Anisotropic Surface Detection Over Coastal Environment Using Near-IR LiDAR Intensity Maps

Near-IR LiDAR intensity maps have been investigated to detect surfaces characterized by spatially anisotropic properties. The developed estimators present an important sensitivity to the surface anisotropic properties (degree of anisotropy and relative anisotropy) and can be corrected for signal-to-noise ratio, which can be highly variable over coastal environments due to heterogeneous moisture distribution in space and time. Two methodologies are proposed to investigate the data in order to unambiguously characterize the surface anisotropic properties by separating the pure textural information from the amplitude weighted one, which provides a more relevant information in geomorphology than the pure texture. As an example, data acquired over sandy beaches are considered to illustrate the potential of surface characterization using both degree of anisotropy and associated texture amplitude. Sea surfaces are also investigated to show how does the pure texture approach allow to discriminate different sea states.