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Spectral characterization of coastal sediments using Field Spectral Libraries,Airborne Hyperspectral Images and Topographic LiDAR Data (FHyL)
Affiliation:1. Central Scientific Research Institute of Geology of Industrial Minerals, ul. Zimina 4, Kazan, 420097, Russia;2. Kazan (Volga region) Federal University, ul. Kremlyovskaya 18, Kazan, 420008, Russia;1. Department of Geology, University of Salamanca, 37008 Salamanca, Spain;2. Institute of Earth Sciences, Université de Lausanne, CH-1015 Lausanne, Switzerland;3. Oceanología, Centro de Investigación Científica y de Educación Superior de Ensenada (CICESE), 22860 Ensenada, Mexico
Abstract:Beach dune systems are important for coastal zone ecosystems as they provide natural sea defences that dissipate wave energy. Geomorphological models of this near-shore topography require site-specific sediment composition, grain size and moisture content as inputs. Hyperspectral, field radiometry and LiDAR remote sensing can be used as tools by providing synoptic maps of these properties. However, multi-remote sensing of near-shore beach images can only be interpreted if there are adequate bio-geophysical or empirical models for information extraction. Our aim was thus to model the effects of varying sediment properties on the reflectance in both field and laboratory conditions within the FHyL (Field Spectral Libraries, Airborne Hyperspectral Images and Topographic LiDAR) procedure, using a multisource dataset (airborne Hyperspectral – MIVIS and topographic LiDAR – Hawk-eye II and field radiometry). The methodology consisted of (i) acquisition of simultaneous multi-source datasets (airborne Hyperspectral – MIVIS and topographic LiDAR – Hawk-eye) (ii) hyperspectral measurements of sediment mixtures with varying physical characteristics (moisture, grain size and minerals) in field and laboratory conditions, (iii) determination and quantification of specific absorption features, and (iv) correlation between the absorption features and physical parameters cited above.Results showed the potential of hyperspectral signals to assess the effect of moisture, grain-size and mineral composition on sediment properties.
Keywords:Hyperspectral  Linear spectral mixing analysis  Field radiometry  FHyL  Sediments  Moisture
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