonia oceanica, aerosols, climate change, coasts, ecosystems, habitats, health status, leaf area index, monitoring, reflectance, remote sensing, seagrasses, Italy
The benthic seabeds and seagrass ecosystems, in particular the vulnerable Posidonia oceanica (PO), are increasingly threatened by climate change and other anthropogenic pressures. Along the 8000 km coastline of Italy, they are often poorly mapped and monitored to properly evaluate their health status. Thus to support these monitoring needs, the improved capabilities of the Landsat 8 Operational Land Imager (OLI) Earth Observation (EO) satellite system were tested for PO mapping by coupling its atmospherically corrected multispectral data with near-synchronous sea truth information. Two different approaches for the necessary atmospheric correction were exploited focusing on the Aerosol Optical Depth (AOD) and adjacency noise effects, which typically occur at land–sea interfaces. The general achievements demonstrated the effectiveness of High Resolution (HR) spectral responses captured by OLI sensor, for monitoring seagrass and sea beds in the optically complex Tyrrhenian shallow waters, with performance level dependent on the type of applied atmospheric pre-processing. The distribution of the PO leaf area index (LAI) on different substrates has been most effectively modelled using on purpose developed spectral indices. They were based on the coastal and blue-green OLI bands, atmospherically corrected using a recently introduced method for AOD retrieval, based on the Short Wave Infrared (SWIR) reflectance. The alternative correction method including a less effective AOD assessment but the removal of adjacency effects has proven its efficacy for improving the thematic discriminability of the seabed types characterized by different PO cover–substrate combinations.