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Geospatially Integrated Seafloor Classification Scheme (G-ISCS): A New Method for Cognitively Interpreting Benthic Biogeomorphological Features

TitleGeospatially Integrated Seafloor Classification Scheme (G-ISCS): A New Method for Cognitively Interpreting Benthic Biogeomorphological Features
Publication TypeJournal Article
Year of Publication2015
AuthorsMakowski, C, Finkl, CW, Vollmer, HM
JournalJournal of Coastal ResearchJ. Coastal Res.J. Coastal Res.
KeywordsGIS and oceanography, Remote sensing, seafloor mapping, submarine geomorphology, marine biota, Florida Reef Tract, IKONOS, LADS, geographic information systems, ESRI ArcGIS

Because benthic environments show ecotonal successions that biophysically fuse geomorphological units with biological
coverages, there is a need for cognitive biogeomorphological classification methods. This study introduces a new
geospatially integrated seafloor classification scheme (G-ISCS) methodology for cognitively interpreting geomorphological
components and dominant biological covers from a variety of remotely sensed imagery within a geographic
information system interface. An ordered, hierarchical classification scheme was thus developed to discriminate various
categories such as physiographic realm, morphodynamic zone, geoform, landform, dominant surface sediment, dominant
biological cover, and density of dominant biological cover. When applying the G-ISCS method to multispectral satellite
imagery (e.g., GeoEye IKONOS-2), individual raw scenes were imported into IDRISI Taiga to enhance frequency
distributions of spectral reflectance through contrast stretching. Image enhancement was applied to blue, green, and red
wavelength bands and combined to create 24-bit color composite images that were suitable for interpretation. Using
ESRI ArcGISt ArcMap software, raster catalogs were created for enhanced imagery data sets and projected on an
interactive SmartBoardt overlay system for real-time, on-screen digitizing of seafloor feature boundaries at a nominal
scale of 1:6000. Differentiation of marine environments was based on spectral reflectance characteristics of color, tone,
saturation, pattern, and texture of the seafloor topology. Individual thematic subset maps were then created by
hierarchical category and amalgamated in ArcMap to create interactive benthic environment maps. Attribute tables
were compiled in conjugation with thematic map products to quantify relationships between mapping units, as well as to
generate accurate biogeomorphological spatial statistics. Overall, the new G-ISCS method can be applied across multiple
remote sensing platforms to cognitively delineate and interpret benthic biogeomorphological features along shelf

Short TitleJournal of Coastal ResearchJournal of Coastal Research
Alternate JournalJournal of Coastal Research