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Advanced Techniques for Mapping Biophysical Environments on Carbonate Banks Using Laser Airborne Depth Sounding (LADS) and IKONOS Satellite Imagery

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Remote Sensing and Modeling

Part of the book series: Coastal Research Library ((COASTALRL,volume 9))

Abstract

Mapping seafloor environments on the continental shelf, over the past several decades, has undergone rapid transitions from early, relatively low-resolution techniques, such as echo sounding in deeper waters and digital aerial photography in shallower waters, to modern advancements like high-density airborne laser bathymetry and multi-spectral satellite imagery that can now detect seafloor reflectance at depths ranging to 50–60 m. Passive imaging systems require clear waters that typically exist on carbonate banks in many regions of the world ocean. Carbonate banks in the south Florida region provide nearly ideal conditions for mapping submarine topography and interpreting geomorphological and biophysical environments. A hierarchical open-ended classification system was developed for both open-ocean and key (low carbonate islands) environments. These classification systems, which are based on cognitive recognition of seafloor features interpreted from LADS and IKONOS imagery, are directly applied in GIS cartography programs to create comprehensive, informative, and interactive products. Examples from the open ocean southeast coast and Marquesa Islands illustrate the applicability and usefulness of advanced remote sensing techniques intercalated with GIS programs and classificatory schema for organizing seafloor typologies. This new technology and its associated classification systems permit major advancements in the detailed mapping of seafloors that have never before been achieved for margins of regional seas.

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Finkl, C.W., Makowski, C., Vollmer, H. (2014). Advanced Techniques for Mapping Biophysical Environments on Carbonate Banks Using Laser Airborne Depth Sounding (LADS) and IKONOS Satellite Imagery. In: Finkl, C., Makowski, C. (eds) Remote Sensing and Modeling. Coastal Research Library, vol 9. Springer, Cham. https://doi.org/10.1007/978-3-319-06326-3_2

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